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Found 6 papers, 2 papers with code
Multimodal Breast Lesion Classification Using Cross-Attention Deep Networks
Would clinical features significantly improve breast lesion classification compared to using mammograms alone?
First arrival picking using U-net with Lovasz loss and nearest point picking method
Similar to \cite{wu2019semi}, we use U-net to perform the segmentation as it is proven to be state-of-the-art in many image segmentation tasks.
StyPath: Style-Transfer Data Augmentation For Robust Histology Image Classification
We also generated Grad-CAM representations of the results which were assessed by an experienced nephropathologist; we used this qualitative analysis to elucidate on the assumptions being made by each model.
Few Is Enough: Task-Augmented Active Meta-Learning for Brain Cell Classification
Meta-learning aims to deliver an adaptive model that is sensitive to these underlying distribution changes, but requires many tasks during the meta-training process.
DECAPS: Detail-Oriented Capsule Networks
We provide extensive experiments on the CheXpert and RSNA Pneumonia datasets to validate the effectiveness of DECAPS.
Radiologist-Level COVID-19 Detection Using CT Scans with Detail-Oriented Capsule Networks
The network then uses the activation maps to focus on regions of interest and combines both coarse and fine-grained representations of the data.
