Fig. 1: Heatmap visualisation of image-based deep learning predictions of malignancy. | Nature Communications

Fig. 1: Heatmap visualisation of image-based deep learning predictions of malignancy.

From: Development and validation of an interpretable model integrating multimodal information for improving ovarian cancer diagnosis

Fig. 1

Visual explanations of DL models are definitely important for qualitative review and clinical relevance, namely irregular solid components, projections, and areas with abundant blood flow signals. a Carcinosarcoma of a 44-year old female; b high-grade serous carcinoma of a 65-year old female; and (c) hydrosalpinx of a 49-year old female that was misdiagnosed by all readers but showed a low probability of malignancy in the heatmap. In the first row of each case, the first two images are B-mode images, and the following one is the colour Doppler image. The images in the second row are their corresponding heatmaps.

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