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Interpretable pap smear cell representation for cervical cancer screening
Findings demonstrate that a score can be calculated for cell abnormality without training models with abnormal samples and localize abnormality to interpret our results with a novel metric based on absolute difference in cross entropy in agglomerative clustering.
Lesion Conditional Image Generation for Improved Segmentation of Intracranial Hemorrhage from CT Images
A lesion conditional image (segmented mask) is an input to both the generator and the discriminator of the LcGAN during training.
How much data is needed to train a medical image deep learning system to achieve necessary high accuracy?
In this paper, we present a study on determining the optimum size of the training data set necessary to achieve high classification accuracy with low variance in medical image classification systems.
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