MULTIDISCIPLINARY AI TEAM SCIENCE THAT INNOVATES AND EDUCATES

Transforming imaging data into computational pipelines to better and smarter health

What we do!

We develop novel computational methods to study and understand tissue micro-anatomy using spatial-omics data acquired via diverse technologies. Our method has implications in clinical diagnostics and allows for studying the fundamentals of biological systems. Currently, our major focus involves studying diabetic kidney disease in humans.

100 100 percent of our graduated Ph.D. students are placed in prominent pharma companies.

Lab Personnel

Latest works!

We published our work for the community on our cloud-based instance for digital pathology WSI visualization, automated segmentation, and error correction for training a semantic segmentation model. The source codedocker image, and a video overview are freely made available for the community.  

Our work integrating deep semantic segmentation and transformer models for disease progression prediction starting from digital image pixels and preserving pixel level spatial relationships between important tissue structures is available online. Great work by Ben Shickel (Assistant Professor, Medicine – Quantitative Health) and Nicholas Lucarelli.

We released FUSION (Functional Unit State Identification in WSIs), a dynamic and interactive visualization tool specialized for spatially resolved molecular-omics and histology images. Example datasets and more information can be found at here. Link to the codes.

join us!

Postdoctoral Associate position available: Job description.

Undergraduate Research Internship available: Job description.

HuBMAP Summer Internship: HuBMAP Website.

NEWS

09/19/2024 Dr. Pinaki Sarder presented “Digital Pathology Meets Spatial Omics: Emerging Problems in Data Integration, Solutions, and New Opportunities” at the University of Iowa Renal Grand Rounds. His talk focused on the challenges of integrating spatial omics data with digital pathology, offering solutions involving machine learning and AI. The presentation highlighted new opportunities for advancing renal pathology and personalized medicine, drawing attention to the transformative potential of these technologies in research and clinical care.

09/01/2024 Nicholas Gauthier’s innovative archaeology project has received crucial support through the 2024 Research Opportunity Seed Fund from UF Research in partnership with Strategic Research Development. His project aims to revolutionize the analysis of petrographic thin sections by integrating Whole Slide Imaging (WSI) and artificial intelligence (AI), automating what is traditionally a manual and labor-intensive process.

08/26/2024 The Journal of Medical Imaging (JMI) is currently inviting submissions for a special section dedicated to Computational Pathology. This is an excellent opportunity for researchers to contribute to a field that is rapidly advancing the capabilities of medical imaging in disease detection, diagnosis, and treatment. We encourage researchers working on fundamental and translational research, as well as those focused on practical applications in computational pathology, to submit their work. For more information, visit this page.

08/02/2024 Sayat Mimar, a Senior Software Engineer, has been awarded a KPMP Fall 2024 travel grant to present his research at the upcoming KPMP consortium meeting in Bethesda, MD. His work, titled “A Cloud-based Gigapixel-Size Whole Slide Image Analysis Platform for KPMP,” focuses on advancing computational pathology through innovative image analysis tools.

07/30/2024 PhD student Sam Border and his team from the CMI lab has published a new study in Scientific Reports titled “Investigating quantitative histological characteristics in renal pathology using HistoLens.” This study explores the use of HistoLens, an open-source tool developed by the lab, for the visual and quantitative analysis of histological datasets, specifically in the context of renal pathology.

PRESENTATIONS BY OUR STUDENTS