计算机工程与应用 ›› 2021, Vol. 57 ›› Issue (6): 1-9.DOI: 10.3778/j.issn.1002-8331.2009-0046

• 热点与综述 • 上一篇    下一篇

淋巴瘤图像分类技术研究综述

张晓丽,张魁星,江梅,魏本征,丛金玉   

  1. 1.山东中医药大学 智能与信息工程学院,济南 250355
    2.山东中医药大学 医学人工智能研究中心,山东 青岛 266112
    3.山东中医药大学 青岛中医药科学院,山东 青岛 266112
  • 出版日期:2021-03-15 发布日期:2021-03-12

Review of Image Classification Technology for Lymphoma

ZHANG Xiaoli, ZHANG Kuixing, JIANG Mei, WEI Benzheng, CONG Jinyu   

  1. 1.College of Intelligence and Information Engineering, Shandong University of Traditional Chinese Medicine, Jinan 250355, China
    2.Center for Medical Artificial Intelligence, Shandong University of Traditional Chinese Medicine, Qingdao, Shandong 266112, China
    3.Qingdao Academy of Chinese Medical Sciences, Shandong University of Traditional Chinese Medicine, Qingdao, Shandong 266112, China
  • Online:2021-03-15 Published:2021-03-12

摘要:

淋巴瘤是源于淋巴造血系统的一类恶性肿瘤,基于医学影像及病理图像的精准诊断对临床治疗淋巴瘤具有重要价值。随着机器学习和深度学习技术的发展,利用人工智能技术对淋巴瘤图像分类已成为医学领域的研究热点之一。对淋巴瘤影像及病理图像分类技术的研究进展进行了系统总结与分析,并重点阐述了基于机器学习等新技术的图像分类方法与研究概况,对淋巴瘤图像分类的相关技术做了总结与展望。

关键词: 淋巴瘤, 医学图像, 特征提取, 深度学习, 机器学习

Abstract:

Lymphoma is a kind of malignant tumor originated from the lymphoid hematopoietic system. Accurate diagnosis based on medical image and pathological image is of great value for its clinical treatment. With the development of machine learning and deep learning technology, the use of artificial intelligence to classify lymphoma images has become a research hotspot in the field of medicine. This paper systematically summarizes and analyzes the research progress of lymphoma imaging and pathological image classification technology, and focuses on the image classification methods and research overview based on new technologies such as machine learning, and finally summarizes and prospects the related technologies of lymphoma image classification.

Key words: lymphoma, medical image, feature extraction, deep learning, machine learning