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Osteoporosis has become an increasingly important public health problem because of the rapidly aging populations. To obtain the sophisticated knowledge on normal vertebral anatomy is essential to understand the vertebral fracture risk. Multi-detector row computed tomography (MDCT) method can be used for quantitative analysis of vertebral anatomy such as volumetric bone mineral density (vBMD), geometry, and alignment with high accuracy and precision from the same dataset. This chapter described our latest two findings on statistical analysis and image analysis for vertebral anatomy by use of the image processing technique on the MDCT scanning. One was the population-based statistical analysis on vBMD at vertebrae. It showed the trabecular vBMD distribution at healthy thoracic and lumbar vertebrae in Japanese subjects and specific differences in age and gender. The other presented a computerized scheme to quantify the vertebral geometry. The scheme provided appropriate values on the vertebral geometry with numerous CT cases. It is likely that such computer-based attempts will help us to achieve the sophisticated vertebral anatomy.

Location of an inner organ in a CT image is the basic information that is required for medical image analysis such as image segmentation, lesion detection, content-based image retrieval, and anatomical annotation. A general approach/scheme for the localization of different inner organs that can be adapted to suit various types of medical image formats is required. However, this is a very challenging problem and can hardly be solved by using traditional image processing techniques. This chapter introduces an ensemble-learning-based approach that can be used to solve organ localization problems. This approach can be used to generate a fast and efficient organ-localization scheme from a limited number of training samples that include both original images and target locations. This approach has been used for localizing five different human organs in CT images, and the accuracy, robustness, and computational efficiency of the designed scheme were validated by experiments.

Aiming at avoiding misregistration in complicated medical image registration based on mutual information-simulated annealing particle swarm optimization (MI-SAPSO), we propose a novel algorithm named regional mutual information-simulated annealing particle swarm optimization (RMI-SAPSO). This method uses wavelet decomposition to denoise images, then determines optimum transformation parameters under choosing regional mutual information as objective function, finally does spatial geometric transformation according to the parameters to register medical images. Experimental results showed that the proposed method can register medical images effectively. It has a good robustness and owns better precision than traditional algorithm.

The elderly population has substantially increased worldwide. Aging is a complex process, and the effects of aging are myriad and insidious, leading to progressive deterioration of various organs, including the skeleton. Age-related bone loss and resultant osteoporosis in the elderly population increase the risk for fractures and morbidity. Osteoporosis is one of the most common conditions associated with aging, and age is an independent risk factor for osteoporotic fractures. With the development of noninvasive imaging techniques such as computed tomography (CT), micro-CT, and high resolution peripheral quantitative CT (HR-pQCT), imaging of the bone architecture provides important information about age-related changes in bone microstructure and estimates of bone strength. In the past two decades, studies of human specimens using imaging techniques have revealed decreased bone strength in older adults compared with younger adults. The present paper addresses recently studied age-related changes in trabecular and cortical bone microstructure based primarily on HR-pQCT and micro-CT. We specifically focus on the three-dimensional microstructure of the vertebrae, femoral neck, and distal radius, which are common osteoporotic fracture sites.

Minimum description length (MDL) based group-wise registration was a state-of-the-art method to determine the corresponding points of 3D shapes for the construction of statistical shape models (SSMs). However, it suffered from the problem that determined corresponding points did not uniformly spread on original shapes, since corresponding points were obtained by uniformly sampling the aligned shape on the parameterized space of unit sphere. We proposed a particle-system based method to obtain adaptive sampling positions on the unit sphere to resolve this problem. Here, a set of particles was placed on the unit sphere to construct a particle system whose energy was related to the distortions of parameterized meshes. By minimizing this energy, each particle was moved on the unit sphere. When the system became steady, particles were treated as vertices to build a spherical mesh, which was then relaxed to slightly adjust vertices to obtain optimal sampling-positions. We used 47 cases of (left and right) lungs and 50 cases of livers, (left and right) kidneys, and spleens for evaluations. Experiments showed that the proposed method was able to resolve the problem of the original MDL method, and the proposed method performed better in the generalization and specificity tests.

