A descriptive framework for the field of deep learning applications in medical images

摘要

Deep learning in medical image analysis is a typical interdisciplinary application, which needs support and cooperation of computer techniques and medical experience, and has broad application prospects. Since 2017, the number of related published articles has increased exponentially, imposing a burden on the literature review in this field. In this survey, we clustered 2068 retrieved articles into 15 topics through Latent Dirichlet Allocation (LDA) and provided a rough overview on the application of deep learning in medical images. On this basis, we conducted a detailed review with 77 top representative articles. We built a descriptive review framework based on LDA and discussed classification, object detection, segmentation, and image generation applications in medical images for the field of deep learning from the perspective of image modalities. We ended with discussing current challenges and future research directions of deep learning in medical images analysis.