VISION Lab
Visual Intelligence for Scalable Imaging and Open-source iNnovation
Advancing computational pathology, multiplex imaging, and visual intelligence through open鈥憇ource, scalable AI research.
About the Lab
The VISION Lab advances research at the intersection of computational pathology, multiplex tissue imaging, computer vision, and scalable AI. We develop novel methods, software tools, and machine learning models that enable high鈥憆esolution analysis of whole鈥憇lide images, multiplex and immunofluorescence imaging platforms, and multimodal biomedical datasets. A central focus of the lab is the quantitative characterisation of the tumour microenvironment, including tumour-immune interactions and spatial cellular organisation across diverse cancer types.
We place particular emphasis on spatial and multiplex immunofluorescence imaging to study tissue heterogeneity, cell-cell interactions, and disease mechanisms at single鈥慶ell and tissue scales. Through the development of open鈥憇ource, reproducible, and trustworthy AI tools such as TIAToolbox, we aim to empower global research communities with robust, scalable solutions for tissue analytics and digital pathology.
Our mission is to translate visual intelligence into practical, clinically relevant solutions by collaborating across disciplines, including pathology, oncology, radiology, computer science, and systems biology. Through international partnerships and a commitment to open innovation, VISION Lab aims to shape the future of AI鈥慸riven imaging, digital diagnostics, and data鈥慸riven understanding of the tumour microenvironment.
Research Themes
- Computational Pathology
- Spatial and Multiplex Tissue Imaging and Analysis
- Multimodal Data Integration
- Open鈥慡ource and Reproducible AI for Pathology
- Computer Vision and Image Analysis Across Domains
Projects Led by VISION Lab
-
HistoMaps funded by MRC 鈥� Stain鈥慳gnostic tissue representation learning for scalable tumour microenvironment mapping.
- INSPIRE (鲍碍鈥揗补濒补测蝉颈补) funded by British Council - AI and multimodal imaging methods for identifying diagnostic biomarkers in nasopharyngeal carcinoma prevalent in LMIC populations.
Collaborative Projects
- 鈥� (Led by Raza) 鈥� The TIA Centre鈥檚 flagship project, an open鈥憇ource computational pathology library, co鈥慸eveloped with researchers across Warwick (including PRISM labLink opens in a new window, APOLLO lab) and international collaborators.
- 鈥� funded by the ERC, led by Radboud, Warwick investigators Rajpoot & Raza
- COBIx鈥� funded by NIHR, led by Rajpoot, Multi-site validation study of the Colon and Rectal Endoscopic Biopsy (COBIx) reporting tool
Past Projects (including Collaborative Projects)
- Precision VISION 鈥� funded by CRUK, led by (Sheffield), Warwick investigator Raza
-
PathLAKE plus鈥� funded by Innovate UK, led by Rajpoot
People
Alumini
Dr Abdullah Alsalemi
Publications
Please click for a full list of publications.
Software & Resources
-
鈥� Open鈥憇ource computational pathology
- 鈥� Cell Detection and Classification using winner of , and grand challenges
- 鈥� A Cell-Level Coarse-to-Fine Image Registration Engine for Multi-stain Image Alignment