Quantum Methods for Neural Networks and Application to Medical Image Classification

By Jonas Landman et al

Published on Dec. 11, 2022

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Table of Contents

1. Introduction
2. Quantum Methods for Neural Networks
2.1 Quantum data-loaders
2.2 Quantum-assisted Neural Networks
2.3 Quantum Orthogonal Neural Network
3. Experimental Results

Summary

This paper introduces quantum methods for neural networks focusing on medical image classification. Two new quantum methods are proposed: quantum-assisted neural networks and Quantum Orthogonal Neural Network (QOrthoNN). The methods leverage quantum circuits for linear algebraic tasks and training classical neural networks. Experimental results show that quantum neural networks achieve comparable accuracy to classical ones in medical image classification tasks, paving the way for the use of quantum methods in visual tasks.