Aiming at the segmentation of liver image with fuzzy edge, a new algorithm based on Markov Random Field and ribs fitting approach is proposed. The new algorithm consists of three main steps. Firstly, an abdominal image is pre-processed to fit ribs and remove the obstructive region. Then, lifting wavelet transform is adopted to decompose an image in different resolutions, and an image segmentation algorithm based on MRF is manipulated to the low frequency sub-images; lastly, morphology operation is adopted to obtain the liver region. The algorithms of the initial and multi-level segmentation in wavelet domain are K-means and MAP/ICM. Several experiments have been carried out and the experimental results show that the proposed algorithm has a good robustness and higher segmentation accuracy than the traditional MRF approach.

Purpose Mandibular cortical width (MCW) measured on dental panoramic radiographs (DPRs) was significantly correlated with bone mineral density. We developed a computer-aided diagnosis scheme that automatically measures MCW to assist dentists in describing a possible osteoporotic risk and suggesting further examinations. Methods In our approach, potential mandible edges are detected by modified Canny edge detector. On the basis of the edge information, a contour model is selected from the reference data and is fitted to the test case by using the active contour model. The reference mental foramina positions of the model are employed as the MCW measurement locations. The MCW is measured on the basis of the grayscale profiles obtained along the lines perpendicular to the fitted mandible contour. One hundred DPRs, including 26 DPRs from osteoporotic cases, were used to evaluate our proposed scheme. Results Experimental results showed that the average MCWs for osteoporotic and control cases were 2.2 and 3.9 mm, respectively. When a threshold of 2.7 mm was applied, the sensitivity and specificity for identifying osteoporotic patients were 88.5 and 97.3 %, respectively. Conclusion An automated MCW measurement technique is feasible using DPRs, and this method has a potential to identify asymptomatic osteoporotic patients.

To investigate the effect of hSCGF-alpha on human Umbilical Cord Mesenchymal Stem Cells (hUCMSCs), we obtained hSCGF-alpha using genetic engineering, hSCGF-alpha gene was amplified from hUCMSCs cDNA using two-step PCR and was inserted into pET-28a(+) plasmid vector. Induced by IPTG at 20 degrees Celsius for 24 h, the fusion protein expressed in E. coli BL21 (DE3) was mainly existing in soluble form. The recombinant hSCGF-a was purified using NI-NTA affinity chromatography and the purity was up to 90%. The colony forming test revealed that combined use hSCGF-alpha and rmGM-CSF (recombinant murine GM-colony stimulating factor, rmGM-CSF) had granulocyte/macrophage (GM) promoting effects on murine bone marrow GM progenitor. In addition, the results indicated that hSCGF-alpha and rhGM-CSF had stimulatory effect on hUCMSCs and their synergetic effect was the strongest.

Osteoporosis is a common disease characterized by low bone mass and microstructural deterioration of bone tissue, with an increased fracture risk. With an aging population, osteoporosis and its related fractures have become an increasingly important health and socioeconomic issue. The aim of osteoporosis screening and treatment is to prevent bone fracture. A fracture occurs when the external force applied to a bone exceeds its strength. The ability of a bone to resist fracture depends on its amount, spatial distribution, and intrinsic properties. Sophisticated bone imaging techniques, as new modalities, improve the potential for non-invasive study of bone anatomy, physiology and pathophysiology. The objective of bone imaging in osteoporosis is to minimize fracture occurrence by identifying the osteoporotic process at an early stage, differentiate distinctive patterns of bone loss, predict fracture risk accurately and monitor treatment response precisely. Non-invasive imaging techniques, such as computed tomography (CT) and magnetic resonance imaging (MRI), provide structural information, beyond bone mineral density (BMD). Non-invasive or non-destructive imaging techniques can provide important structural information about the local and systemic skeletal status and about the propensity to fracture. These advanced imaging techniques provide information about bone beyond standard bone mineral densitometry. In this chapter, we will discuss recent progress in bone imaging in a range from the macroto micro-structures in order to investigate the structural basis of the skeletal fragility underlying osteoporosis.

ROC studies require complex procedures to select cases from many data samples, and to set confidence levels in each selected case to generate ROC curves. In some observer performance studies, researchers have to develop software with specific graphical user interface (GUI) to obtain confidence levels from readers. Because ROC studies could be designed for various clinical situations, it is difficult task for preparing software corresponding to every ROC studies. In this work, we have developed software for recording confidence levels during observer studies on tiny personal handheld devices such as iPhone, iPod touch, and iPad. To confirm the functions of our software, three radiologists performed observer studies to detect lung nodules by using public database of chest radiograms published by Japan Society of Radiological Technology. The output in text format conformed to the format for the famous ROC kit from the University of Chicago. Times required for the reading each case was recorded very precisely.

