Automated quantification of epicardial adipose tissue (EAT) in coronary CT angiography; comparison with manual assessment and correlation with coronary artery disease.

Background: Epicardial adipose tissue (EAT) is emerging as a risk factor for coronary artery disease (CAD).

Objective: The aim of this study was to determine the applicability and efficiency of automated EAT quantification.

Methods: EAT volume was assessed both manually and automatically in 157 patients undergoing coronary CT angiography.

Fully automated right ventricular volumetry from ECG-gated coronary CT angiography data: evaluation of prototype software.

Enlargement and dysfunction of the right ventricle (RV) is a sign and outcome predictor of many cardiopulmonary diseases. Due to the complex geometry of the RV exact volumetry is cumbersome and time-consuming. We evaluated the performance of prototype software for fully automated RV segmentation and volumetry from cardiac CT data.

Efficient detection of native and bypass coronary ostia in cardiac CT volumes: anatomical vs. pathological structures.

Cardiac computed tomography (CT) is the primary noninvasive imaging modality to diagnose coronary artery disease. Though various methods have been proposed for coronary artery segmentation, most rely on at least one user click to provide a seed point for initialization. Automatic detection of the coronary ostia (where coronaries originate from the aorta), including both the native coronary ostia and graft ostia of the bypass coronaries, can make the whole coronary exam workflow fully automatic, therefore increasing a physician's throughput.

Detection, grading and classification of coronary stenoses in computed tomography angiography.

Recently conducted clinical studies prove the utility of Coronary Computed Tomography Angiography (CCTA) as a viable alternative to invasive angiography for the detection of Coronary Artery Disease (CAD). This has lead to the development of several algorithms for automatic detection and grading of coronary stenoses. However, most of these methods focus on detecting calcified plaques only.

Patient-specific modeling and quantification of the aortic and mitral valves from 4-D cardiac CT and TEE.

As decisions in cardiology increasingly rely on noninvasive methods, fast and precise image processing tools have become a crucial component of the analysis workflow. To the best of our knowledge, we propose the first automatic system for patient-specific modeling and quantification of the left heart valves, which operates on cardiac computed tomography (CT) and transesophageal echocardiogram (TEE) data. Robust algorithms, based on recent advances in discriminative learning, are used to estimate patient-specific parameters from sequences of volumes covering an entire cardiac cycle.

New techniques in CT angiography.

Computed tomographic (CT) angiography has been improved significantly with the introduction of four- to 64-section spiral CT scanners, which offer rapid acquisition of isotropic data sets. A variety of techniques have been proposed for postprocessing of the resulting images. The most widely used techniques are multiplanar reformation (MPR), thin-slab maximum intensity projection, and volume rendering.

Standardized 3D documentation for neurosurgery.

Objective: Although direct volume visualization is now a standard tool for diagnosis and therapy planning for medical conditions in the brain, its application is normally restricted to radiological workstations. We propose the use of standardized digital video sequences which can be easily ported to mobile computing platforms and thereby to diverse clinical environments. The effectiveness of this approach is demonstrated in the operating room.