Automated coronary CT angiography plaque-lumen segmentation

We are investigating the feasibility of a computer-aided detection (CAD) system to assist radiologists in diagnosing coronary artery disease in ECG gated cardiac multi-detector CT scans having calcified plaque. Coronary artery stenosis analysis is challenging if calcified plaque or the iodinated blood pool hides viable lumen. The research described herein provides an improved presentation to the radiologist by removing obscuring calcified plaque and blood pool. The algorithm derives a Gaussian estimate of the point spread function (PSF) of the scanner responsible for plaque blooming by fitting measured CTA image profiles. An initial estimate of the extent of calcified plaque is obtained from the image evidence using a simple threshold. The Gaussian PSF estimate is then convolved with the initial plaque estimate to obtain an estimate of the extent of the blooming artifact and this plaque blooming image is subtracted from the CT image to obtain an image largely free of obscuring plaque. In a separate step, the obscuring blood pool is suppressed using morphological operations and adaptive region growing. After processing by our algorithm, we are able to project the segmented plaque-free lumen to form synthetic angiograms free from obstruction. We can also analyze the coronary arteries with vessel tracking and centerline extraction to produce cross sectional images for measuring lumen stenosis. As an additional aid to radiologists, we also produce plots of calcified plaque and lumen cross-sectional area along selected blood vessels. The method was validated using digital phantoms and actual patient data, including in one case, a validation against the results of a catheter angiogram.