# of Displayed Technologies: 3 / 3

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Virtual image generation of immunohistochemical stained tissue sections using an artificial neural network
TS-039781 — Realistic immunohistochemical stained tissue section databases for training, certification, and machine standards.
Immunohistochemistry (IHC) is used to determine antigen distribution in a tissue and is widely used for diagnosis of cancers and other diseases. Diagnostic and research laboratories in the United States use locally devised IHC tissue slide preparation and scanning protocols to check scanner perfor…
  • College: College of Medicine (COM)
  • Inventors: Gurcan, Metin; Lozanski, Gerard; Senaras, Caglar
  • Licensing Officer: Hampton, Andrew

Automated Detection of Tumor Budding in Colorectal Cancer
TS-039267 — A non-invasive and automated tumor budding image analysis system for colorectal cancer. This program can detect tumor buds in traditional H&E stained sections without the need for manual assessment.
Colorectal cancer is the third most commonly diagnosed cancer in the United States. With a survival rate of less than 65%, early detection and treatment are key factors in survival. Tumor budding, associated with higher tumor stage, lymph node metastasis, and decreased disease-free survival, has e…
  • College: College of Medicine (COM)
  • Inventors: Gurcan, Metin; Ahmad Fauzi, Mohammad Faizal; Chen, Wei "Wei"; Frankel, Wendy
  • Licensing Officer: Hampton, Andrew

At-Home Digital Platform for Scoring Skin Disease
TS-038429 — An automated image analysis system for the recognition and quantification of skin disease
Acne and rosacea are skin diseases that affect around 85% of individuals, the former being the most common skin condition afflicting up to 50 million people. There is no gold standard for evaluation of these skin diseases, and their treatment efficacy is generally determined according to a poorly …
  • College: College of Medicine (COM)
  • Inventors: Kaffenberger, Benjamin; Gurcan, Metin
  • Licensing Officer: Hampton, Andrew

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