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在胸部 X 光片中识别肺癌的感知学习。

Perceptual learning in the identification of lung cancer in chest radiographs.

机构信息

Department of Psychology, University of Minnesota, N240 Elliott Hall, 75 East River Road, Minneapolis, MN, 55455, USA.

School of Psychology, University of Queensland, Brisbane, Australia.

出版信息

Cogn Res Princ Implic. 2020 Feb 3;5(1):4. doi: 10.1186/s41235-020-0208-x.

Abstract

Extensive research has shown that practice yields highly specific perceptual learning of simple visual properties such as orientation and contrast. Does this same learning characterize more complex perceptual skills? Here we investigated perceptual learning of complex medical images. Novices underwent training over four sessions to discriminate which of two chest radiographs contained a tumor and to indicate the location of the tumor. In training, one group received six repetitions of 30 normal/abnormal images, the other three repetitions of 60 normal/abnormal images. Groups were then tested on trained and novel images. To assess the nature of perceptual learning, test items were presented in three formats - the full image, the cutout of the tumor, or the background only. Performance improved across training sessions, and notably, the improvement transferred to the classification of novel images. Training with more repetitions on fewer images yielded comparable transfer to training with fewer repetitions on more images. Little transfer to novel images occurred when tested with just the cutout of the cancer region or just the background, but a larger cutout that included both the cancer region and some surrounding regions yielded good transfer. Perceptual learning contributes to the acquisition of expertise in cancer image perception.

摘要

大量研究表明,实践可以产生高度特定的简单视觉属性的感知学习,例如方向和对比度。这种相同的学习是否能体现出更复杂的感知技能?在这里,我们研究了复杂医学图像的感知学习。新手在四个会话中接受训练,以区分两张胸片中哪一张包含肿瘤,并指出肿瘤的位置。在训练中,一组接受了 6 次 30 张正常/异常图像的重复,另一组接受了 3 次 60 张正常/异常图像的重复。然后,对各组进行了训练和新图像的测试。为了评估感知学习的性质,测试项目以三种格式呈现 - 完整图像、肿瘤的裁剪或仅背景。随着训练的进行,表现逐渐提高,并且显著的是,这种提高可以转移到对新图像的分类上。在更少的图像上进行更多重复的训练可以产生与在更多图像上进行更少重复的训练相当的转移效果。仅用癌症区域的裁剪或仅用背景进行测试时,向新图像的转移很少,但包含癌症区域和一些周围区域的较大裁剪可以产生良好的转移效果。感知学习有助于癌症图像感知专业知识的获取。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0dc9/6997313/0e43d67128f2/41235_2020_208_Fig1_HTML.jpg

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