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 …

The proportions of muscle and fat tissues in the human body, referred to as body
composition is a vital measurement for cancer patients. Body composition has been recently …

In this paper, we propose a novel approach for segmenting the skeletal muscles in MRI
automatically. In order to deal with the absence of contrast between the different muscle …

We present a novel probabilistic shape representation that implicitly includes prior
anatomical volume and adjacency information, termed the generalized log-ratio (GLR) …

Purpose Automatic muscle segmentation is critical for advancing our understanding of
human physiology, biomechanics, and musculoskeletal pathologies, as it allows for timely …

Automatic segmentation of anatomic structures of magnetic resonance thigh scans can be a
challenging task due to the potential lack of precisely defined muscle boundaries and issues …

Severity and progression of degenerative neuromuscular diseases can be sensitively
captured by evaluating the fat infiltration of muscle tissue in T1-weighted MRI scans of …

This paper presents an end-to-end solution for MRI thigh quadriceps segmentation. This is
the first attempt that deep learning methods are used for the MRI thigh segmentation task …

Image segmentation is often performed via the minimization of an energy function over a
domain of possible segmentations. The effectiveness and applicability of such methods …

Incorporating prior knowledge into image segmentation algorithms has proven useful for
obtaining more accurate and plausible results. Two important constraints, containment and …