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Fig. 5 | BMC Medical Imaging

Fig. 5

From: The efficacy of deep learning models in the diagnosis of endometrial cancer using MRI: a comparison with radiologists

Fig. 5

Three cases of false negatives were observed in the single image set of axial ADC: a A 55-year-old woman with grade 1 endometrioid carcinoma, in which the CNN was able to diagnose cancer, but the readers 1, 2, and 3 were not (the CNN confidence; cancer = 99.9%). The image shows a tiny tumor filling the uterine cavity (arrow); b A 34-year-old woman with grade 1 endometrioid carcinoma, in which all the three readers could diagnose cancer, but the CNN could not (the CNN confidence; cancer = 18.8%). The image shows a massive tumor protruding into the myometrium of the posterior wall of the uterus (arrow); c A 31-year-old woman with grade 2 endometrioid carcinoma, in which neither the CNN nor the three readers could diagnose the presence of cancer (the CNN confidence; cancer = 22.5%). The image shows the tumor filling the uterine cavity (arrow). A slight decrease in the single image of ADC map might have made the diagnosis of tumor difficult with a single image without considering the other images for radiologists

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