The purpose of this study is to develop an automated carotid artery calcification (CAC) detection scheme on dental panoramic radiographs (DPRs). The CAC is one of the indices for predicting the risk of arteriosclerosis. First, regions of interest (ROIs) that include CACs were determined on the basis of inflection points of the mandibular contour. Initial CAC candidates were detected by using a grayscale top-hat filter and simple grayscale thresholding technique. Finally, a rule-based approach and support vector machine to reduce the number of false positive (FP) findings were applied using features such as area, location, and circularity. Thirty-four DPRs were used to evaluate the proposed scheme. The sensitivity for the detection of CACs was 93.6% with 4.4 FPs per image. Experimental results showed that our computer-aided detection scheme may be useful to detect CACs.

Modern graphics processing units work efficiently in the RF Pulse Design for MR image reconstruction, which could make the reconstruction of images quicker with higher signal to noise ratio (SNR) and higher resolution. This paper introduces using GPU techniques, such as multithreads, sharedMem, coalesce, and constMem to optimize the performance of the conjugate gradient least square algorithm for reconstructing MR images. Compared to a full CPU implementation, a version utilizing the conjugate gradient least square algorithm on the NVIDIA Tesla C 1060 is significantly faster. The total image reconstruction time, including all CPU to GPU setup and overhead, also improves dramatically.

a b s t r a c t Purpose: Organ segmentation is an essential step in the development of computer-aided diagnosis/surgery systems based on computed tomography (CT) images. A universal segmentation approach/scheme that can adapt to different organ segmentations can substantially increase the efficiency and robustness of such computer-aided systems. However, this is a very challenging problem. An initial determination of the approximate position and range of a target organ in CT images is prerequisite for precise organ segmentations. In this study, we have proposed a universal approach that enables automatic localization of the approximate position and range of different solid organs in the torso region on three-dimensional (3D) CT scans. Methods: The location of a target organ in a 3D CT scan is presented as a 3D rectangle that bounds the organ region tightly and accurately. Our goal was to automatically and effectively detect such a target organ-specific 3D rectangle. In our proposed approach, multiple 2D detectors are trained using ensemble learning and their outputs are combined using a collaborative majority voting in 3D to accomplish the robust organ localizations. Results: We applied this approach to localize the heart, liver, spleen, left-kidney, and right-kidney regions independently using a CT image database that includes 660 torso CT scans. In the experiment, we man- ually labeled the abovementioned target organs from 101 3D CT scans as training samples and used our proposed approach to localize the 5 kinds of target organs separately on the remaining 559 torso CT scans. The localization results of each organ were evaluated quantitatively by comparing with the corre- sponding ground truths obtained from the target organs that were manually labeled by human operators. Experimental results showed that success rates of such organ localizations were distributed from 99% to 75% of the 559 test CT scans. We compared the performance of our approach with an atlas-based approach. The errors of the detected organ-center-positions in the successful CT scans by our approach had a mean value of 5.14 voxels, and those errors were much smaller than the results (mean value about 25 voxels) from the atlas-based approach. The potential usefulness of the proposed organ localization was also shown in a preliminary investigation of left kidney segmentation in non-contrast CT images. Conclusions: We proposed an approach to accomplish automatic localizations of major solid organs on torso CT scans. The accuracy of localizations, flexibility of localizations of different organs, robustness to contrast and non-contrast CT images, and normal and abnormal patient cases, and computing efficiency were validated on the basis of a large number of torso CT scans.

The senescence-accelerated mouse strain P6 (SAMP6) is a model of senile osteoporosis, which possesses many features of senile osteoporosis in humans. So far, little is known about the systemic bone microstructural changes that occur at multiple skeletal sites. In this study, we therefore, investigated site (vertebra, femur and tibia) dependence of bone microstructure and bone mineral density (BMD) in SAMP6 and the normal control mouse (SAMR1) at 5 and 12 months of age using quantitative micro computed tomography (micro-CT) and image analysis software. As compared with SAMR1, the most prominent change in SAMP6 was the reduction of vertebral trabecular bone volume fraction (BV/TV) and trabecular BMD. Moderate decrease of trabecular bone mass was observed in the proximal tibia and distal femur. Increased marrow area and periosteal perimeter were investigated, though the cortical area and cortical thickness had no marked changes in the mid-tibial and mid-femoral cortical bones. These results indicate that bone microstructural properties in SAMP6 are remarkably heterogeneous throughout the skeleton, which is analogous to changes that occur in human bones. These findings further validate the relevance of SAMP6 as a model of senile osteoporosis.

