Advanced high-speed CT scanners, such as the dynamic spatial reconstructor (DSR), now exist that provide high-resolution three-dimensional (3-D) volumetric images of the heart. Given a volumetric image (volume) of the heart, one can estimate the volume and 3-D spatial distribution of left ventricular (LV) myocardial muscle mass. The first stage of this problem is to extract the LV chamber. The prevalent techniques for solving this problem require manual editing of the data on a computer console. Unfortunately, manual editing is subject to operator errors and biases, only draws upon two-dimensional views, and it extremely time consuming. We describe a semiautomatic method for extracting the volume and shape of the LV chamber from a DSR cardiac volume. For a given volume, the operator first performs some simple manual edits. Then, an automated stage, which incorporates concepts from 3-D mathematical morphology and technology, the maximum-homogeneity filter, and an adaptive 3-D thresholder, extracts the LV chamber. The method gives more consistent measurements and demands considerably less operator time than manual slice-editing.
All Science Journal Classification (ASJC) codes
- Radiological and Ultrasound Technology
- Computer Science Applications
- Electrical and Electronic Engineering