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The presentation of cortical arteries is challenging, as most of their course is hidden in the depth of the sulci. Despite that, demonstrating the arteries on the cortical surface is a standard way of their presentation. To keep advantages of surface presentation while lessening its limitation, we propose a novel context-related method of cerebrovasculature presentation by cortical openings consisting in the removal of a selected region from the cortical mantle and exposing underlying structures. We also introduce a reverse than standard vessel-to-context mapping from a gyrus/lobule to vessels supplying it.The method has the following steps: define a cortical opening, develop a tool to perform them, create cortical openings for gyri and lobules with underlying white matter and intracranial arteries, generate labeled and parcellated images for the created openings, and integrate the cortical opening images with the NOW in BRAIN public repository of 8600 3D neuroimages.The cortical openings are created for 64 gyri and six lobules for the left and right cerebral hemispheres resulting in 210 images arranged in triples as spatially corresponding non-parcellated and unlabeled, parcellated by color and unlabeled, and parcellated and labeled images.The cortical opening approach, generally, increases vessel exposure in a higher number of depicted branches, revealing arteries otherwise hidden deep in sulci, a more complete vessel course, and a lower number of required views.The gyrus/lobule-to-arteries mapping facilitates exploration of a studied region, encapsulates all local arteries, and reduces vascular complexity by decomposing the entire vascular system into smaller sets involved in the studied region., Competing Interests: Declaration of Conflicting InterestsThe author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Purpose : Integrating neuroradiology with neuroanatomy is essential in medical neuroeducation and neuroimage interpretation. To bridge 2D neuroradiology and 3D neuroanatomy, spatially correlated pairs of labeled images were employed, planar radiologic, and planar-surface combined. Research design : The method employs a 3D fully parcellated and labeled brain atlas extended to the head and neck with about 3000 3D components to create planar radiologic and surface neuroanatomic images. The atlas handles reformatted radiologic images as 3D objects using texture mapping which provides consistency with polygonal 3D neuroanatomic structures. This ensures a precise spatial correspondence of dual 2D-2D/3D images for any composed 3D scene reformatted in arbitrary orientation. The sequences of labeled dual images were created spanning a structure/system of interest in multiple orientations. To facilitate image searching, the image name encodes its content, orientation, and stereotactic location. Results : Labeled dual 2D-2D/3D neuroimage sequences in multiple orientations were created for the cerebrum, brainstem, deep nuclei, cerebral ventricles, intracranial arteries, dural sinuses, extracranial arteries, extracranial veins, trigeminal nerve, head muscles, glands, bones of cranium, and visual system. They all were hierarchically organized as a planar-surface gallery with 42 folders and 502 neuroimages. This gallery was integrated with a public NOW in BRAIN repository at www.nowinbrain.org with more than 7700 neuroimages. Conclusions : Owing to its advantages, simplicity, and free availability, this resource is useful for medical students, residents, educators, and clinicians to study the brain, head, and neck as well as to prepare presentations and teaching materials. The approach might potentially enhance image interpretation by integrating brain atlases with radiologic workstations.

We have recently witnessed an explosion of large-scale initiatives and projects addressing mapping, modeling, simulation and atlasing of the human brain, including the BRAIN Initiative, the Human Brain Project, the Human Connectome Project (HCP), the Big Brain, the Blue Brain Project, the Allen Brain Atlas, the Brainnetome, among others. Besides these large and international initiatives, there are numerous mid-size and small brain atlas-related projects. My contribution to these global efforts has been to create adult human brain atlases in health and disease, and to develop atlas-based applications. For over two decades with my R&D lab I developed 35 brain atlases, licensed to 67 companies and made available in about 100 countries. This paper has two objectives. First, it provides an overview of the state of the art in brain atlasing. Second, as it is already 20 years from the release of our first brain atlas, I summarise my past and present efforts, share my experience in atlas creation, validation and commercialisation, compare with the state of the art, and propose future directions.