We investigated age- and gender-related variation of both cortical and trabecular microstructure in human femoral neck. We found that age-related change of cortical porosity is more noticeable than that of trabecular parameter. Our data may help to gain more insight into the potential mechanism of osteoporotic femoral neck fractures. Variations in the microstructure of cortical and trabecular bone contribute to decreased bone strength. Age- and gender-related changes in cortical and trabecular microstructure of femoral neck is unclear. The aim of this study was to identify three-dimensional (3D) microstructural changes of both cortical and trabecular bone simultaneously in human femoral neck with age and gender, using micro-computed tomography (micro-CT). We hypothesized that there would be differences in age-related changes of cortical and trabecular bone for both women and men. We used 56 femoral necks of 28 women and men (57–98 years of age) from a Japanese population. The subjects were chosen to give an even age and gender distribution. Both women and men were divided into three age groups: middle (57–68 years), old (72–82 years), and elderly (87–98 years) groups. We examined cortical bone specimen from the inferior sector of femoral neck and trabecular bone specimen from the middle of femoral neck using micro-CT and 3D bone analysis software. Cortical thickness (Ct.Th) decreased by 10–15%, cortical porosity (Ca.V/TV) almost doubled, and canal diameter (Ca.Dm) increased by 65–77% between the middle-aged and elderly groups for both women and men. The trabecular bone volume fraction (BV/TV) decreased by around 20%; trabecular thickness (Tb.Th), trabecular number (Tb.N), and connectivity density (Conn.D) decreased; and trabecular separation (Tb.Sp) and structure model index (SMI) increased with age for both women and men. As compared with women, men had higher Ct.Th and BV/TV and lower Ca.V/TV and Ca.Dm among three age groups. There was a significant inverse correlation between Ca.V.TV and BV/TV for both women and men. Our findings indicate that Ct.Th and BV/TV decreased, and Ca.V/TV and Ca.Dm increased in femoral neck with age for both women and men. The most obvious age-related change is the increase of Ca.V/TV. The decrease of BV/TV with age is more noticeable than that of Ct.Th. This is the first study that has provided both cortical and trabecular microstructural data simultaneously in a Japanese sample. These data may help us to gain more insight into the potential mechanism of osteoporotic femoral neck fractures.

Age-related bone loss, which is poorly characterized, is a major underlying cause of osteoporotic fractures in the elderly. In order to identify the morphological feature of age-related bone loss, we investigated sex and site (tibia, femur and vertebra) dependence of bone microstructure in aging hamsters from 3 to 24 months of age using micro-CT. In the proximal tibia and distal femur, trabecular bone volume (BV/TV), trabecular number (Tb.N), trabecular thickness (Tb.Th) and bone mineral density (BMD) increased to a maximum at 6 or 12 months and then declined progressively from 12 to 24 months of age. Trabecular separation (Tb.Sp), trabecular bone pattern factor (TBPf) and structure model index (SMI) increased with age. As compared with male hamsters, BV/TV and Tb.N were significantly lower in females at 18 and 24 months of age. Age-related decrease of trabecular BV/TV in the vertebral body was less than that of the femoral and tibial metaphyses. In the mid-femoral diaphysis, cortical bone area remained constant from 3 to 24 months of age. Cortical thickness decreased from 12 to 24 months and cortical BMD declined significantly from 18 to 24 months of age. These findings indicate that skeletal site and sex differences exist in hamster bone structure. Age-related bone changes in hamsters resemble those in humans. We conclude that hamster may be a useful model to study at least some aspects of bone loss during human aging.

Accurately identifying corresponded landmarks from a population of shape instances is the major challenge in constructing statistical shape models. In this paper, we address this landmark-based shape-correspondence problem for 3D cases by developing a highly efficient landmark-sliding algorithm. This algorithm is able to quickly refine all the landmarks in a parallel fashion by sliding them on the 3D shape surfaces. We use 3D thin-plate splines to model the shape-correspondence error so that the proposed algorithm is invariant to affine transformations and more accurately reflects the nonrigid biological shape deformations between different shape instances. In addition, the proposed algorithm can handle both open-and closed-surface shape, while most of the current 3D shape-correspondence methods can only handle genus-0 closed surfaces. We conduct experiments on 3D hippocampus data and compare the performance of the proposed algorithm to the state-of-the-art MDL and SPHARM methods. We find that, while the proposed algorithm produces a shape correspondence with a better or comparable quality to the other two, it takes substantially less CPU time. We also apply the proposed algorithm to correspond 3D diaphragm data which have an open-surface shape.

