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Rationale and Objectives: This study explores morphological relationships and structural variability of the corpus callosum (CC), fornix (Fo), anterior (AC), and posterior commissures (PC)., Materials and Methods: These structures are extracted automatically on the midsagittal plane. The CC and Fo are modeled using best-fit ellipses. The parameters characterizing these structures and relationships among them are points, distances, angles, and eccentricities. The minimum, maximum and mean values, standard deviations, and coefficients of variation for all parameters are calculated for 62 diversified MRI datasets. Subsequently, the regression analysis and parameter distribution study are performed., Results: The parameters have at least 10% variations. The major axis of CC and eccentricities of CC and Fo vary much less than the other parameters The major axis of CC is approximately parallel to the AC-PC line. The mean eccentricity of each of CC and Fo is greater than 0.95. The most significant correlation (P < .05) is observed between various angles and the angle between the major axes of CC and Fo. The correlation is also significant between other angles and distances. The Weibull distribution characterizes the major axis of CC, and distance between the AC and the most superior point of CC. Distribution of angle between the major axes of CC and Fo is log (logistic), and normal for the AC-PC distance., Conclusions: The AC-PC distance, used prevalently for brain normalization, is not correlated with any parameters except with the distance between the AC and the most superior point on the body of the CC with P < .05.

Stereotactic human brain atlases, either in print or electronic form, are useful not only in functional neurosurgery, but also in neuroradiology, human brain mapping, and neuroscience education. The existing atlases represent structures on 2D plates taken at variable, often large intervals, which limit their applications. To overcome this problem, we propose a hybrid interpolation approach to build high-resolution brain atlases from the existing ones. In this approach, all section regions of each object are grouped into two types of components: simple and complex. A NURBS-based method is designed for interpolation of the simple components, and a distance map-based method for the complex components. Once all individual objects in the atlas are interpolated, the results are combined hierarchically in a bottom-up manner to produce the interpolation of the entire atlas. In the procedure, different knowledge-based and heuristic strategies are used to preserve various topological relationships. The proposed approach has been validated quantitatively and used for interpolation of two stereotactic brain atlases: the Talairach-Tournoux atlas and Schaltenbrand-Wahren atlas. The interpolations produced are of high resolution and feature high accuracy, 3D consistency, smooth surface, and preserved topology. They potentially open new applications for electronic stereotactic brain atlases, such as atlas reformatting, accurate 3D display, and 3D nonlinear warping against normal and pathological scans. The proposed approach is also potentially useful in other applications, which require interpolation and 3D modeling from sparse and/or variable intersection interval data. An example of 3D modeling of an infarct from MR diffusion images is presented.

Rationale and Objective: Accurate identification of the anterior commissure (AC) and posterior commissure (PC) is critical in neuroradiology, functional neurosurgery, human brain mapping, and neuroscience research. Moreover, major stereotactic brain atlases are based on the AC and PC. Our goal is to provide an algorithm for a rapid, robust, accurate and automatic identification of AC and PC., Materials and Method: The method exploits anatomical and radiological properties of AC, PC and surrounding structures, including morphological variability. The localization is done in two stages: coarse and fine. The coarse stage locates the AC and PC on the midsagittal plane by analyzing their relationships with the corpus callosum, fornix, and brainstem. The fine stage refines the AC and PC in a well-defined volume of interest, analyzing locations of lateral and third ventricles, interhemispheric fissure, and massa intermedia., Results: The algorithm was developed using simple operations, like histogramming, thresholding, region growing, 1D projections. It was tested on 94 diversified T1W and SPGR datasets. After the fine stage, 71 (76%) volumes had an error between 0-1 mm for the AC and 55 (59%) for the PC. The mean errors were 1.0 mm (AC) and 1.0 mm (PC). The accuracy has improved twice due to fine stage processing. The algorithm took about 1 second for coarse and 4 seconds for fine processing on P4, 2.5 GHz., Conclusion: The use of anatomical and radiological knowledge including variability in algorithm formulation aids in localization of structures more accurately and robustly. This fully automatic algorithm is potentially useful in clinical setting and for research.

The major shortcomings of the Schaltenbrand-Wahren (SW) brain atlas include 3-dimensional (3D) inconsistency and spatial sparseness. This work quantifies and visualizes 3D inconsistency of the globus pallidus internus (GPi), a stereotactic target for the treatment of Parkinson's disease, dystonia and Huntington disease. The GPi 3D models 3D-A, 3D-C and 3D-S are reconstructed from the SW axial, coronal and sagittal microseries, respectively, by applying a shape-based (Nonuniform Rational B Splines) method. All three 3D models, placed in the SW coordinate system, are compared quantitatively in terms of location (centroids), size (volumes), shape (normalized eigen values), orientation (eigen vectors) and mutual spatial relationships (overlaps and inclusions). The analysis is done in 3D within each orientation and across them. The reconstructed 3D GPi models substantially differ in location, size and inclusion rate. The centroid of 3D-C is located more medially (15.6 mm) than those of 3D-A (17.5 mm) and 3D-S (18.2 mm), and that of 3D-A more ventrally (-2.3 mm) than those of 3D-C (-0.1 mm) and 3D-S (-0.4 mm). 3D-S has the smallest volume (347.3 mm3); 3D-A is 1.18 and 3D-C 1.85 times larger. The highest inclusion rate is for 3D-S (54.3 and 56.3%) and the lowest for 3D-C (28.8 and 30.6%). A smaller variability is observed in shape, orientation and overlap size (196.8, 196.1 and 185.5 mm3). To get a better correspondence between 3D-C and 3D-S, the coronal microseries were scaled laterally by 1.1667. This results in a substantial improvement of the inclusion rate of 3D-S (87.9%), though raising the volume mismatch to 2.16. The GPi in the SW atlas has a substantial 3D inaccuracy within each orientation and across them. Therefore, absolute and direct reliance on the original atlas is unsafe, and this atlas has to be used with great care and understanding of its limitations. As matching various SW microseries by global scaling is not feasible, we propose the target-dependent scaling based on structure centroid matching., (Copyright 2006 S. Karger AG, Basel.)

