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首页> 外文期刊>Journal of vision >The 'Gist' of the Abnormal in Radiology Scenes: Where is the Signal?
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The 'Gist' of the Abnormal in Radiology Scenes: Where is the Signal?

机译:放射学场景异常的“要点”:信号在哪里?

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Humans are very adept at extracting the "gist" of a scene in as little as a fraction of a second. This "gist" perception can be learned for novel stimuli. We have found that this extends to the gist of breast cancer. Radiologists can distinguish between normal mammograms and those containing subtle signs of cancer at above chance levels with 250 msec exposure but are at chance in localizing the abnoramility. This pattern of results suggests that they are detecting a global signal of abnormality. What are the stimulus properties that might support this ability? Across four experiments, we systematically investigated the nature of the "gist" signal by asking radiologists to make detection and localization responses about briefly presented mammograms in which the spatial frequency, symmetry and/or size of the images was manipulated. Interestingly, the signal is stronger in the higher spatial frequencies. Performance is poor with low-pass filtered images but almost as good with high-pass as with unfiltered images. Performance does not depend on detection of breaks in the normal symmetry of left and right breasts. Moreover, above chance classification is possible using images of the normal breast of a patient with overt signs of cancer in the other breast. Some signal is present in the portions of the parenchyma (breast tissue) that do not contain a lesion or that are in the contralateral breast. This signal does not appear to be a simple assessment of breast density. The experiments indicate that detection may be based on a widely-distributed image statistic, learned by experts (Non-expert observers perform at chance). The finding that global signal related to disease can be detected in parenchyma independent of the appearance of the cancer may have further relevance in the clinic.
机译:人类非常善于在短短的几分之一秒内提取出场景的“要点”。这种“要旨”感知可以通过新颖的刺激来学习。我们已经发现这延伸到乳腺癌的要点。放射科医生可以区分正常的乳房X线照片和在250毫秒以上的较高机会水平下包含细微癌症征象的乳房X线照片,但有机会定位其异常性。这种结果模式表明,他们正在检测异常的整体信号。哪些刺激特性可以支持此功能?在四个实验中,我们通过要求放射科医生对简要介绍的乳房X线照片进行检测和定位响应,从而系统地研究了“主”信号的性质,在X线照片中对空间频率,对称性和/或图像大小进行了处理。有趣的是,信号在较高的空间频率下更强。低通滤波图像的性能较差,但高通滤波的性能与未滤波图像的性能几乎一样。性能并不取决于检测到左右乳房的正常对称性是否破裂。此外,使用另一只乳房中有明显癌症迹象的患者正常乳房的图像可以进行以上机会分类。在薄壁组织(乳房组织)中不包含病变或对侧乳腺中存在一些信号。该信号似乎不是对乳房密度的简单评估。实验表明,检测可能基于专家们掌握的广泛分布的图像统计信息(非专家观察员会偶然地执行)。可以在实质中检测到与疾病有关的全局信号,而与癌症的出现无关,这一发现可能在临床上具有进一步的意义。

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