Automatic detection of myocardial contours in cine-computed tomographic images

Journal Article · Wed Jun 01 04:00:00 EDT 1994 · IEEE Transactions on Medical Imaging (Institute of Electrical and Electronics Engineers); (United States)

DOI:https://doi.org/10.1109/42.293917· OSTI ID:7082206

Philip, K P; Dove, E L; Stanford, W; Chandran, K B ^[1]; McPherson, D D; Gotteiner, N L; Vonesh, M J ^[2]; Reed, J E; Rumberger, J A ^[3]

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1. Univ. of Iowa, Iowa City, IA (United States). Dept. of Biomedical Engineering
2. Northwestern Univ., Chicago, IL (United States). Dept. of Internal Medicine
3. Mayo Clinic, Rochester, MN (United States). Dept. of Cardiovascular Diseases

Quantitative evaluation of cardiac function from cardiac images requires the identification of the myocardial walls. This generally requires the clinician to view the image and interactively trace the contours. This method is susceptible to great variability that depends on the experience and knowledge of the particular operator tracing the contours. The particular imaging modality that is used may also add tracing difficulties. Cine-computed tomography (cine-CT) is an imaging modality capable of providing high quality cross-sectional images of the heart. CT images, however, are cluttered. To decrease this variability, investigators have developed computer-assisted or near-automatic techniques for tracing these contours. All of these techniques, however, require some operator intervention to confidently identify myocardial borders. The authors present a new algorithm that automatically finds the heart within the chest, and then proceeds to outline the myocardial contours. Information at each tomographic slice is used to estimate the contours at the next tomographic slice, thus allowing the algorithm to work in near-apical cross-sectional images where the myocardial borders are often difficult to identify. The algorithm does not require operator input and can be used in a batch mode to process large quantities of data. An evaluation and correction phase is included to allow an operator to view the results and selectively correct portions of contours. They tested the algorithm by automatically identifying the myocardial borders of 27 cardiac images obtained from three human subjects and quantitatively comparing these automatically determined borders with those traced by an experienced cardiologist.

• OSTI ID: 7082206
• Journal Information: IEEE Transactions on Medical Imaging (Institute of Electrical and Electronics Engineers); (United States), Journal Name: IEEE Transactions on Medical Imaging (Institute of Electrical and Electronics Engineers); (United States) Vol. 13:2; ISSN 0278-0062; ISSN ITMID4
• Country of Publication: United States
• Language: English

Related Subjects

550601* -- Medicine-- Unsealed Radionuclides in Diagnostics
62 RADIOLOGY AND NUCLEAR MEDICINE
ALGORITHMS
BODY
CARDIOVASCULAR DISEASES
CARDIOVASCULAR SYSTEM
COMPUTERIZED TOMOGRAPHY
COUNTING TECHNIQUES
DIAGNOSTIC TECHNIQUES
DISEASES
HEART
IMAGE PROCESSING
MATHEMATICAL LOGIC
MUSCLES
MYOCARDIUM
ORGANS
PROCESSING
RADIOISOTOPE SCANNING
TOMOGRAPHY