A visual neural classifier.

A new neural classifier allows visualization of the training set and decision regions, providing benefits for both the designer and the user. We demonstrate the visualization capabilities of this visual neural classifier using synthetic data, and compare the visualization performance to Kohunen's self-organizing map. We show in applications to image segmentation and medical diagnosis that visualization enables a designer to refine the classifier to achieve low error rates and enhances a user's ability to make classifier-assisted decisions.

Technical note: A new TLD-phantom measurement system for determining dose distribution levels in the right and left breast from spiral CT chest imaging.

Two specially designed plastic/aluminum phantoms positioned thermoluminescent dosimeters (TLDs) at the right and left breast location of an anthrophomorophic chest torso. Imaging was performed on a spiral CT for a Volume of the chest phantom through the breast area for a noncontiguous (pitch 1.5) helical chest scan.

Computer-aided, case-based diagnosis of mammographic regions of interest containing microcalcifications.

Rationale And Objectives: The purpose of this study was to evaluate the effectiveness of a mapped-database diagnostic system in reducing the incidence of benign biopsies and misdiagnosed cancers among mammographic regions of interest (ROIs).

Materials And Methods: A novel neural network was devised (a) to respond to a query ROI by recommending to biopsy or not to biopsy and (b) to map each ROI in the database as a dot on a computer screen. The network was designed so that clusters in the array of dots help the radiologist to find proved ROIs visually similar to the query ROI.

Biplane X-ray angiograms, intravascular ultrasound, and 3D visualization of coronary vessels.

The technology for determination of the 3D vascular tree and quantitative characterization of the vessel lumen and vessel wall has become available. With this technology, cardiologists will no longer rely primarily on visual inspection of coronary angiograms but use sophisticated modeling techniques combining images from various modalities for the evaluation of coronary artery disease and the effects of treatment. Techniques have been developed which allow the calculation of the imaging geometry and the 3D position of the vessel centerlines of the vascular tree from biplane views without a calibration object, i.

Reconstructing the 3-D medial axes of coronary arteries in single-view cineangiograms.

Describes a technique for reconstructing the skeletal structure of coronary arteries from a succession of frames of a single-view cineangiogram. The authors use local features in each frame to determine correspondences of arterial segments in successive frames. They define a similarity measure in 2D image space as the change in angular coordinates of corresponding pairs.