A Survey of Deep Learning Models for Medical Image Analysis

Mohammad Umer, Shilpa Sharma, Punam Rattan
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引用次数: 1

Abstract

Deep learning algorithms have lately risen to prominence as the primary tool for processing medical images. These algorithms are suitable for solving these image processing problems because of their efficient learning abilities and the potential to deal with complex problems relatively easily. Deep Learning's usefulness in health domain has grown drastically over the past few years as the amount of medical data has expanded exponentially. The main deep learning models, that have become popular over a last few years, relevant to medical image analysis are reviewed in this work. Various studies based on medical image analysis using deep learning models are surveyed in this study. This study provides an overview of various technologies used in Deep Learning in medical imagery and gives a brief idea about their performance.
医学图像分析的深度学习模型综述
深度学习算法最近成为处理医学图像的主要工具。这些算法由于其高效的学习能力和相对容易处理复杂问题的潜力而适用于解决这些图像处理问题。随着医疗数据量呈指数级增长,深度学习在健康领域的有用性在过去几年中急剧增长。在这项工作中,回顾了过去几年流行的与医学图像分析相关的主要深度学习模型。本研究综述了基于深度学习模型的医学图像分析的各种研究。本研究概述了医学图像中深度学习所使用的各种技术,并简要介绍了它们的性能。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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