The problem of segmenting a volumetric layer of nite thickness is encountered in several important ar eas within medical image analysis Key examples in clude the extraction of the cortical gray matter of the brain and the left ventricle myocardium of the heart The coupling between the two bounding surfaces of such a layer provides important information that helps to solve the segmentation probl...

Although many interactive segmentation methods exists, none can be considered a silver bullet for all clinical tasks. Moreover, incompatible data representations prevent multiple algorithms from being combined as desired. We propose the GeoMap as a unified representation for segmentation results and illustrate how it facilitates the design of an integrated framework for interactive medical imag...

We have developed a new computer-aided diagnostic system for differentiating oral borderline malignancies in hematoxylin-eosin stained microscopic images. Epithelial dysplasia and carcinoma in-situ (CIS) of oral mucosa are two different borderline grades similar to each other, and it is difficult to distinguish between them. A new image processing and analysis method has been applied to a varie...

Medical image segmentation, the task of partitioning an image into meaningful parts, is an important step toward automating medical image analysis and is at the crux of a variety of medical imaging applications, such as computer aided diagnosis, therapy planning and delivery, and computer aided interventions. However, the existence of noise, low contrast and objects’ complexity in medical image...

Modern multislice X-ray CT scanners provide high-resolution volumetric image data containing a wealth of structural and functional information. The size of the volumes makes it more and more difficult for human observers to visually evaluate their contents. Similar to other areas of medical image analysis, highly automated extraction and quantitative assessment of volumetric data is increasingl...

Although, most of the abnormal structures of human brain do not alter the shape of outer envelope of brain (surface), some abnormalities can deform the surface extensively. However, this may be a major problem in a surface-based registration technique, since two nearly identical surfaces are required for surface fitting process. A type of verification known as the circularity check for th...

Today, a wide range of different image segmentation techniques can be found in medical imaging. Image segmentation is an important part of image processing, which often has a large impact on quantitative image analysis results. These allow the radiologist to obtain two and three-dimensional view of the internal structures of the human body, it has a large application domain for redundant clinic...

BACKGROUND One of the most important lesion features predicting malignancy is border irregularity. Accurate assessment of irregular borders is clinically important due to significantly different occurrence in benign and malignant skin lesions. METHOD In this research, we present a new approach for the detection of border irregularities, as one of the major parameters in a widely used diagnost...

Medical image analysis technology, with image segmentation, image matching /registration, motion tracking and the measurement of anatomical and physiological parameters as the main research areas, has seen a tremendous amount of growth over the past decade. The work described in this chapter is concerned with the problem of automatically aligning 3D medical images. Image registration is one of ...