综述:深度学习在数字病理图像中的应用

      Review on Applications of Deep Learning in Pathological Images

      • 摘要: 计算机辅助的病理图像分析方法能够提升医师的阅片效率和诊断准确性,有效应对病理诊断人力短缺的问题。随着人工智能和数字病理学的快速发展,深度学习技术在组织病理学领域催生了大量研究。该文综述了深度学习在数字病理图像分析中的多种应用,如病理图像分割、癌症诊断和预后预测等,并探讨了应用中的挑战及解决方案。该文还预测了深度学习在病理图像分析中的未来趋势,并提出了潜在的研究方向。

         

        Abstract: Computer-assisted methods for pathological image analysis can enhance the efficiency and accuracy of doctors' image reading, effectively addressing the shortage of pathology diagnostic manpower. With the rapid development of artificial intelligence and digital pathology, deep learning technology has spurred a wealth of research in the field of histopathology. This article reviews the various applications of deep learning in digital pathological image analysis, such as pathological image segmentation, cancer diagnosis, and prognosis prediction, and discusses the challenges and solutions in its application. The article also predicts future trends in deep learning for pathological image analysis and proposes potential research directions.

         

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