A probabilistic model was proposed in this research for fully-automated segmentation of liver region in non-contrast X-ray torso CT images. This probabilistic model was composed of two kinds of probability that show the location and density (CT number) of the liver in CT images. The probability of the liver on the spatial location was constructed from a number of CT scans in which the liver regions were pre-segmented manually as gold standards. The probability of the liver on density was estimated specifically using a Gaussian function. The proposed probabilistic model was used for automated liver segmentation from non-contrast CT images. 132 cases of the CT scans were used for the probabilistic model construction and then this model was applied to segment liver region based on a leave-one-out method. The performances of the probabilistic model were evaluated by comparing the segmented liver with the gold standard in each CT case. The validity and usefulness of the proposed model were proved.

We have developed a computer-aided diagnosis system (CAD) to detect abnormalities in fundus images. In Japan, ophthalmologists usually detect hypertensive changes by identifying arteriolar narrowing and focal arteriolar narrowing. The purpose of this study is to develop an automated method for detecting arteriolar narrowing and focal arteriolar narrowing on fundus images. The blood vessel candidates were detected by the density analysis method. In blood vessel tracking, a local detection function was used to determine the centerline of the blood vessel. A direction comparison function using three vectors was designed to optimally estimate the next possible location of a blood vessel. After the connectivity of vessel segments was adjusted based on the recognized intersections, the true tree-like structure of the blood vessels was established. The blood vessels were recognized as arteries or veins by hue of HSV color space and their diameters. The arteriolar narrowing was detected by the ratio of diameters (artery vs. vein; A/V ratio). Focal arteriolar narrowing was detected by measuring the diameter of an artery. By applying this method to 100 fundus images, the detection sensitivity for arteriolar narrowing was found to be 76% when the specificity was 91%. Furthermore, by applying this method to 70 other different fundus images, the detection sensitivity for the focal arteriolar narrowing was 75% with 2.9 false positives per image. The number of some false positives is planned to be reduced during the next stage of development. Such an automated detection of abnormal vessels could help ophthalmologists in diagnosing ocular diseases.

The anatomical human structure recognition is very important and necessary during the development of computer-aided diagnosis (CAD) system. In this paper, we propose an image processing scheme that can recognize the general structure of human torso by identifying the human torso region from CT images automatically and separating it into 7 parts: skin, subcutaneous fat, muscle, bone, diaphragm, thoracic cavity and abdominal cavity based on CT number distribution and spatial relations between different organ and tissue regions. We applied this scheme to 313 patient cases of torso CT images and confirmed its usefulness from the preliminary experiment.

In this paper, we present an arithmetic-based address translation scheme for low-power and real-time embedded processors with virtual memory support. General-purpose virtual memory support comes with its fundamental disadvantages of excessive power consumption and nondeterministic execution times. These disadvantages have been the main reason for not adopting virtual memory and its associated benefits in embedded systems where energy efficiency and real-time operations are major requirements. To address these issues, we propose a novel scheme for application-driven address translation where most of the virtual address translations, which are traditionally performed as lookups in the Translation Lookaside Buffer (TLB), are replaced with fast and energy efficient arithmetic add operations. To achieve this, a program and system-wide information is used to identify sequences of consecutive virtual page numbers, which are mapped to sequences of consecutive physical page frames. For such pairs of virtual and physical page sequences, only the addition of a constant to the virtual page number is needed to produce the physical page frame. The proposed methodology relies on the combined efforts of compiler, operating system, and hardware architecture to achieve a significant power reduction. As the approach fundamentally eliminates conflicts inherent in the hardware translation table, execution time is not only improved but also made predictable during system design time. The experiments that we have performed on a set of embedded applications show power reductions in the range of 80% to 95% compared to a general-purpose Translation Lookaside Buffer (TLB).

