人工智能
深度学习
计算机科学
管道(软件)
图像分割
分割
同种类的
基于分割的对象分类
批判性评价
尺度空间分割
组分(热力学)
计算机视觉
图像(数学)
机器学习
模式识别(心理学)
医学
数学
病理
程序设计语言
替代医学
物理
组合数学
热力学
作者
Mohammad Hesam Hesamian,Wei Jia,Xiangjian He,Paul J. Kennedy
标识
DOI:10.1007/s10278-019-00227-x
摘要
Deep learning-based image segmentation is by now firmly established as a robust tool in image segmentation. It has been widely used to separate homogeneous areas as the first and critical component of diagnosis and treatment pipeline. In this article, we present a critical appraisal of popular methods that have employed deep-learning techniques for medical image segmentation. Moreover, we summarize the most common challenges incurred and suggest possible solutions.
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