Background Commercially available software for cardiovascular image analysis often has
limited functionality and frequently lacks the careful validation that is required for clinical …

Continuous advances in imaging technologies enable ever more comprehensive
phenotyping of human anatomy and physiology. Concomitant reduction of imaging costs …

Segmentation of the heart in cardiac cine MR is clinically used to quantify cardiac function.
We propose a fully automatic method for segmentation and disease classification using …

Cardiac cine magnetic resonance imaging (MRI) continues to be recognized as an
established modality for non-invasive assessment of the function and structure of the …

Cardiac imaging is an integral part of the evaluation and management of patients with
known or suspected heart disease. These techniques offer insight into morphologic features …

Current magnetic resonance imaging (MRI) technology allows the determination of patient-
individual coronary tree structure, detection of infarctions, and assessment of myocardial …

The emergence of deep learning has considerably advanced the state-of-the-art in cardiac
magnetic resonance (CMR) segmentation. Many techniques have been proposed over the …

The diagnosis of cardiovascular disease requires the precise assessment of both
morphology and function. Nearly all aspects of cardiovascular function and flow can be …

Purpose To propose and to evaluate a novel method for the automatic segmentation of the
heart's two ventricles from dynamic (“cine”) short‐axis “steady state free precession”(SSFP) …

This chapter focuses on the problem of measuring the performance of medical image
processing and analysis techniques. There are two important, but quite different, possible …