Brain atlases have a wide range of use from education to research to clinical applications. Mathematical methods as well as computational methods and tools play a major role in the process of brain atlas building and developing atlas-based applications. Computational methods and tools cover three areas: dedicated editors for brain model creation, brain navigators supporting multiple platforms, and atlas-assisted specific applications. Mathematical methods in atlas building and developing atlas-aided applications deal with problems in image segmentation, geometric body modelling, physical modelling, atlas-to-scan registration, visualisation, interaction and virtual reality. Here I overview computational and mathematical methods in atlas building and developing atlas-assisted applications, and share my contribution to and experience in this field.

Human brain atlases, although prevalent in medical education and stereotactic and functional neurosurgery, are not yet applied practically in neuroradiology. In a step towards introducing brain atlases to neuroradiology, we discuss nine different situations of potential atlas use: (1) to support interpretation of brain scans with clearly visible structures (to increase confidence of non-neuroradiologists); (2) to delineate and label scans of low anatomical content (with indiscernible or poorly visible anatomy); (3) to assist in generating the structured report; (4) to assist in interpreting small deep lesions, since an atlas's anatomical parcellation is higher than that of the interpreted scan; (5) to approximate distorted due to pathology (and unknown to the interpreter) anatomy and label it; (6) to cope with data explosion; (7) to assist in the interpretation of functional scans (to label the activation foci with the underlying anatomy and Brodmann's areas); (8) to support ischemic stroke image handling by means of atlases of anatomy and blood supply territories; and (9) to communicate image interpretation results (diagnosis) to others. The usefulness of the atlas for automatic structure identification, localisation, delineation, labelling and quantification, as well as for reporting and communication, potentially increases the interpreter's efficiency and confidence, as well as expedites image interpretation., (© The Author(s) 2016.)

Our objective was to construct a 3D, interactive, and reference atlas of the extracranial vasculature spatially correlated with the intracranial blood vessels, cranial nerves, skull, glands, and head muscles.The atlas has been constructed from multiple 3T and 7T magnetic resonance angiogram (MRA) brain scans, and 3T phase contrast and inflow MRA neck scans of the same specimen in the following steps: vessel extraction from the scans, building 3D tubular models of the vessels, spatial registration of the extra- and intracranial vessels, vessel editing, vessel naming and color-coding, vessel simplification, and atlas validation.This new atlas contains 48 names of the extracranial vessels (25 arterial and 23 venous) and it has been integrated with the existing brain atlas.The atlas is valuable for medical students and residents to easily get familiarized with the extracranial vasculature with a few clicks; is useful for educators to prepare teaching materials; and potentially can serve as a reference in the diagnosis of vascular disease and treatment, including craniomaxillofacial surgeries and radiologic interventions of the face and neck., (© The Author(s) 2015 Reprints and permissions: sagepub.co.uk/journalsPermissions.nav.)

Computer-aided detection/diagnosis (CAD) is a key component of routine clinical practice, increasingly used for detection, interpretation, quantification and decision support. Despite a critical need, there is no clinically accepted CAD system for stroke yet. Here we introduce a CAD system for hemorrhagic stroke. This CAD system segments, quantifies, and displays hematoma in 2D/3D, and supports evacuation of hemorrhage by thrombolytic treatment monitoring progression and quantifying clot removal. It supports seven-step workflow: select patient, add a new study, process patient's scans, show segmentation results, plot hematoma volumes, show 3D synchronized time series hematomas, and generate report. The system architecture contains four components: library, tools, application with user interface, and hematoma segmentation algorithm. The tools include a contour editor, 3D surface modeler, 3D volume measure, histogramming, hematoma volume plot, and 3D synchronized time-series hematoma display. The CAD system has been designed and implemented in C++. It has also been employed in the CLEAR and MISTIE phase-III, multicenter clinical trials. This stroke CAD system is potentially useful in research and clinical applications, particularly for clinical trials.

