TY - JOUR
T1 - Extraction of Left-Ventricular Chamber from 3-D CT Images of the Heart
AU - Higgins, William E.
AU - Chung, Namsik
AU - Ritman, Erik L.
N1 - Funding Information:
Manuscript received May 14. 1989; revised March 28. 1990. This work was supported in part by the National Institutes of Health under research Grants HL-07269-K, HL-04664, RR-02540. W. E. Higgins is with Department of Electrical Engineering and Biocn-gineering. Pennsylvania State University, University Park. PA. N. Chung and E. L. Ritman are with the Department Physiology and Biophysics, Mayo Medical School, Mayo Foundation, Rochester, MN. IEEE Log Number 9036385.
PY - 1990/12
Y1 - 1990/12
N2 - 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.
AB - 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.
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U2 - 10.1109/42.61754
DO - 10.1109/42.61754
M3 - Article
AN - SCOPUS:0025661499
SN - 0278-0062
VL - 9
SP - 384
EP - 395
JO - IEEE transactions on medical imaging
JF - IEEE transactions on medical imaging
IS - 4
ER -