Image segmentation is considered as one of the most fundamental tasks in image
processing applications. Segmentation of magnetic resonance (MR) brain images is also an …

There is an urgent need to develop and integrate new statistical, mathematical, visualization,
and computational models with the ability to analyze Big Data in order to retrieve useful …

Autism Spectrum Disorder (ASD), commonly known as autism, is a lifelong developmental
disorder associated with a broad range of symptoms including difficulties in social …

Optical coherence tomography (OCT) is a noninvasive imaging technique that has been
used increasingly to diagnose and manage a variety of retinal diseases. OCT enables …

We propose using multi-scale image textures to investigate links between neuroanatomical
regions and clinical variables in MRI. Texture features are derived at multiple scales of …

Blood pressure (BP) changes with age are widespread, and systemic high blood pressure
(HBP) is a significant contributor for strokes and cognitive impairment. A non-invasive …

A new 3D segmentation method based on the level set technique is proposed. The main
contribution is a robust evolutionary model that requires no fine tuning of parameters. A …

This paper introduces a new framework for the segmentation of different brain structures
(white matter, gray matter, and cerebrospinal fluid) from 3D MR brain images at different life …

This paper introduces a novel shape-based computer-aided diagnosis (CAD) system using
magnetic resonance (MR) brain images for autism diagnosis at different life stages. To …

Developing an effective computer-aided diagnosis (CAD) system for lung cancer is of great
clinical importance and can significantly increase the patient's chance for survival. For this …