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- Implementation of the paper "Deep Learning-based Prediction of Breast Cancer Tumor and Immune Phenotypes from Histopathology" by Tiago Gonçalves, Dagoberto Pulido-Arias, Julian Willett, Katharina V. Hoebel, Mason Cleveland, Syed Rakin Ahmed, Elizabeth Gerstner, Jayashree Kalpathy-Cramer, Jaime S. Cardoso, Christopher P. Bridge and Albert E. Kim.
preprocessing
Public`preprocessing` is a python library designed for the purpose of preprocessing MRI data at QTIM. It currently supports reorganization of dicom and nifti files to follow BIDS conventions, dicom to nifti conversion, and preprocessing for brain data. Its outputs are intended to follow the BIDS organizational scheme.Challenges
PublicGA_Prospective_Study
Publicwandb-deploy-example
Publicsegmentation_generic
PublicOptimEYES-Anaylsis
PublicEyeLiner
PublicCorisDB_Curation
Publicmodel_conversion
PublicOPTIMEyes
PublicsegmentationMonaiLabel
Publiccodabench
PublicCodabench is a flexible, easy-to-use and reproducible benchmarking platform. Check our paper at Patterns Cell Press https://hubs.li/Q01fwRWB0FL_ViT_pretraining
Publictrame_optimeyes
Publicvideo_action_annotation
Publicvideo_action_annotator
PublicMedSAM
Publicqtim-lab.github.io
Publicdl-prediction-brca-tiph
PublicImplementation of the paper "Deep Learning-based Prediction of Breast Cancer Tumor and Immune Phenotypes from Histopathology" by Tiago Gonçalves, Dagoberto Pulido-Arias, Julian Willett, Katharina V. Hoebel, Mason Cleveland, Syed Rakin Ahmed, Elizabeth Gerstner, Jayashree Kalpathy-Cramer, Jaime S. Cardoso, Christopher P. Bridge and Albert E. Kim.hardwareProjects
PublicLLM-Report-Labeling
Publicconvert_images
PublicOphVideoMAE2
PublicimageNet
Public