This paper overviews one of the most important, interesting, and challenging problems in
oncology, the problem of lung cancer diagnosis. Developing an effective computer-aided …

This paper overviews one of the most important, interesting, and challenging problems in
oncology, early diagnosis of prostate cancer. Developing effective diagnostic techniques for …

This book provides a brief introduction to medical imaging, stochastic modeling, and model-
guided image analysis. It presents the latest state of the art in stochastic modeling for …

This paper proposes a novel framework for the classification of lung nodules using
computed tomography (CT) scans. The proposed framework is based on the integrating the …

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 …

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 …

A novel framework for the detection of radiation-induced lung injury (RILI) from 4D computed
tomography (CT) has been proposed. Our framework performs 4D-CT lung fields …

Performing accurate and fully automated lung segmentation of high-resolution computed
tomography (HRCT) images affected by dense abnormalities is a challenging problem. This …

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 …