Jun Jiang is an Assistant Professor and computational biomedical engineer with nine years of experience applying data-driven methods to histopathology and multi-modal biomedical imaging to improve disease diagnosis and treatment. Trained with a PhD in Biomedical Engineering, he has advanced imaging-phenotype correlations at Mayo Clinic and now leads research at UTHealth Houston to elucidate cancer mechanisms and inform personalized therapies. His work blends deep learning, image analysis, and clinical insight to reveal biologically meaningful patterns from routine pathology slides—translating algorithmic findings toward actionable clinical biomarkers. Active on GitHub, he focuses on reproducible computational tools for biomedical image analysis, reflecting a commitment to open, clinically relevant research.
Simple prototype of converting whole slide image (WSI) to multiframe DICOM images
Contributions:14 commits, 9 pushes, 1 branch in 2 years 9 months
dicomwsiconvertsvsimage-format
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