In this paper, we propose a knowledge-driven highly automatic methodology for extracting the masseter from magnetic resonance (MR) data sets for clinical purposes. The masseter is a muscle of mastication which acts to raise the jaw and clench the teeth. In our initial work, we designed a process which allowed us to perform 2-D segmentation of the masseter on 2-D MR images. In the methodology proposed here, we make use of ground truth to first determine the index of the MR slice in which we will carry out 2-D segmentation of the masseter. Having obtained the 2-D segmentation, we will make use of it to determine the region of interest (ROI) of the masseter in the other MR slices belonging to the same data set. The upper and lower thresholds applied to these MR slices, for extraction of the masseter, are determined through the histogram of the 2-D segmented masseter. Visualization of the 3-D masseter is achieved via volume rendering. Our methodology has been applied to five MR data sets. Validation was done by comparing the segmentation results obtained by using our proposed methodology against manual contour tracings, obtaining an average accuracy of 83.5%

A novel thresholding approach to confine the intensity frequency range of the object based on supervision is introduced. It consists of three steps. First, the region of interest (ROI) is determined in the image. Then, from the histogram of the ROI, the frequency range in which the proportion of the background to the ROI varies is estimated through supervision. Finally, the threshold is determined by minimizing the classification error within the constrained variable background range. The performance of the approach has been validated against 54 brain MR images, including images with severe intensity inhomogeneity and/or noise, CT chest images, and the Cameraman image. Compared with nonsupervised thresholding methods, the proposed approach is substantially more robust and more reliable. It is also computationally efficient and can be applied to a wide class of computer vision problems, such as character recognition, fingerprint identification, and segmentation of a wide variety of medical images.

A new method has been developed for multimedia enhancement of electronic teaching files created by using the standard protocols and formats offered by the Medical Imaging Resource Center (MIRC) project of the Radiological Society of North America. The typical MIRC electronic teaching file consists of static pages only; with the new method, audio and visual content may be added to the MIRC electronic teaching file so that the entire image interpretation process can be recorded for teaching purposes. With an efficient system for encoding the audiovisual record of on-screen manipulation of radiologic images, the multimedia teaching files generated are small enough to be transmitted via the Internet with acceptable resolution. Students may respond with the addition of new audio and visual content and thereby participate in a discussion about a particular case. MIRC electronic teaching files with multimedia enhancement have the potential to augment the effectiveness of diagnostic radiology teaching., (RSNA, 2005.)

The Talairach transformation (TT), the most prevalent method for brain normalization and atlas-to-data warping, is conceptually simple, fast and can be automated. Two problems with the TT in the clinical setting that are addressed in this article are reduced accuracy at the orbitofrontal cortex and upper corpus callosum (CC) and unsuitability for functional neurosurgery because of incomplete scanning. To increase dorsoventral accuracy, we introduce 2 additional landmarks: the top of the CC (SM) and the most ventral point of the orbitofrontal cortex on the midsagittal slab (IM). A method for their automatic calculation is proposed and validated against 55 diversified magnetic resonance (MR) imaging cases. The SM and IM landmarks are identified accurately and robustly in an automatic way. The average error of SM localization is 0.69 mm, and 91% of all cases have an error not greater than 1 mm. The average error of IM localization is 0.98 mm, approximately three quarters of cases have an error not greater than 1 mm, and 95% of all cases have an error not larger than 2 mm. The SM is correlated (R(2) = 0.72) with the most superior cortical landmark, whereas the IM is only loosely correlated (R(2) = 0.22) with the most inferior cortical landmark. On average, the original TT overlays the atlas axial plate at -24 on the orbitofrontal cortex as opposed to the correct plate at -28. Therefore, 1-dimensional ventral scaling in the original TT is insufficient to cope with variability in the orbitofrontal cortex. The key advantages of our approach are the preserved conceptual simplicity of the TT, fully automatic identification of the new landmarks, improved accuracy of the atlas-to-data match without compromising performance, and enabled TT use in functional neurosurgery when a dorsal part of the brain is not available in the scan.

Objective: Statistical analysis of patients previously operated on may improve our methods of performing subsequent surgical procedures. In this article, we introduce a method for studying the functional properties of cerebral structures from electrophysiological and neuroimaging data by using the probabilistic functional atlas (PFA). The PFA provides a spatial distribution of the clinically most effective contacts normalized to a common space. This distribution is converted into a probability function for a given point in space to be inside an effective contact. The PFA was used to analyze spatial properties of the functional subthalamic nucleus (STN), defined as the spatial volume corresponding to the distribution of effective contacts. These results may potentially be useful in planning subthalamic implantation of electrodes., Methods: In all, 168 bilateral subthalamic stimulations were examined. An algorithm was developed for converting these data into the PFA. The PFA for the STN (here called "atlas") was calculated with 0.25-mm3 resolution, and several features characterizing the left and right STN were studied. The analysis was performed with and without lateral compensation against the width of the third ventricle. The key feature introduced here used for analysis of the functional STN is a (probabilistic) functional volume of structure (defined for a given probability as the volume of a region whose every point has a probability equal to or greater than this given probability)., Results: The analysis has been performed for two situations: with and without lateral compensation against the width of the third ventricle. Without lateral compensation, the differences between the mean values and standard deviations of their barycenter coordinates for the left and right functional STNs are 0.31 and 0.18 mm, respectively. The left STN and right STN exhibit differences in functional volume size and probability distribution. The entire functional volume is 240 mm3 for the left and 229 mm3 for the right STN. A more prominent difference exists in the region of high probabilities (0.7 or higher), called "hot STN." The volume of the left hot STN is 5.52 mm3, whereas that of the right is 3.92 mm3. The left hot STN is 1.41 times bigger and 20% more dense than the right hot STN. For a given probability, the corresponding functional volume for the left hot STN is up to 43 times larger than that for the right STN. Practically speaking, lateral compensation does not change these results qualitatively. Quantitatively, differentiation between the left and right STNs is lower. For instance, for a given probability, the corresponding functional volume for the left hot STN is only up to 11 times larger than that for the right one. In either situation (i.e., with and without lateral compensation), the size of the hot STN in relation to the whole STN remains very small (1-2%). In addition, statistical analysis shows that in either situation, the means of the left and right functional STNs are significantly different., Conclusion: PFA-based planning may be superior to the current practice of using anatomic atlases that provide delineation of the target structure only, because it is more precise and provides a unique target point in the stereotactic space. This best stereotactic target is the point in the individualized atlas with the highest probability, meaning the highest probability of having the best target on the basis of the patients previously operated on. This best target is located in the hot STN, the size of which determines the precision of targeting. Because the size of the hot STN in comparison to the whole STN remains very small (1-2%) independent of whether or not lateral compensation is applied, target planning and execution have to be performed with high precision. The methodology presented, based on the PFA and on the functional volume, is general and can be applied to other structures and data sets. As numerous centers keep gathering large amounts of electrophysiological human and animal data, this work may facilitate opening new avenues in exploiting these data.

