计算机科学与探索2026，Vol.20Issue(1)：79-98,20.DOI:10.3778/j.issn.1673-9418.2502055
面向2D医学图像检测的YOLO算法研究综述
Review of YOLO Algorithm Research for 2D Medical Image Detection
摘要
Abstract
In recent years,the breakthrough development of artificial intelligence technology has promoted a paradigm change in the interdisciplinary field of medicine and engineering,among which the object detection algorithm based on deep learning has shown significant advantages in medical image analysis.As a typical representative of the single-stage detection framework,the YOLO(you only look once)series algorithms have demonstrated unique advantages of high real-time,strong generalization ability and precise positioning in the field of medical image analysis through the"end-to-end"detection paradigm,and have gradually become the mainstream research methods for lesion detection,cell recognition and other tasks.The research of YOLO improved algorithm for medical object detection is sorted out.Firstly,based on the dimension of algorithm architecture innovation,the core evolution path of 12 generations of basic algorithms from YOLOv1 to YOLOv11 is sorted out,and the improvement breakthroughs,advantages and limitations,and medical scene performance of each version of YOLO are compared and analyzed.Secondly,the classic open-source datasets in the field of medical object detection are summarized,and the commonly used evaluation indicators in object detection are expounded.At the same time,the literature research on the use of YOLO improved algorithm in the detection of cervical cells,blood cells,pulmonary nodules and diabetic retinopathy in 2D medical images is reviewed,and different improved methods are comprehensively compared and analyzed.Finally,this paper summarizes the medical scenarios corresponding to different improvement ideas of YOLO,and discusses the challenges and future development directions in this field.关键词
深度学习/目标检测/YOLO/宫颈细胞检测/血细胞检测/肺结节检测/糖尿病视网膜病变检测Key words
deep learning/object detection/YOLO/detection of cervical cells/detection of blood cells/detection of pulmonary nodules/detection of diabetic retinopathy分类
信息技术与安全科学引用本文复制引用
郭振,刘静,仇大伟,李宇皓..面向2D医学图像检测的YOLO算法研究综述[J].计算机科学与探索,2026,20(1):79-98,20.基金项目
国家自然科学基金面上项目(82174528) （82174528）
山东省专业学位研究生教学案例库建设项目(SDYAL21054) （SDYAL21054）
山东中医药大学青年科研创新团队项目(校科字[2024]1号) （校科字[2024]1号）
山东中医药大学科学研究基金面上项目(KYZK2024M14).This work was supported by the National Natural Science Foundation of China(82174528),the Teaching Case Library Construction Project for Professional Degree Graduates in Shandong Province(SDYAL21054),the Youth Scientific Research and Innovation Team Project of Shandong University of Traditional Chinese Medicine,and the General Project of Scientific Research Fund of Shandong University of Traditional Chinese Medicine(KYZK2024M14). （KYZK2024M14）
