2022
DOI: 10.1101/2022.03.07.22272004
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Phase Recognition in Contrast-Enhanced CT Scans based on Deep Learning and Random Sampling

Abstract: Purpose: A fully automated system for interpreting abdominal computed tomography (CT) scans with multiple phases of contrast enhancement requires an accurate classification of the phases. Current approaches to classify the CT phases are commonly based on 3D convolutional neural network (CNN) approaches with high computational complexity and high latency. This work aims at developing and validating a precise, fast multi-phase classifier to recognize three main types of contrast phases in abdominal CT scans. Me… Show more

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