This paper describes a fully automated segmentation and recognition scheme, which is designed to recognize lung anatomical structures in the human chest by segmenting the different chest internal organ and tissue regions sequentially from high-resolution chest CT images. A sequential region-splitting process is used to segment lungs, airway of bronchus, lung lobes and fissures based on the anatomical structures and statistical intensity distributions in CT images. The performance of our scheme is evaluated by segmenting lung structures from high-resolution multi-slice chest CT images from 44 patients; the validity of our method was proved by preliminary experimental results.

Autopsy studies have shown atherosclerotic changes in angiographically normal coronary lesions (ANCL), and conventional intravascular ultrasound shows intimal thickening in these lesions, but cannot differentiate the lipid core. Accurate characterization of ANCL is essential to prevent progression to coronary artery disease.ANCL (n=120) were analyzed by integrated backscatter intravascular ultrasound (IB-IVUS) in 30 patients with stable angina pectoris. Of the 120 arterial segments analyzed by IB-IVUS, 78 (65%) showed lipid cores of 0.69+/-0.35 mm2 with fibrous caps of 200+/-100 microm thick, 44 (37%) had intimal hyperplasia with a thickness of 350+/-100 microm, and 65 (54%) showed fibrosis in the intimal wall without lipid core with a thickness of 450+/-150 microm. The diabetes mellitus (DM) group (n=14) had significantly (p0.05) bigger lipid cores (0.62+/-0.38 mm2) and thinner intimal hyperplasia (100+/-100 microm) compared with the non-DM group (0.31+/-0.33 mm2, 150+/-150 microm, respectively). The hypertension (HT) group (n=23) had significantly more intimal hyperplasia (150+/-150 microm) compared with the non-HT group (50+/-100 microm). Hyperlipidemia (n=16) or smoking (n=6) did not significantly affect tissue characteristics.IB-IVUS showed various types of plaque in ANCL and the plaque characteristics were affected by DM and HT. The results provide new clinical insight into the early stage of human coronary atherosclerosis.

We have been developing a computer-aided diagnosis (CAD) system for distinguishing the cirrhosis in MR images by shape and texture analysis. Two shape features are calculated from a segmented liver region, and seven texture features are quantified by using grey level difference method (GLDM) within the small region-of-interests (ROIs). The degree of cirrhosis is derived from integrating the shape and texture features of the liver into a three-layer feed-forward artificial neural network (ANN). A liver is regarded as cirrhosis if the percentage of the ROIs with a degree over 0.5 is greater than 50%. The initial experimental result showed that the ANN can learn all of the patterns in the training data sets. In testing of the whole liver regions, 82% cirrhosis and 100% normal cases were correctly differentiated from 18 test cases, that indicates our proposed method is effective to the cirrhosis prediction on MRI.

We have developed a new recognition approach using 2nd order autocorrelation and multi-regression analysis to detect a small (7mm in diameter) lung nodules in chest 3D CT images. By combining our previous detection method of the template matching based on genetic algorithm, the detection performance was 94% true-positive rate at 2.05 false-positive marks per case using leave-one- out study.

We have developed an algorithm that can distinguish the central part of the vertebral body from abdominal X-ray CT images to determine whether it is possible to aid a diagnosis of osteoporosis. We classified three measures for the principal component analysis and linear discriminant function. When we judged whether patients had osteoporosis or not, the ratio usable for diagnosing osteoporosis (sensitivity) was 1.00 (15/15), and for diagnosing as normal (specificity) was 0.64 (7/11). We believe that this algorithm can be used to aid in diagnosing osteoporosis, utilizing the measures obtained from the CT images.

We outline the first steps of an effort to start defining a communications architecture for supporting broadband data communications from the International Space Station. We focus on a direct-to-ground architecture, which could serve as an intermediate solution to satisfy the near term communications needs of commercial experiments and payloads on the ISS and overcome certain limitations of the current ISS communications infrastructure. We address three communications options and evaluate an architecture for the direct-to-ground option, focusing on a particular user's requirements, communications links, and coverage availability. We also discuss system, mobility support and protocol issues that need to be addressed for this solution to be a feasible alternative.

In this paper a three dimensional (3D) image processing expert system called 3D-IMPRESS is presented. This system can automatically construct a 3D image processing procedure by using pairs of an original input image and a desired output figure called sample figure given by a user This paper describes the outline of 3D-IMPRESS and presents a method of procedure consolidation for generating a procedure commonly applicable to some other 3D gray images. Finally, we show segmentation results of 3D chest CT images by using the procedures generated by 3D-IMPRESS and discuss the performance of the system.