Rationale and Objectives: Determination of distorted brain anatomy surrounding a tumor causing a mass effect is much more difficult than interpretation of normal brain scans, particularly because this distortion is not easily predictable a tumor may be located in any place and vary substantially in size, shape, and radiological appearance. The objective of our work is to provide a qualitative means for rapid estimation of brain anatomy distorted by tumor., Materials and Methods: Toward achieving this objective, we use an electronic and deformable brain atlas of gross anatomy along with a fast atlas-to-data warping technique. The deformed atlas determines the distorted anatomy surrounding a tumor and can be used for structure labeling (naming). The warping algorithm uses the Talairach transformation followed by three-dimensional nonlinear tumor deformation based on a geometric assumption that the tumor, delineated on radiological images, compresses its surrounding tissues radially., Results: The approach is implemented and a dedicated application is developed. It processes the data automatically in five steps: (1) load data, (2) set the Talairach landmarks and perform the Talairach transformation, (3) segment the tumor, (4) warp the scan nonlinearly in three dimensions, and (5) explore the scan. The approach is very fast, and a magnetic resonance imaging scan is processed in 10-15 seconds on a standard personal computer. It is fully automatic and gives the user control over the entire process., Conclusion: Despite its limitations in modeling and validation, this practical solution provides a rapid and potentially useful qualitative assessment of anatomy deformed by a mass effect tumor.

We propose an anatomy-based approach for an efficient construction of a three-dimensional human normal cerebral arterial model from segmented and skeletonized angiographic data. The centerline-based model is used for an accurate angiographic data representation. A vascular tree is represented by tubular segments and bifurcations whose construction takes into account vascular anatomy. A bifurcation is defined quantitatively and the algorithm calculating it is given. The centerline is smoothed by means of a sliding average filter. As the vessel radius is sensitive to quality of data as well as accuracy of segmentation and skeletonization, radius outlier removal and radius regression algorithms are formulated and applied. In this way, the approach compensates for some inaccuracies introduced during segmentation and skeletonization. To create the frame of vasculature, we use two different topologies: tubular and B-subdivision based. We also propose a technique to prevent vessel twisting. The analysis of the vascular model is done on a variety of data containing 258 vascular segments and 131 bifurcations. Our approach gives acceptable results from anatomical, topological and geometrical standpoints as well as provides fast visualization and manipulation of the model. The approach is applicable for building a reference cerebrovascular atlas, developing applications for simulation and planning of interventional radiology procedures and vascular surgery, and in education.

The Talairach transformation is the most prevalent way to normalize brains and is hindered by, among others things, a lack of automatic determination of cortical landmarks. An algorithm to locate the modified Talairach cortical landmarks in three steps is proposed: determination of the three planes containing the landmarks; segmentation of the planes based on range-constrained thresholding and morphologic operations; and local refinement of the segmentation to locate the landmarks. The algorithm has been validated against 62 T(1)-weighted and SPGR MR diversified data sets. For each data set, it takes less than 2 s on a Pentium 4 to extract all six landmarks. The average landmark location errors are below 0.9 mm. The algorithm is robust due to incorporation of anatomic knowledge. A low computational cost results from processing of three 2D images and employing only simple operations like thresholding, basic morphologic operations, and distance transform., (Copyright 2005 Wiley-Liss, Inc.)

Of the existing atlases of the brain anatomy and cerebrovasculature, none integrates the anatomy and vasculature by providing for direct manipulation of three-dimensional (3D) cerebral models. An atlas-based application was developed in four steps: (a) construction of 3D anatomic models, (b) construction of 3D vascular models, (c) interactive spatial coregistration of the anatomic and vascular models, and (d) development of functionality and a user interface for the application. Three-dimensional anatomic models were imported from an electronic brain atlas database derived from classic print atlases. A novel vascular modeling technique was developed and applied to create a vascular atlas from magnetic resonance angiographic data. The use of 3D polygonal models allows smooth navigation (rotation, zooming, panning) and interactive labeling of anatomic structures and vascular segments. This application enables the user to examine 3D anatomic structures and 3D cerebral vasculature and to gain a better understanding of the relationships between the two. The combined anatomic-vascular atlas is a user-friendly neuroeducational tool that is useful for medical students and neuroscience researchers as well as for educators in preparing teaching materials., ((c) RSNA, 2005.)

We have previously introduced a concept of a probabilistic functional atlas (PFA) to overcome limitations of the current electronic stereotactic brain atlases: anatomical nature, spatial sparseness, inconsistency and lack of population information. The PFA for the STN has already been developed. This work addresses construction of the PFA for the ventrointermediate nucleus (PFA-VIM). The PFA-VIM is constructed from pre-, intra- and postoperative electrophysiological and neuroimaging data acquired during the surgical treatment of Parkinson's disease patients. The data contain the positions of the chronically implanted electrodes and their best contacts. For each patient, the intercommissural distance, height of the thalamus and width of the third ventricle were measured. An algorithm was developed to convert these data into the PFA-VIM, and to present them on axial, coronal and sagittal planes and in 3-D. The PFA-VIM gives a spatial distribution of the best contacts, and its probability is proportional to best contact concentration in a given location. The region with the highest probability corresponds to the best target. The PFA-VIM is calculated with 0.25-mm3 resolution from 107 best contacts in two situations: with and without lateral compensation against the width of the third ventricle. For the PFA-VIM compensated laterally, the anterior, lateral and dorsal coordinates of the mean value are (in mm) 6.24, 13.83, 1.68 for the left VIM and 6.54, -13.84, 2.10 for the right VIM. The coordinates of the mean value of the highest probability region along with the highest number of the best contacts (P) are: 6.25, 14.25, 1.75, P = 16, for the left VIM, and 6.0, -14.0, 1.00, P = 18, for the right VIM. The coordinate system origin is at the posterior commissure. For the PFA-VIM not compensated laterally, the coordinates of the mean value are 6.24, 13.99, 1.68 for the left VIM and 6.53, -14.13, 2.10 for the right VIM. The coordinates of the mean value of the highest probability region along with the highest number of the best contacts are 5.58, 13.67, 1.33, P = 14, for the left VIM, and 6.36, -14.03, 1.11, P = 17, for the right VIM. The PFA-VIM atlas overcomes several limitations of the current anatomical atlases and can improve targeting of thalamotomies and thalamic stimulations. It is dynamic and can easily be extended with new cases., (2005 S. Karger AG, Basel.)