Characterization of hematomas is essential in scan reading, manual delineation, and designing automatic segmentation algorithms. Our purpose is to characterize the distribution of intraventricular (IVH) and intracerebral hematomas (ICH) in NCCT scans, study their relationship to gray matter (GM), and to introduce a new tool for quantitative hematoma delineation. We used 289 serial retrospective scans of 51 patients. Hematomas were manually delineated in a two-stage process. Hematoma contours generated in the first stage were quantified and enhanced in the second stage. Delineation was based on new quantitative rules and hematoma profiling, and assisted by a dedicated tool superimposing quantitative information on scans with 3D hematoma display. The tool provides: density maps (40-85HU), contrast maps (8/15HU), mean horizontal/vertical contrasts for hematoma contours, and hematoma contours below a specified mean contrast (8HU). White matter (WM) and GM were segmented automatically. IVH/ICH on serial NCCT is characterized by 59.0HU mean, 60.0HU median, 11.6HU standard deviation, 23.9HU mean contrast, -0.99HU/day slope, and -0.24 skewness (changing over time from negative to positive). Its 0.1(st)-99.9(th) percentile range corresponds to 25-88HU range. WM and GM are highly correlated (R (2)=0.88; p<10(-10)) whereas the GM-GS correlation is weak (R (2)=0.14; p<10(-10)). The intersection point of mean GM-hematoma density distributions is at 55.6±5.8HU with the corresponding GM/hematoma percentiles of 88(th)/40(th). Objective characterization of IVH/ICH and stating the rules quantitatively will aid raters to delineate hematomas more robustly and facilitate designing algorithms for automatic hematoma segmentation. Our two-stage process is general and potentially applicable to delineate other pathologies on various modalities more robustly and quantitatively.

Understanding brain pathology along with the underlying neuroanatomy and the resulting neurological deficits is of vital importance in medical education and clinical practice. To facilitate and expedite this understanding, we created a three-dimensional (3D) interactive atlas of neurological disorders providing the correspondence between a brain lesion and the resulting disorder(s). The atlas contains a 3D highly parcellated atlas of normal neuroanatomy along with a brain pathology database. Normal neuroanatomy is divided into about 2,300 components, including the cerebrum, cerebellum, brainstem, spinal cord, arteries, veins, dural sinuses, tracts, cranial nerves (CN), white matter, deep gray nuclei, ventricles, visual system, muscles, glands and cervical vertebrae (C1-C5). The brain pathology database contains 144 focal and distributed synthesized lesions (70 vascular, 36 CN-related, and 38 regional anatomy-related), each lesion labeled with the resulting disorder and associated signs, symptoms, and/or syndromes compiled from materials reported in the literature. The initial view of each lesion was preset in terms of its location and size, surrounding surface and sectional (magnetic resonance) neuroanatomy, and labeling of lesion and neuroanatomy. In addition, a glossary of neurological disorders was compiled and for each disorder materials from textbooks were included to provide neurological description. This atlas of neurological disorders is potentially useful to a wide variety of users ranging from medical students, residents and nurses to general practitioners, neuroanatomists, neuroradiologists and neurologists, as it contains both normal (surface and sectional) brain anatomy and pathology correlated with neurological disorders presented in a visual and interactive way.

Anatomical knowledge of the cranial nerves (CN) is fundamental in education, research and clinical practice. Moreover, understanding CN-related pathology with underlying neuroanatomy and the resulting neurological deficits is of vital importance. To facilitate CN knowledge anatomy and pathology understanding, we created an atlas of CN-related disorders, which is a three-dimensional (3D) interactive tool correlating CN pathology with the underlying surface and sectional neuroanatomy as well as the resulting neurological deficits. A computer platform was developed with: 1) anatomy browser along with the normal brain atlas (built earlier); 2) simulator of CN lesions; 3) tools to label CN-related pathology; and 4) CN pathology database with lesions and disorders, and the resulting signs, symptoms and/or syndromes. The normal neuroanatomy comprises about 2,300 3D components subdivided into modules. Cranial nerves contain more than 600 components: all 12 pairs of cranial nerves (CN I - CN XII) and the brainstem CN nuclei. The CN pathology database was populated with 36 lesions compiled from clinical textbooks. The initial view of each disorder was preset in terms of lesion location and size, surrounding surface and sectional neuroanatomy, and disorder and neuroanatomy labeling. Moreover, path selection from a CN nucleus to a targeted organ further enhances pathology-anatomy relationships. This atlas of CN-related disorders is potentially useful to a wide variety of users ranging from medical students and residents to general practitioners, neuroradiologists and neurologists, as it contains both normal brain anatomy and CN-related pathology correlated with neurological disorders presented in a visual and interactive way.

