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Segmentation Of Intracranial Structures From Noncontrast Ct Images With Deep Learning, Evan Porter
Segmentation Of Intracranial Structures From Noncontrast Ct Images With Deep Learning, Evan Porter
Wayne State University Dissertations
Presented in this work is an investigation of the application of artificially intelligent algorithms, namely deep learning, to generate segmentations for the application in functional avoidance radiotherapy treatment planning. Specific applications of deep learning for functional avoidance include generating hippocampus segmentations from computed tomography (CT) images and generating synthetic pulmonary perfusion images from four-dimensional CT (4DCT).A single institution dataset of 390 patients treated with Gamma Knife stereotactic radiosurgery was created. From these patients, the hippocampus was manually segmented on the high-resolution MR image and used for the development of the data processing methodology and model testing. It was determined that …