Multimodal Deep Learning for Cervical Dysplasia Diagnosis

MICCAI, pp. 115-123, 2016.

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Abstract:

To improve the diagnostic accuracy of cervical dysplasia, it is important to fuse multimodal information collected during a patient’s screening visit. However, current multimodal frameworks suffer from low sensitivity at high specificity levels, due to their limitations in learning correlations among highly heterogeneous modalities. In th...More

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