Deep Learning for Medical Imaging From Diagnosis Prediction to its Counterfactual Explanation

Sumedha Singla

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arXiv · 2209.02929

Deep Learning for Medical Imaging From Diagnosis Prediction to its Counterfactual Explanation

Sumedha Singla

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Abstract

Deep neural networks (DNN) have achieved unprecedented performance in computer-vision tasks almost ubiquitously in business, technology, and science. While substantial efforts are made to engineer highly accurate architectures and provide usable model explanations, most state-of-the-art approaches are first designed for natural vision and then translated to the medical domain. This dissertation seeks to address this gap by proposing novel architectures that integrate the domain-specific constraints of medical imaging into the DNN model and explanation design.

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eess.IV cs.CV

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Sumedha Singla. 2022-09-07. Deep Learning for Medical Imaging From Diagnosis Prediction to its Counterfactual Explanation. https://arxiv.org/abs/2209.02929

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