The Talairach-Tournoux (TT) atlas is probably the most often used brain atlas. We overview briefly the activities in developments of electronic versions of the TT atlas and focus on our more than 10-yr efforts in its continuous enhancement resulting in three main versions: TT-1997, TT-2000, and TT-2004. The recent TT-2004 version is substantially improved over the digitized print original with a higher structure parcellation, better quality and resolution of individual structures, and improved three-dimensional (3D) spatial consistency. It is also much more suitable for developing atlas-based applications owing to pure color-coding (for automatic structure labeling), contour representation (to avoid scan blocking by the overlaid atlas), and color cross-atlas consistency (for the simultaneous use of multiple atlases). We also provide a procedure for 3D spatial consistency improvement and illustrate its use. Finally, we present some of our latest atlas-assisted applications for fast and automatic interpretation of morphological, stroke, and molecular images, and discuss the future steps in TT atlas enhancement.

This paper introduces a method for generation and validation of a probabilistic functional brain atlas of subcortical structures from electrophysiological and neuroimaging data. The method contains three major steps: (1) acquisition of pre, intra, and postoperative multimodal data; (2) selection of an accurate data set for atlas generation; and (3) generation of the atlas from the selected data set. The method is applied to construct the probabilistic functional atlas of the human subthalamic nucleus (STN). The STN atlas has been built from data collected during surgical treatment of 184 patients with Parkinson's disease. It is based on preoperative X-ray ventriculography imaging, intraoperative electrophysiological measurements and X-ray imaging, and postoperative neurological assessment. The atlas features a high resolution of 0.25 mm(3) and a high accuracy of 0.25 mm. It is dynamic and can be rapidly recalculated for arbitrary resolution and extended by adding new patient data. The atlas can easily be reformatted and warped to match patient-specific data. Its applications include planning of subthalamic stimulations and neuroscience research to study functional properties of the STN. The presented method is general and can be applied for constructing human and animal probabilistic brain atlases.

A knowledge-driven algorithm for a rapid, robust, accurate, and automatic extraction of the human cerebral ventricular system from MR neuroimages is proposed. Its novelty is in combination of neuroanatomy, radiological properties, and variability of the ventricular system with image processing techniques. The ventricular system is divided into six 3D regions: bodies and inferior horns of the lateral ventricles, third ventricle, and fourth ventricle. Within each ventricular region, a 2D region of interest (ROI) is defined based on anatomy and variability. Each ventricular region is further subdivided into subregions, and conditions detecting and preventing leakage into the extra-ventricular space are specified for each subregion. The algorithm extracts the ventricular system by (1) processing each ROI (to calculate its local statistics, determine local intensity ranges of cerebrospinal fluid and gray and white matters, set a seed point within the ROI, grow region directionally in 3D, check anti-leakage conditions, and correct growing if leakage occurred) and (2) connecting all unconnected regions grown by relaxing growing conditions. The algorithm was validated qualitatively on 68 and quantitatively on 38 MRI normal and pathological cases (30 clinical, 20 MGH Brain Repository, and 18 MNI BrainWeb data sets). It runs successfully for normal and pathological cases provided that the slice thickness is less than 3.0 mm in axial and less than 2.0 mm in coronal directions, and the data do not have a high inter-slice intensity variability. The algorithm also works satisfactorily in the presence of up to 9% noise and up to 40% RF inhomogeneity for the BrainWeb data. The running time is less than 5 s on a Pentium 4, 2.0 GHz PC. The best overlap metric between the results of a radiology expert and the algorithm is 0.9879 and the worst 0.9527; the mean and standard deviation of the overlap metric are 0.9723 and 0.01087, respectively.

Objective: The Schaltenbrand-Wahren atlas (SWA) is anatomical, sparse and inconsistent in three dimensions. A high-resolution, electrophysiology-based atlas derived from numerous specimens overcomes these limitations. A combined anatomy-physiology atlas leverages the strengths and complementarity of both, which is studied here., Method: An electronic version of the SWA was constructed. A probabilistic functional atlas (PFA) was developed from electrophysiological and neuroimaging data with 0.25 mm3 resolution. A combined atlas is constructed by co-registering the PFA with the SWA by applying linear scaling along the intercommissural distance and the height of the thalamus., Results: An anatomy-physiology atlas is superior to its component atlases. When in register, the anatomical and functional atlases are displayed together and used simultaneously. A structure of interest from the PFA can be displayed with high resolution, compensating for its sparseness in the SWA, while its surrounding structures are obtained from the SWA. The best anatomical and functional targets can be compared: for the subthalamic nucleus, the horizontal and lateral coordinates of the SWA-based and PFA- based targets are approximately the same, while the latter is located 1.3-1.5 mm more anteriorly., Conclusion: An anatomy-physiology atlas may enhance the accuracy of targeting and increase the neurosurgeon's confidence. It also opens new research avenues to serve as a reference for: (1) constructing an extendable atlas by adding new electrophysiological data, (2) comparing anatomical and functional targets, (3) studying and comparing various symptoms, and (4) comparing image-based targets obtained from various modalities., (2004 S. Karger AG, Basel.)

