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Found 6 papers, 4 papers with code
Improved Multimodal Fusion for Small Datasets with Auxiliary Supervision
We validate the proposed approaches on prostate cancer diagnosis from paired histopathology imaging and tabular clinical features.
Detection of prostate cancer in whole-slide images through end-to-end training with image-level labels
As such, developing algorithms which do not require manual pixel-wise annotations, but can learn using only the clinical report would be a significant advancement for the field.
Streaming convolutional neural networks for end-to-end learning with multi-megapixel images
This method exploits the locality of most operations in modern convolutional neural networks by performing the forward and backward pass on smaller tiles of the image.
Neural Ordinary Differential Equations for Semantic Segmentation of Individual Colon Glands
Automated medical image segmentation plays a key role in quantitative research and diagnostics.
Automated Gleason Grading of Prostate Biopsies using Deep Learning
We developed a fully automated deep learning system to grade prostate biopsies.
Training convolutional neural networks with megapixel images
To train deep convolutional neural networks, the input data and the intermediate activations need to be kept in memory to calculate the gradient descent step.