A method for extracting and recognizing thoracic organ regions from three-dimensional (3D) CT chest images has been proposed in this paper. This method can be simply described as a pixel-labelling process, that is, each pixel in a chest CT image is attached with a predefined label that indicates a special organ or tissue of human body. The density distribution and strength of connectivity of different organ regions have been investigated and used for the recognition process. We developed a system to visualize the 3D CT images based on volume rendering technique and intergraded this method into it. We found that with the recognition results we can view the shape of a special organ without any overlap and can understand the relationship of human organs more clearly and easily.

A novel page table organisation for real-time and memory-constrained embedded system is presented. Increasingly many high-end embedded processors offer virtual memory support in the form of hardware memory management unit, which is responsible for caching and rapidly looking-up the address mapping required to access memory. However, to completely implement virtual memory support the system software needs to maintain a page table per task, which goal is to capture the virtual to physical page translation information for the entire address space. Page tables have been traditionally designed for general-purpose systems where their size and real-time performance have not been of primary importance; the average performance of page table traversal has been the major concern. Many embedded systems, however, impose strict real-time requirements coupled with limited memory resources. To address these problems, a novel page table organisation is proposed, which not only requires significantly less memory than the traditional page tables, but also enables a rapid and deterministic hardware-based page table traversal. This is achieved by exploiting application knowledge regarding the memory footprint of the program under execution and, in particular, the fact that often times large sequences of consecutive virtual pages are mapped to a non-fragmented region in physical memory comprising of consecutive physical memory frames.

Objectives The purpose of the present study was twofold: 1) to evaluate the usefulness of three-dimensional (3D) integrated backscatter (IB) intravascular ultrasound (IVUS) for quantitative tissue characterization of coronary plaques; and 2) to use this imaging technique to determine if six months of statin therapy alters the tissue characteristics of coronary plaques. Background Three-dimensional IVUS techniques for quantitative tissue characterization of plaque composition have not been developed. Methods Radiofrequency (RF) signals were obtained using an IVUS system with a 40-MHz catheter. The IB values of the RF signal were calculated and color-coded. The 3D reconstruction of the color-coded map was performed by computer software. A total of 18 IB IVUS images were captured at an interval of 1 mm in each plaque. A total of 52 patients with hyperlipidemia were randomized to treatment with pravastatin (20 mg/day, n = 17), atorvastatin (20 mg/day, n = 18), or diet (n = 17) for six months. The tissue characteristics of arterial plaque in each patient (one arterial segment per patient) were analyzed with 3D IB IVUS before and after treatment. Results Significant increases of fibrous volume (pravastatin: 25.4 ± 6.5% to 28.1 ± 6.1%; atorvastatin: 26.2 ± 5.7% to 30.1 ± 5.5%) and mixed lesion volume (atorvastatin: 25.5 ± 6.6% to 28.7 ± 5.1%) and a reduction of lipid volume (pravastatin: 25.5 ± 5.7% to 21.9 ± 5.3%; atorvastatin: 26.5 ± 5.2% to 19.9 ± 5.5%) were observed after statin therapy. Conclusions Statin therapy reduced the lipid component in patients with stable angina without reducing the degree of stenosis. Three-dimensional IB IVUS offers the potential for quantitative volumetric tissue characterization of coronary atherosclerosis.

Cirrhosis of the liver is characterized by the presence of widespread nodules and fibrosis in the liver. The fibrosis and nodules formation causes distortion of the normal liver architecture, resulting in characteristic texture patterns. Texture patterns are commonly analyzed with the use of co-occurrence matrix based features measured on regions-of-interest (ROIs). A classifier is subsequently used for the classification of cirrhotic or non-cirrhotic livers. Problem arises if the classifier employed falls into the category of supervised classifier which is a popular choice. This is because the 'true disease states' of the ROIs are required for the training of the classifier but is, generally, not available. A common approach is to adopt the 'true disease state' of the liver as the 'true disease state' of all ROIs in that liver. This paper investigates the use of a nonsupervised classifier, the k-means clustering method in classifying livers as cirrhotic or non-cirrhotic using unlabelled ROI data. A preliminary result with a sensitivity and specificity of 72% and 60%, respectively, demonstrates the feasibility of using the k-means non-supervised clustering method in generating a characteristic cluster structure that could facilitate the classification of cirrhotic and non-cirrhotic livers.

