Skip to content

Cluster Triplet Loss for Unsupervised Domain Adaptation on Histology Images and Joint Prediction of Response to Therapy, Molecular Traits, and Spatial Organisation in Colorectal Cancer Biopsies

Notifications You must be signed in to change notification settings

rubywood/MultitaskGraphDomainAdaptation

Repository files navigation

Multitask Graph Therapy Response and Domain Adaptation with Cluster Triplet Loss


In the main folder, find code for the paper: Joint Prediction of Response to Therapy, Molecular Traits, and Spatial Organisation in Colorectal Cancer Biopsies

Cite this paper

Wood, R. et al. (2023). Joint Prediction of Response to Therapy, Molecular Traits, and Spatial Organisation in Colorectal Cancer Biopsies. In: Greenspan, H., et al. Medical Image Computing and Computer Assisted Intervention – MICCAI 2023. MICCAI 2023. Lecture Notes in Computer Science, vol 14224. Springer, Cham. https://doi.org/10.1007/978-3-031-43904-9_73


In the Clustering folder, find code for the paper: Cluster Triplet Loss for Unsupervised Domain Adaptation on Histology Images

Cite this paper

Wood, Ruby, et al. "Cluster Triplet Loss for Unsupervised Domain Adaptation on Histology Images." Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition. 2024. https://openaccess.thecvf.com/content/CVPR2024W/DEF-AI-MIA/papers/Wood_Cluster_Triplet_Loss_for_Unsupervised_Domain_Adaptation_on_Histology_Images_CVPRW_2024_paper.pdf

About

Cluster Triplet Loss for Unsupervised Domain Adaptation on Histology Images and Joint Prediction of Response to Therapy, Molecular Traits, and Spatial Organisation in Colorectal Cancer Biopsies

Resources

Stars

Watchers

Forks

Releases

No releases published

Packages

No packages published

Languages