Automatic detection of cardiac abnormalities in low dose chest CT scans using machine learning techniques
A small randomly selected subset of the data will be used for training the machine learning algorithms. Remaining large dataset will be used to perform quantitative evaluation and to understand generalization abilities of the proposed algorithms.
1) Develop an automated heart segmentation algorithm to measure heart volume and to define a region of interest for the calcium detection algorithm.
2) Develop an automated calcium scoring algorithm in low-dose chest CT.
3) Develop an automated aorta segmentation algorithm and measure aortic diameters.
4) Develop an automated pulmonary artery segmentation algorithm and measure pulmonary diameter.
5) Perform a quantitative evaluation of the algorithms in a large dataset
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