Cirrhosis of the liver is a chronic disease. It is characterized by the presence of widespread nodules and fibrosis in the liver which results in characteristic texture patterns. Computerized analysis of hepatic texture patterns is usually based on regions-of-interest (ROIs). However, not all ROIs are typical representatives of the disease stage of the liver from which the ROIs originated. This leads to uncertainties in the ROI labels (diseased or non-diseased). On the other hand, supervised classifiers are commonly used in determining the assignment rule. This presents a problem as the training of a supervised classifier requires the correct labels of the ROIs. The main purpose of this paper is to investigate the use of an unsupervised classifier, the k-means clustering, in classifying ROI based data. In addition, a procedure for generating a receiver operating characteristic (ROC) curve depicting the classification performance of k-means clustering is also reported. Hepatic MRI images of 44 patients (16 cirrhotic; 28 non-cirrhotic) are used in this study. The MRI data are derived from gadolinium-enhanced equilibrium phase images. For each patient, 10 ROIs selected by an experienced radiologist and 7 texture features measured on each ROI are included in the MRI data. Results of the k-means classifier are depicted using an ROC curve. The area under the curve (AUC) has a value of 0.704. This is slightly lower than but comparable to that of LDA and ANN classifiers which have values 0.781 and 0.801, respectively. Methods in constructing ROC curve in relation to k-means clustering have not been previously reported in the literature.

The purpose of this study is to recognize the psoas major muscle on X-ray CT images. For this purpose, we propose a novel recognition method. The recognition process in this method involves three steps: the generation of a shape model for the psoas major muscle, recognition of anatomical points such as the origin and insertion, and the recognition of the psoas major muscles by the use of the shape model. We generated the shape model using 20 CT cases and tested the model for recognition in 20 other CT cases. The average Jaccard similarity coefficient (JSC) and reproducibility rate were 0.704 and 0.783, respectively. Experimental results indicate that our method was effective for a 2-D cross-sectional area (CSA) analysis.

The aim of this paper is to describe three emerging computer-aided diagnosis (CAD) systems induced by Japanese health care needs. CAD has been developing fast in the last two decades. The idea of using a computer to help in medical image diagnosis is not new. Some pioneer studies are dated back to the 1960s. In 1998, the first U.S. FDA (Food and Drug Administration) approved commercial CAD system, a film-digitized mammography system, was launched by R2 Technologies, Inc. The success was quickly repeated by a number of companies. The approval of Medicare CAD reimbursement in the U.S. in 2001 further boosted the industry. Today, CAD has its significance in the economy of the medical industry. FDA approved CAD products in the field of breast imaging (mammography, ultrasonography and breast MRI) and chest imaging (radiography and CT) can be seen. In Japan, as part of the ''Knowledge Cluster Initiative'' of the government, three computer-aided diagnosis (CAD) projects are hosted at the Gifu University since 2004. These projects are regarding the development of CAD systems for the early detection of (1) cerebrovascular diseases using brain MRI and MRA images by detecting lacunar infarcts, unruptured aneurysms, and arterial occlusions; (2) ocular diseases such as glaucoma, diabetic retinopathy, and hypertensive retinopathy using retinal fundus images; and (3) breast cancers using ultrasound 3-D volumetric whole breast data by detecting the breast masses. The projects are entering their final development stage. Preliminary results are presented in this paper. Clinical examinations will be started soon, and commercialized CAD systems for the above subjects will appear by the completion of this project.

Bone is one of the most important anatomical structures in humans and osteoporosis is one of the major public health concerns in the world. Osteoporosis is a main target disease of bone, which can be detected by medical image techniques. The purpose of this study is to develop a fully automated computer scheme to measure bone-mineral-density (BMD) values for vertebral trabecular bones. This scheme will aid osteoporosis diagnosis performed using computer tomography (CT) images. This scheme includes the following processing steps: segmentation of the bone region, recognition of the skeletal structures and measurement of the BMD value in vertebral trabecular bone of each vertebral body. The proposed scheme was applied to 20 X-ray torso CT cases to measure the BMD values for vertebral trabecular bones. The experimental results show that the mean and standard deviation of the difference between the BMD values measured by using the proposed method and those measured using a manual segmentation method were 6.93 mg/cm(3) and 6.82 mg/cm(3) respectively. The accuracy of the proposed scheme satisfied the requirement for a computer-aided system used in osteoporosis diagnosis.