AI-driven 3D Spatial Transcriptomics

no code implementations • 25 Feb 2025 • Cristina Almagro-Pérez, Andrew H. Song, Luca Weishaupt, Ahrong Kim, Guillaume Jaume, Drew F. K. Williamson, Konstantin Hemker, Ming Y. Lu, Kritika Singh, Bowen Chen, Long Phi Le, Alexander S. Baras, Sizun Jiang, Ali Bashashati, Jonathan T. C. Liu, Faisal Mahmood

A comprehensive three-dimensional (3D) map of tissue architecture and gene expression is crucial for illuminating the complexity and heterogeneity of tissues across diverse biomedical applications.

Multimodal Whole Slide Foundation Model for Pathology

2 code implementations • 29 Nov 2024 • Tong Ding, Sophia J. Wagner, Andrew H. Song, Richard J. Chen, Ming Y. Lu, Andrew Zhang, Anurag J. Vaidya, Guillaume Jaume, Muhammad Shaban, Ahrong Kim, Drew F. K. Williamson, Bowen Chen, Cristina Almagro-Perez, Paul Doucet, Sharifa Sahai, Chengkuan Chen, Daisuke Komura, Akihiro Kawabe, Shumpei Ishikawa, Georg Gerber, Tingying Peng, Long Phi Le, Faisal Mahmood

The field of computational pathology has been transformed with recent advances in foundation models that encode histopathology region-of-interests (ROIs) into versatile and transferable feature representations via self-supervised learning (SSL).

Cross-Modal Retrieval model +4

HEST-1k: A Dataset for Spatial Transcriptomics and Histology Image Analysis

1 code implementation • 23 Jun 2024 • Guillaume Jaume, Paul Doucet, Andrew H. Song, Ming Y. Lu, Cristina Almagro-Pérez, Sophia J. Wagner, Anurag J. Vaidya, Richard J. Chen, Drew F. K. Williamson, Ahrong Kim, Faisal Mahmood

Spatial transcriptomics enables interrogating the molecular composition of tissue with ever-increasing resolution and sensitivity.

Benchmarking Representation Learning +1