A rapid algorithm for robust, accurate, and automatic extraction of the midsagittal plane (MSP) of the human cerebrum from normal and pathological neuroimages is proposed. The MSP is defined as a plane formed from the interhemispheric fissure line segments having the dominant orientation. The algorithm extracts the MSP in four steps: (1) determine suitable axial slices for processing, (2) localize the fissure line segments on them, (3) select inliers from the extracted fissure line segments through histogram-based outlier removal, and (4) calculate the equation of the MSP from the selected inliers. The fissure line segments are localized by minimizing the local symmetry index characterizing anatomical properties of images in the vicinity of the interhemispheric fissure. A two-stage angular and distance outlier removal is introduced to handle abnormalities. The algorithm has been validated quantitatively with 125 structural MRI and CT cases from 10 centers on three continents by studying its accuracy; tolerance to rotation, noise, asymmetry, and bias field; sensitivity to parameters; and performance. A statistical relationship between algorithm accuracy and the data's adherence to planarity is also determined. The algorithm extracts the MSP below 6 s on Pentium 4 (2.4 GHz) with the average angular and distance errors of (0.40 degrees; 0.63 mm) for normal and (0.59 degrees; 0.73 mm) for pathological cases. The robustness to noise, asymmetry, rotation, and bias field is achieved by extracting the MSP based on the dominant orientation and local symmetry index. A low computational cost results from applying simple operations capturing intrinsic anatomic features, constraining the searching space to the local vicinity of the interhemispheric fissure, and formulating a noniterative algorithm with a coarse and fine fixed-step searching. In comparison to the existing methods, our algorithm is much faster, performs accurately and robustly for a wide range of diversified data, and is fully automatic and thoroughly validated, which make it suitable for clinical applications.

The article introduces an atlas-assisted method and a tool called the Cerefy Neuroradiology Atlas (CNA), available over the Internet for neuroradiology and human brain mapping. The CNA contains an enhanced, extended, and fully segmented and labeled electronic version of the Talairach-Tournoux brain atlas, including parcelated gyri and Brodmann's areas. To our best knowledge, this is the first online, publicly available application with the Talairach-Tournoux atlas. The process of atlas-assisted neuroimage analysis is done in five steps: image data loading, Talairach landmark setting, atlas normalization, image data exploration and analysis, and result saving. Neuroimage analysis is supported by a near-real-time, atlas-to-data warping based on the Talairach transformation. The CNA runs on multiple platforms; is able to process simultaneously multiple anatomical and functional data sets; and provides functions for a rapid atlas-to-data registration, interactive structure labeling and annotating, and mensuration. It is also empowered with several unique features, including interactive atlas warping facilitating fine tuning of atlas-to-data fit, navigation on the triplanar formed by the image data and the atlas, multiple-images-in-one display with interactive atlas-anatomy-function blending, multiple label display, and saving of labeled and annotated image data. The CNA is useful for fast atlas-assisted analysis of neuroimage data sets. It increases accuracy and reduces time in localization analysis of activation regions; facilitates to communicate the information on the interpreted scans from the neuroradiologist to other clinicians and medical students; increases the neuroradiologist's confidence in terms of anatomy and spatial relationships; and serves as a user-friendly, public domain tool for neuroeducation. At present, more than 700 users from five continents have subscribed to the CNA.

Object: Functional imaging is an established neurosurgical modality for studying the brain in health and disease. Identifying numerous activation loci on many functional images and reading their underlying cortical and subcortical anatomy, coordinates, and anatomical and functional values is a tedious, time-consuming, and error-prone task. In this study the authors propose a novel approach to this problem by using an electronic brain atlas in conjunction with a locus-driven mechanism., Methods: The Brain Atlas for Functional Imaging containing an enhanced and extended electronic version of the Talairach-Tournoux brain atlas was used for analysis. It enables loading of anatomical and functional data, correlation of these data, identification of activation loci, and their labeling with Brodmann areas, gyri, and subcortical structures by means of the atlas. The Talairach proportional grid system transformation is used to register the anatomical and functional data with the atlas. The availability of numerous tools supports this process. A locus-driven mechanism for analysis of activation loci is implemented. Locus placement within the activation region is supported by thresholding, and its location can be further edited in three dimensions on any orthogonal plane. Once all loci are identified and edited, their labels, coordinates, and anatomical/functional values are read automatically and saved in an external file. This mechanism enables the analysis to be performed in an automated, rapid, explicit, three-dimensionally consistent, and user-friendly way., Conclusions: The electronic brain atlas with locus-driven mechanism is a useful tool for localization analysis of functional images.

This work presents an efficient and automated method to extract the human cerebral ventricular system from MRI driven by anatomic knowledge. The ventricular system is divided into six three-dimensional regions; six ROIs are defined based on the anatomy and literature studies regarding variability of the cerebral ventricular system. The distribution histogram of radiological properties is calculated in each ROI, and the intensity thresholds for extracting each region are automatically determined. Intensity inhomogeneities are accounted for by adjusting intensity threshold to match local situation. The extracting method is based on region-growing and anatomical knowledge, and is designed to include all ventricular parts, even if they appear unconnected on the image. The ventricle extraction method was implemented on the Window platform using C++, and was validated qualitatively on 30 MRI studies with variable parameters.

The paper introduces an optimal algorithm for rapid calculation of a probabilistic functional atlas (PFA) of subcortical structures from data collected during functional neurosurgery procedures. The PFA is calculated based on combined intraoperative electrophysiology, pre- and intraoperative neuroimaging, and postoperative neurological verification. The algorithm converts the coordinates of the neurologically most effective contacts into probabilistic functional maps taking into account the geometry of a stimulating electrode. The PFA calculation comprises the reconstruction of the contact coordinates from two orthogonal projections, normalizing (warping) the contacts modeled as cylinders, voxelizing the contact models, calculating the atlas, and computing probability. In addition, an analytical representation of the PFA is formulated based on Gaussian modeling. The initial PFA has been calculated from the data collected during the treatment of 274 Parkinson's disease patients, most of them operated bilaterally (487 operated hemispheres). It contains the most popular stereotactic targets, the subthalamic nucleus, globus pallidus internus, and ventral intermedius nucleus. The key application of the algorithm is targeting in stereotactic and functional neurosurgery, and it also can be employed in human and animal brain research.

