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AI in Medicine and Imaging - Stanford Symposium 2020
Through the AIMI Symposium we hope to address gaps and barriers in the field and catalyze more evidence-based solutions to improve health for all.
health medicine medical-imaging stanford
Stochastic Segmentation Networks
An efficient probabilistic method for modelling aleatoric uncertainty with any image segmentation network architecture.
segmentation health medical-imaging mri
Multimodal Brain Tumor Segmentation
Segmentation of gliomas in pre-operative MRI scans. Use the provided clinically-acquired training data to produce segmentation labels.
u-net medical-imaging tumor-segmentation computer-vision
Semixup: In- and Out-of-Manifold Regularization
Semixup is a semi-supervised learning method based on in/out-of-manifold regularization.
semi-supervised-learning manifold-regularization kl-divergence medical-imaging
GradCAM for the BreaKHis Dataset
An NBDev package for fine-tuning ResNets to visualize gradient-weighted class activation for the BreaKHis dataset.
medical-imaging computer-vision transfer-learning tutorial
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