人工智能在乳腺结节BI-RADS分类诊断中的研究进展
Research progress of artificial intelligence in BI-RADS classification and diagnosis of breast nodules
叶涛 1徐华春 1李华玉 1李强1
作者信息
- 1. 宁波大学附属人民医院影像科 浙江 宁波 315040
- 折叠
摘要
乳腺结节分类及乳腺密度分类是乳腺成像报告和数据系统(BI-RADS)的两个重要方面,目前存在结节分类易误诊、医师间一致性低等缺点,人工智能(artificial intelligence,AI)可以高效、准确分类结节及密度并提高医师间诊断结论的一致性,具有广阔的应用前景,近年来也出现了较多的新研究成果.本文就AI在BI-RADS分类诊断中的最新研究进展作一综述.
Abstract
Breast nodule classification and breast density classification are two important aspects of breast imaging reporting and data systems(BI-RADS).Currently,there are shortcomings such as easy misdiagnosis of nodule classification and low con-sistency among physicians.Artificial intelligence(AI)can efficiently and accurately classify nodules and densities,and improve the consistency of diagnostic conclusions among doctors,with broad application prospects.In recent years,there have also been many new research achievements.This article provides a review of the latest research progress on AI in BI-RADS classification di-agnosis.
关键词
乳腺肿瘤/乳腺密度/影像组学/机器学习Key words
Breast neoplasms/Breast density/Radiomics/Machine learning引用本文复制引用
基金项目
浙江省自然科学基金(LGF20H180005)
浙江省自然科学基金(LY24H160002)
浙江省宁波市自然科学基金重点项目(2023J021)
出版年
2024
NETL
NSTL
维普
万方数据