Understanding stroke-related pathology with underlying neuroanatomy and resulting neurological deficits is critical in education and clinical practice. Moreover, communicating a stroke situation to a patient/family is difficult because of complicated neuroanatomy and pathology. For this purpose, we created a stroke atlas. The atlas correlates localized cerebrovascular pathology with both the resulting disorder and surrounding neuroanatomy. It also provides 3D display both of labeled pathology and freely composed neuroanatomy. Disorders are described in terms of resulting signs, symptoms and syndromes, and they have been compiled for ischemic stroke, hemorrhagic stroke, and cerebral aneurysms. Neuroanatomy, subdivided into 2,000 components including 1,300 vessels, contains cerebrum, cerebellum, brainstem, spinal cord, white matter, deep grey nuclei, arteries, veins, dural sinuses, cranial nerves and tracts. A computer application was developed comprising: 1) anatomy browser with the normal brain atlas (created earlier); 2) simulator of infarcts/hematomas/aneurysms/stenoses; 3) tools to label pathology; 4) cerebrovascular pathology database with lesions and disorders, and resulting signs, symptoms and/or syndromes. The pathology database is populated with 70 lesions compiled from textbooks. The initial view of each pathological site is preset in terms of lesion location, size, surrounding surface and sectional neuroanatomy, and lesion and neuroanatomy labeling. The atlas is useful for medical students, residents, nurses, general practitioners, and stroke clinicians, neuroradiologists and neurologists. It may serve as an aid in patient-doctor communication helping a stroke clinician explain the situation to a patient/family. It also enables a layman to become familiarized with normal brain anatomy and understand what happens in stroke.

Accurate quantification of haemorrhage volume in a computed tomography (CT) scan is critical in the management and treatment planning of intraventricular (IVH) and intracerebral haemorrhage (ICH). Manual and semi-automatic methods are laborious and time-consuming limiting their applicability to small data sets. In clinical trials measurements are done at different locations and on a large number of data; an accurate, consistent and automatic method is preferred. A fast and efficient method based on texture energy for identification and segmentation of hemorrhagic regions in the CT scans is proposed. The data set for the study was obtained from CLEAR-IVH clinical trial phase III (41 patients' 201 sequential CT scans from ten different hospitals, slice thickness 2.5-10 mm and from different scanners). The DICOM data were windowed, skull stripped, convolved with textural energy masks and segmented using a hybrid method (a combination of thresholding and fuzzy c-means). Artifacts were removed by statistical analysis and morphological processing. Segmentation results were compared with the ground truth. Descriptive statistics, Dice statistical index (DSI), Bland-Altman and mean difference analysis were carried out. The median sensitivity, specificity and DSI for slice identification and haemorrhage segmentation were 86.25%, 100%, 0.9254 and 84.90%, 99.94%, 0.8710, respectively. The algorithm takes about one minute to process a scan in MATLAB(®). A hybrid method-based volumetry of haemorrhage in CT is reliable, observer independent, efficient, reduces the time and labour. It also generates quantitative data that is important for precise therapeutic decision-making.

Existing methods of neuroimage registration typically require high quality scans and are time-consuming. We propose a simple and fast method which allows intra-patient multi-modal and time-series neuroimage registration as well as landmark identification (including commissures and superior/inferior brain landmarks) for sparse data. The method is based on elliptical approximation of the brain cortical surface in the vicinity of the midsagittal plane (MSP). Scan registration is performed by a 3D affine transformation based on parameters of the cortex elliptical fit and by aligning the MSPs. The landmarks are computed using a statistical localization method based on analysis of 53 structural scans without detectable pathology. The method is illustrated for multi-modal registration, analysis of hemorrhagic stroke time series, and ischemic stroke follow ups, as well as for localization of hardly visible or not discernible landmarks in sparse neuroimages. The method also enables a statistical localization of landmarks in sparse morphological/non-morphological images, where landmark points may be invisible.