Normal and abnormal brains can be segmented by registering the target image with an
atlas. Here, an atlas is defined as the combination of an intensity image (template) and its …

Deep convolutional neural networks (CNNs) are state-of-the-art for semantic image
segmentation, but typically require many labeled training samples. Obtaining 3D …

A general-purpose deformable registration algorithm referred to as “DRAMMS” is presented
in this paper. DRAMMS bridges the gap between the traditional voxel-wise methods and …

We propose a tracking method which tracks the complete object regions, adapts to changing
visual features, and handles occlusions. Tracking is achieved by evolving the contour from …

Knowledge-based segmentation has been explored significantly in medical imaging. Prior
anatomical knowledge can be used to define constraints that can improve performance of …

Segmentation of medical images is an important step in various applications such as
visualization, quantitative analysis and image-guided surgery. Numerous segmentation …

Motion degrades magnetic resonance (MR) images and prevents acquisition of self-
consistent and high-quality volume images. A novel methodology, Snapshot magnetic …

Abstract Computerized Image Registration approaches can offer automatic and accurate
image alignments without extensive user involvement and provide tools for visualizing …

A system and method of evaluating dose delivered by a radiation therapy system using a
marker that indicates motion. The marker is associated with the patient. In one method of …

This paper deals with the registration of geometric shapes. Our primary contribution is the
use of a simple and robust shape representation (distance functions) for global-to-local …