Techniques for Improving Medical Image Analysis: from Traditional Methods to Deep Learning Methods

Publication date
January 2021

Abstract

Medical imaging has become an increasingly critical step in modern healthcare diagnostics and procedures. Accurate representations of medical images plays an important role in early detection, monitoring, diagnosis and follow-up therapy. Deep learning algorithms, in particular convolutional neural networks(CNNs), have been widely employed for analysing medical images. While CNNs shows the capabilities to solve challenging tasks such as classification, segmentation and object detection, there remain several challenges towards medical image analysis due to the shortage of training data, class imbalance, time consuming and expensive annotation.This thesis presents a series of interdisciplinary researches at deep learning and medical image anal...

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