Breast cancer is the most common form of cancer among women worldwide. Early detection
of breast cancer can increase treatment options and patients' survivability. Mammography is …

Deep learning networks have recently been shown to outperform other segmentation
methods on various public, medical-image challenge datasets, particularly on metrics …

This work covers the current state of the art with regard to approaches to segment
subcortical brain structures. A huge range of diverse methods have been presented in the …

Describes a system that is being used to segment gray matter from magnetic resonance
imaging (MRI) and to create connected cortical representations for functional MRI …

Medical imaging provides the convenience of physicians to analyze the disease by
providing visual data of the body parts required for clinical research and treatment. Today …

Gliomas segmentation is a critical and challenging task in surgery and treatment, and it is
also the basis for subsequent evaluation of gliomas. Magnetic resonance imaging is …

Legacy code can often be made more understandable and maintainable by extracting out
selected sets of statements to form procedures and replacing the extracted code with …

This paper explores the possibility of applying techniques for segmenting the regions of
medical image. For this we need to investigate the use of different techniques which helps …

The purpose of this study is to investigate the utility of obtaining “core samples” of regions in
CT volume scans for extraction of radiomic features. We asked four readers to outline tumors …

Extensive growth in functional brain imaging, perfusion-weighted imaging, diffusion-
weighted imaging, brain mapping and brain scanning techniques has led tremendously to …