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3
Visual search in breast imaging.乳腺影像学中的视觉搜索。
Br J Radiol. 2019 Oct;92(1102):20190057. doi: 10.1259/bjr.20190057. Epub 2019 Jul 18.
4
Digital Breast Tomosynthesis: Concepts and Clinical Practice.数字乳腺断层合成:概念与临床实践。
Radiology. 2019 Jul;292(1):1-14. doi: 10.1148/radiol.2019180760. Epub 2019 May 14.
5
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Cogn Res Princ Implic. 2019 Feb 22;4(1):7. doi: 10.1186/s41235-019-0159-2.
6
Automated Breast Ultrasonography (ABUS) in the Screening and Diagnostic Setting: Indications and Practical Use.自动乳腺超声(ABUS)在筛查和诊断中的应用:适应证和实际应用。
Acad Radiol. 2018 Nov;25(11):1457-1470. doi: 10.1016/j.acra.2018.02.014. Epub 2018 Mar 16.
7
Ultrasound Imaging Technologies for Breast Cancer Detection and Management: A Review.用于乳腺癌检测与管理的超声成像技术:综述
Ultrasound Med Biol. 2018 Jan;44(1):37-70. doi: 10.1016/j.ultrasmedbio.2017.09.012. Epub 2017 Oct 26.
8
Comparing search patterns in digital breast tomosynthesis and full-field digital mammography: an eye tracking study.数字乳腺断层合成与全视野数字乳腺摄影的搜索模式比较:一项眼动追踪研究。
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9
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10
A 'snapshot' of the visual search behaviours of medical sonographers.医学超声检查技师视觉搜索行为的“快照”
Australas J Ultrasound Med. 2015 May;18(2):70-77. doi: 10.1002/j.2205-0140.2015.tb00045.x. Epub 2015 Dec 31.

眼动追踪能告诉我们放射科医生如何使用自动乳腺超声。

What eye tracking can tell us about how radiologists use automated breast ultrasound.

作者信息

Wolfe Jeremy M, Lyu Wanyi, Dong Jeffrey, Wu Chia-Chien

机构信息

Brigham and Women's Hospital, Boston, Massachusetts, United States.

Harvard Medical School, Boston, Massachusetts, United States.

出版信息

J Med Imaging (Bellingham). 2022 Jul;9(4):045502. doi: 10.1117/1.JMI.9.4.045502. Epub 2022 Jul 26.

DOI:10.1117/1.JMI.9.4.045502
PMID:35911209
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC9315059/
Abstract

: Automated breast ultrasound (ABUS) presents three-dimensional (3D) representations of the breast in the form of stacks of coronal and transverse plane images. ABUS is especially useful for the assessment of dense breasts. Here, we present the first eye tracking data showing how radiologists search and evaluate ABUS cases. : Twelve readers evaluated single-breast cases in 20-min sessions. Positive findings were present in 56% of the evaluated cases. Eye position and the currently visible coronal and transverse slice were tracked, allowing for reconstruction of 3D "scanpaths." : Individual readers had consistent search strategies. Most readers had strategies that involved examination of all available images. Overall accuracy was 0.74 (sensitivity = 0.66 and specificity = 0.84). The 20 false negative errors across all readers can be classified using Kundel's (1978) taxonomy: 17 are "decision" errors (readers found the target but misclassified it as normal or benign). There was one recognition error and two "search" errors. This is an unusually high proportion of decision errors. Readers spent essentially the same proportion of time viewing coronal and transverse images, regardless of whether the case was positive or negative, correct or incorrect. Readers tended to use a "scanner" strategy when viewing coronal images and a "driller" strategy when viewing transverse images. These results suggest that ABUS errors are more likely to be errors of interpretation than of search. Further research could determine if readers' exploration of all images is useful or if, in some negative cases, search of transverse images is redundant following a search of coronal images.

摘要

自动乳腺超声(ABUS)以冠状面和横断面图像堆栈的形式呈现乳腺的三维(3D)图像。ABUS对致密型乳腺的评估特别有用。在此,我们展示了首批眼动追踪数据,以显示放射科医生如何搜索和评估ABUS病例。12名读者在20分钟的时间段内评估单乳病例。在56%的评估病例中发现了阳性结果。追踪眼位以及当前可见的冠状面和横断面切片,从而能够重建三维“扫描路径”。个体读者具有一致的搜索策略。大多数读者的策略包括检查所有可用图像。总体准确率为0.74(敏感性 = 0.66,特异性 = 0.84)。所有读者的20例假阴性错误可根据昆德尔(1978年)分类法进行分类:17例为“决策”错误(读者发现了目标但将其错误分类为正常或良性)。有1例识别错误和2例“搜索”错误。这是决策错误的比例异常高。无论病例是阳性还是阴性、正确还是错误,读者查看冠状面和横断面图像所花费的时间比例基本相同。读者在查看冠状面图像时倾向于使用“扫描器”策略,在查看横断面图像时倾向于使用“钻孔器”策略。这些结果表明,ABUS错误更可能是解释错误而非搜索错误。进一步的研究可以确定读者对所有图像的探索是否有用,或者在某些阴性病例中,在搜索冠状面图像之后搜索横断面图像是否多余。