A Comprehensive Review of Medical Image Analysis Technology Based on CNN

Abstract

In recent years, artificial intelligence technology has achieved remarkable breakthroughs in the field of healthcare. CNN, with its powerful image feature extraction capability, has become a vital technical pillar in the field of medical image analysis. At the model level, this paper systematically combs the innovative characteristics of typical CNN architectures and their adaptive improvements in the medical imaging field, clarifying the technological development context. At the application level, it focuses on four core tasks of medical image analysis, i.e., classification, boundary detection, registration, and text-integrated analysis. Datasets corresponding to each task and their acquisition methods are also meticulously organized, providing technical guidance and data support for related research.