A PC based system for simulating image-guided interventional neuroradiological procedures for physician training and patient specific pretreatment planning is described. The system allows physicians to manipulate and interface interventional devices such as catheters, guidewires, stents and coils within 2-D and hybrid surface and volume rendered 3-D patient vascular images in real time. A finite element method is employed to model the interaction of the catheters and guidewires with the vascular system. Fluoroscopic, roadmapping and volume rendered 3-D presentations of the vasculature are provided. System software libraries allow for the use of commonly employed catheters, guidewires, stents and occluding coils of various shapes and sizes. The results of an initial clinical validation suggest that the experience gained from our simulator is comparable with that of using a vascular phantom. We are conducting further validation with the aim of providing patient specific pretreatment planning.

Objective: This paper describes an Internet portal for stereotactic and functional neurosurgery with a probabilistic functional atlas (PFA) calculated from electrophysiological and neuroimaging data. This portal enables (1) data sharing among neurosurgeons; (2) the calculation of probabilistic functional maps of stereotactic target structures from a neurosurgeon's own data, optionally combined with data from other neurosurgeons, and (3) the construction and development of a PFA of the human brain by the neurosurgical community via the Internet., Method: The overall approach is done in three steps: (1) development and validation of the algorithm for PFA generation; (2) design and development of the portal for stereotactic and functional neurosurgery with tools for the rapid calculation, presentation, and use of the PFA, and (3) portal testing with the initial data acquired for 274 Parkinson's disease patients, 487 hemispheres, and 500 best contacts. This paper covers step 2 and some results from step 3., Results: The Internet portal has been developed in Java and tested with the available data. Functions have been developed for: (1) data input, transfer, and editing; (2) data selection for PFA generation; (3) PFA generation; (4) PFA display and interactive manipulation, and (5) target planning. The portal has been put on the Internet for public use and so far more than 100 users downloaded it., Conclusion: The Internet portal for stereotactic and functional neurosurgery with a PFA potentially increases both the accuracy of targeting and the neurosurgeon's confidence. The portal may be useful for both experienced functional neurosurgeons who have studied numerous cases and novices in the field. The use of the PFA through this portal, and sharing and expanding its content by neurosurgeons represents a paradigm shift from manufacturer centric to community centric., (Copyright 2002 S. Karger AG, Basel)

In this paper, a novel non-rigid registration method is proposed for registration of the Talairach-Tournoux brain atlas with MRI images and the Schaltenbrand-Wahren brain atlas. A metalforming principle-based finite element method with the large deformation problem is used to find the local deformation, in which finite element equations are governed by constraints in the form of displacements derived from the correspondence relationship between extracted feature points. Some detectable substructures, such as the cortical surface, ventricles and corpus callosum, are first extracted from MRI, forming feature points which are classified into different groups. The softassign method is used to establish the correspondence relationship between feature points within each group and to obtain the global transformation concurrently. The displacement constraints are then derived from the correspondence relationship. A metalforming principle-based finite element method with the large deformation problem is used in which finite element equations are reorganized and simplified by integrating the displacement constraints into the system equations. Our method not only matches the model to the data efficiently, but also decreases the degrees of freedom of the system and consequently reduces the computational cost. The method is illustrated by matching the Talairach-Tournoux brain atlas to MRI normal and pathological data and to the Schaltenbrand-Wahren brain atlas. We compare the results quantitatively between the force assignment-based method and the proposed method. The results show that the proposed method yields more accurate results in a fraction of the time taken by the previous method.

Background: Brain atlas-assisted operations, such as targeting in stereotactic and functional neurosurgery, localisation analysis and metanalysis in human brain mapping, or structure segmentation and labelling in neuroradiology, highly depend on the accurate localisation of the landmarks used for atlas-to-data registration. One of practical and widely used registration methods is the Talairach proportional grid system transformation based on the Talairach landmarks. However, there are several problems associated with the original Talairach landmarks. In the Talairach-Tournoux brain atlas, some Talairach landmarks are not available and locations of others contradict their definitions. When dealing with patient-specific data, the definitions of the Talairach landmarks are not constructive enough or make their identification time consuming. Moreover, there is an inconsistency between the Talairach landmarks and Talairach grid., Method: The modified Talairach landmarks, conceptually equivalent to the original Talairach landmarks, are introduced here. They have several advantages and overcome some limitations of the original Talairach landmarks. Three various intercommissural distances are defined: central, internal, and tangential, and the formulas determining their lengths and errors associated are derived. An efficient method for calculating the modified cortical landmarks is proposed., Findings: The internal intercommissural distance is the closest to the original Talairach intercommissural distance. Its relative intercommissural error is only 0.5%, as opposed to the central and tangential intercommissural distances resulting in high (about 10%) relative intercommissural errors. On the other hand, the internal and central intercommissural distances result in a high maximum displacement error at cortex amounting to about 11 mm while the tangential intercommissural distance gives only 1 mm error. The sensitivity of the internal intercommissural distance to the actual location of the intercommissural plane is high reaching above 10%. On the other hand, the sensitivity of the central intercommissural distance is below 0.5%. Each of the Talairach cortical landmarks needs three coordinates for its identification that requires the availability of two two-dimensional projections, the generation and analysis of which is computationally expensive. A modified cortical landmark is identified on a single, one-dimensional projection., Interpretation: The modified Talairach landmarks facilitate the rapid and automated calculation of the Talairach transformation and give more flexibility in their use for specific applications. In stereotactic and functional neurosurgery, the internal intercommissural distance is the most suitable to provide a high accuracy for subcortical structures. In localisation analysis in human brain mapping research, a high accuracy has to be achieved at the cortex and the tangential intercommissural line is superior. Human brain mapping metanalysis may benefit from the use of the central intercommissural distance minimising errors due to the intercommissural plane positioning. In neuroradiology, a high accuracy is required both for subcortical and cortical structures and the tangential intercommissural line should be used.

