▪ Abstract Image segmentation plays a crucial role in many medical-imaging applications, by
automating or facilitating the delineation of anatomical structures and other regions of …

MRI-based medical image analysis for brain tumor studies is gaining attention in recent
times due to an increased need for efficient and objective evaluation of large amounts of …

Humans perceive the three-dimensional structure of the world with apparent ease. However,
despite all of the recent advances in computer vision research, the dream of having a …

Several properties of the cerebral cortex, including its columnar and laminar organization, as
well as the topographic organization of cortical areas, can only be properly understood in …

Accurate and automated methods for measuring the thickness of human cerebral cortex
could provide powerful tools for diagnosing and studying a variety of neurodegenerative and …

Partial differential equations (PDEs) have led to an entire new field in image processing and
computer vision. Hundreds of publications have appeared in the last decade, and PDE …

Statistical shape models (SSMs) have by now been firmly established as a robust tool for
segmentation of medical images. While 2D models have been in use since the early 1990s …

This paper presents a review of automated image registration methodologies that have been
used in the medical field. The aim of this paper is to be an introduction to the field, provide …

Statistical models of shape and appearance are powerful tools for interpreting medical
images. We assume a training set of images in which corresponding landmark points have …

Vascular diseases are among the most important public health problems in developed
countries. Given the size and complexity of modern angiographic acquisitions, segmentation …