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 …

Whole heart segmentation from magnetic resonance imaging or computed tomography is a
prerequisite for many clinical applications. Since manual delineation can be tedious and …

Automatic image processing methods are a pre-requisite to efficiently analyze the large
amount of image data produced by computed tomography (CT) scanners during cardiac …

For many orthopaedic, neurological, and oncological applications, an exact segmentation of
the vertebral column including an identification of each vertebra is essential. However …

Visual Computing for Medicine, Second Edition, offers cutting-edge visualization techniques
and their applications in medical diagnosis, education, and treatment. The book includes …

We present a fully automated deformable model technique for myocardium segmentation in
3D MRI. Loss of signal due to blood flow, partial volume effects and significant variation of …

We present a fully automatic 3D segmentation method for the liver from contrast-enhanced
CT data. It is based on a combination of a constrained free-form and statistical deformable …

We propose an automated method for supervised segmentation of vertebral bodies (VBs)
from three-dimensional (3D) magnetic resonance (MR) spine images that is based on …

Automated and semi-automated detection and segmentation of spinal and vertebral
structures from computed tomography (CT) images is a challenging task due to a relatively …

Purpose: The authors present a fully automatic algorithm for the segmentation of the prostate
in three‐dimensional magnetic resonance (MR) images. Methods: The approach requires …