Objective: This paper introduces a method for localization analysis of functional images assisted by a brain atlas. The usefulness of the system developed, based on this method, is analyzed for human brain mapping and neuroradiology., Materials and Methods: We use an enhanced and extended electronic Talairach-Tournoux brain atlas, containing segmented and labeled subcortical structures, Brodmann's areas, and gyri. The brain atlas serves as a tool for anatomy referencing, segmentation, labeling, registration, and providing 3D anatomical relationships. The process of localization analysis is decomposed into five steps: data loading, feature extraction, data normalization, identification and editing of loci, and getting labels and values. This analysis is supported by near real-time data-to-atlas warping based on the Talairach transformation. Metanalysis is enabled by merging the current and external lists of activation loci., Results: We have designed, developed, tested, and deployed a commercial system for atlas-assisted localization analysis of functional images. This is the first system where an electronic version of the Talairach-Tournoux brain atlas is used interactively for analysis of functional images. This system runs on personal computers and provides functions for a rapid normalization of anatomical and functional volumetric data, data segmentation and labeling, readout of Talairach coordinates, and data display. It also is empowered with several unique features including: interactive warping facilitating fine tuning of the data-to-atlas fit, a backtracking mechanism to compensate for missing landmarks and enhancing the outcome of the overall process of data analysis, navigation on the triplanar formed by the data and the atlas, multiple-images-in-one display with atlas-anatomy-function blending, a fast locus-controlled generation of results, editing of loci, multiple label display, and saving and reading of loci. The system normalizes a single image in near real-time (0.7 s), so analysis of anatomical and functional datasets can be done on-the-fly regardless of the number of slices. The same task performed by the state-of-the-art non-linear registration methods may require up to several days., Conclusions: The system is a useful tool for atlas-assisted localization analysis and a helpful adjunct to function/location metanalysis in human brain mapping research. It is also a step forward in bringing the atlas and the clinical data together within a practical and powerful solution that is fast and flexible, yet low-cost and affordable.

The authors report the case of a patient with an ischemic lesion in the left midbrain. The patient presented with paresis of left inferior rectus, pupil, right superior rectus, convergence and transiently, of the left medial rectus. A lesion in the left dorsal midbrain close to the oculomotor nuclear complex, selectively involving the fascicles innervating the above muscles, is proposed. Fine magnetic resonance sections showed a consistent lesion in the left paramedian dorsal midbrain. A detailed, three-dimensional, schematic computer model of the oculomotor nucleus and fascicles was constructed. Using this model, the authors topographically validate the putative site of the lesion. The medial rectus subnucleus is divided into three subgroups, A, B, and C. Subgroup C is thought to be the site of the majority of neurons controlling convergence. In the above model, the putative lesion is closer to subgroup A than to C; this suggests that subgroup A, rather than subgroup C, may have a higher concentration of neurons involved in convergence.

Objective: To report our experience with preoperative neurosurgical planning in our stereoscopic virtual reality environment for 21 patients with intra- and extra-axial brain tumors and vascular malformations., Methods: A neurosurgical planning system called VIVIAN (Virtual Intracranial Visualization and Navigation) was developed for the Dextroscope, a virtual reality environment in which the operator reaches with both hands behind a mirror into a computer-generated stereoscopic three-dimensional (3-D) object and moves and manipulates the object in real time with natural 3-D hand movements. Patient-specific data sets from multiple imaging techniques (magnetic resonance imaging, magnetic resonance angiography, magnetic resonance venography, and computed tomography) were coregistered, fused, and displayed as a stereoscopic 3-D object. A suite of 3-D tools accessible inside the VIVIAN workspace enabled users to coregister data, perform segmentation, obtain measurements, and simulate intraoperative viewpoints and the removal of bone and soft tissue., Results: VIVIAN was used to plan neurosurgical procedures primarily in difficult-to-access areas, such as the cranial base and the deep brain. The intraoperative and virtual reality 3-D scenarios correlated well. The VIVIAN system substantially contributed to surgical planning by 1) providing a quick and better understanding of intracranial anatomic and abnormal spatial relationships, 2) simulating the craniotomy and the required cranial base bone work, and 3) simulating intraoperative views., Conclusion: The VIVIAN system allows users to work with complex imaging data in a fast, comprehensive, and intuitive manner. The 3-D interaction of this virtual reality environment is essential to the efficient assembly of surgically relevant spatial information from the data derived from multiple imaging techniques. The usefulness of the system is highly dependent on the accurate coregistration of the data and the real-time speed of the interaction.

Three patients underwent stereotactic posteroventral pallidotomy, and 1 patient underwent pallidal deep brain stimulation, for medically intractable symptoms of advanced Parkinson's disease, characterized by peak-dose levodopa dyskinesias, wearing-off fluctuations, tremor, rigidity and bradykinesia. Surgery was performed stereotactically under local anaesthesia, with eventual target coordinates derived from a combination of magnetic resonance imaging (MRI), coregistration with an electronic brain atlas, intraoperative microelectrode neuronal recordings and microstimulation before lesioning or placement of a deep brain stimulator was done. Assessment was made at baseline preoperatively and at 3-month intervals postoperatively, with Unified Parkinson's Disease Rating Scale (UPDRS) and Core Assessment Program for Intracerebral Transplantation (CAPIT) scoring. All patients improved in dyskinesia, tremor, rigidity and bradykinesia contralateral to the lesion side, but also on the ipsilateral side to a lesser extent. The improvement was largely seen in the 'off' state: UPDRS by 41%, and CAPIT by 19% on the contralateral side. 'On' freezing was not helped. There were no deaths and no visual complications, but there was one complication of a delayed contralateral upper limb dystonia after pallidotomy. The 1 patient with pallidal deep brain stimulation (DBS) obtained similar improvement as those with pallidotomy. Posteroventral pallidotomy and pallidal stimulation improves all the cardinal features of Parkinson's disease, and effectively ameliorates levodopa dyskinesias.

This paper presents a novel approach for the use of the Atlas for Stereotaxy of the Human Brain by Schaltenbrand and Wahren [Stuttgart, Thieme, 1977] for anatomical targeting in functional neurosurgery. We propose to use simultaneously all three electronic axial, coronal and sagittal mutually coregistered Schaltenbrand-Wahren brain atlas microseries. The printed atlas microseries are digitized, extended to cover both hemispheres, contoured, labeled, organized into atlas volumes, and mutually coregistered. The electronic atlas is interactively registered with the data by using the three-dimensional Talairach proportional grid system transformation, followed up by local warping in the region of interest based on any clearly visible landmarks. The detailed targeting steps for pallidotomy, thalamotomy and subthalamotomy are formulated. The potential of this approach is to increase the accuracy of target definition, to decrease the time of the procedure by reducing the number of microelectrode tracts, and to give an extra degree of confidence to the neurosurgeon. The advantages of the approach and the limitations of the Schaltenbrand-Wahren atlas are discussed.

The Electronic Clinical Brain Atlas is a CD-ROM containing several classic brain atlases and a real-time yet simple registration function that deforms the atlases to match them with specific patient studies. This article presents the use of this registration function for functional neurosurgery planning. We first propose the CD-ROM assisted planning procedure, then illustrate it with two cases: a pallidal stimulation and a thalamic stimulation. The Schaltenbrand-Wahren atlas is registered and scaled to conform with an actual patient's data by means of two-dimensional (2-D) local deformations performed in multiple orientations. First a rectangular region of interest (ROI), which is set between any clearly visible landmarks chosen by the neurosurgeon, is measured on the film or scanner console. The corresponding atlas plate with the target is then deformed in real time for the same landmarks, such that the dimensions of this ROI are the same on the film and on the deformed atlas plate. Next the target is set on the deformed (individualized) atlas plate and its coordinates are read. The individualized atlas plate can also be printed on transparent foil and superimposed on the film or, alternatively, this superimposition can be done electronically. The planning steps can be repeated for all available orientations. The proposed atlas-assisted planning procedure extends the traditional use of printed stereotactic atlases by individualizing them to specific patients. The preliminary results show that this procedure may improve the definition of the target and may have several advantages over other approaches, such as indirect measurements based on the AC-PC line or 1-D (intercommissural distance based) scaling. It provides the neurosurgeon with a convenient and immediate means of accessing ancillary data that is usually only available in the printed form.

We present a suite of neurosurgery supporting tools developed around (i) the Virtual Workbench, a productive environment for the control of 3-D data, in which delicate work can be performed for hours on end without strain, and (ii) the Electronic Brain Atlas, integrating the major print brain atlases in day-to-day clinical use. We describe in detail the Brain Bench, a surgical planning system for stereotactic frame neurosurgery. Its objective is to prepare faster plans; have a better and more accurate choice of target points; improve the avoidance of sensitive structures; have fewer sub-optimal frame attachments and speedier, more effective planning and training. If validated by a clinical study now under way, this will improve medical efficacy and reduce costs.

In neuroscience research, the use of true single-unit microelectrode technique has been confined largely to the animal neurophysiology laboratory due to the complexity of the equipment required and the fastidious, time-consuming nature of the methodology. We report here our successful clinical use of this technique in human patients with Parkinson's disease undergoing awake stereotactic movement disorder neurosurgery. The common targets in such operations are the postero-ventral portion of the globus pallidus interna in the basal ganglia (for dopa-induced dyskinesias particularly) and the ventro-intermediate nucleus of the thalamus (for tremor-predominant Parkinson's disease). Accurate and exquisite neurophysiological localisation of these small targets deep within the brain can be obtained with single-unit microelectrode technique prior to the insertion of a deep brain stimulator or definitive neurosurgical radiofrequency lesioning in the target area. This accuracy translates into better outcomes for patients and a reduced incidence of complications. The wealth of data gained from studying the abnormal behaviour of neurons within the basal ganglia and thalamus also provides us with fundamental insights into the pathophysiology behind Parkinson's disease.

The authors present their experience in the use of an atlas-based computer system for preoperative functional neurosurgery planning and postoperative analysis. It has also some potential for intraoperative support. The system is based on a deformable electronic version of "Atlas of Stereotaxy of the Human Brain" by Schaltenbrand and Wahren. This atlas is used for interactive segmentation and labelling of clinical data in two- and three dimensions, and for definition of stereotactic targets. The Schaltenbrand-Wahren atlas microseries are digitized, enhanced, segmented, labelled, aligned and organized into atlas volumes. They are mutually preregistered, and three-dimensional models of the structures are constructed. The atlas may be interactively registered with an actual patient's data. A computer system is developed which provides data interpolation, reformatting, registration, visualization, navigation, mensuration and path display and editing in two- and three dimensions. The system increases the accuracy of target definition, reduces the time of planning and the time of the procedure itself. It also constitutes a research platform for the construction of more advanced neurosurgery supporting tools and brain atlases.

For the purpose of developing multiple, complementary, fully labeled electronic brain atlases and an atlas-based neuroimaging system for analysis, quantification, and real-time manipulation of cerebral structures in two and three dimensions, we have digitized, enhanced, segmented, and labeled the following print brain atlases: Co-Planar Stereotaxic Atlas of the Human Brain by Talairach and Tournoux, Atlas for Stereotaxy of the Human Brain by Schaltenbrand and Wahren, Referentially Oriented Cerebral MRI Anatomy by Talairach and Tournoux, and Atlas of the Cerebral Sulci by Ono, Kubik, and Abernathey. Three-dimensional extensions of these atlases have been developed as well. All two- and three-dimensional atlases are mutually preregistered and may be interactively registered with an actual patient's data. An atlas-based neuroimaging system has been developed that provides support for reformatting, registration, visualization, navigation, image processing, and quantification of clinical data. The anatomical index contains about 1,000 structures and over 400 sulcal patterns. Several new applications of the brain atlas database also have been developed, supported by various technologies such as virtual reality, the Internet, and electronic publishing. Fusion of information from multiple atlases assists the user in comprehensively understanding brain structures and identifying and quantifying anatomical regions in clinical data. The multiple brain atlas database and atlas-based neuroimaging system have substantial potential impact in stereotactic neurosurgery and radiotherapy by assisting in visualization and real-time manipulation in three dimensions of anatomical structures, in quantitative neuroradiology by allowing interactive analysis of clinical data, in three-dimensional neuroeducation, and in brain function studies.