Using advanced digital imaging and AI to improve prostate cancer diagnosis
Virtual Digital Histopathology with Explainable Deep Learning for Prostate Cancer Diagnosis
This study is working on using advanced computer technology to help doctors better understand prostate cancer by analyzing tissue samples, making it easier to spot tumors and explain the results clearly.
Quick facts
| Grant type | R21 grant |
|---|---|
| Study type | NIH-funded research |
| Funding institution | University of California-Irvine NIH-funded |
| Lab location | 1 site (Irvine, United States) |
| Project ID | NIH-10990125 on NIH RePORTER |
What this research studies
This research focuses on enhancing prostate cancer diagnosis through the use of digital histopathology and deep learning algorithms. By analyzing tissue biopsy images, the project aims to automate tumor segmentation and provide clearer explanations of the results to clinicians. The approach involves converting non-stained biopsy images into virtual stained versions, allowing for better evaluation of tumor characteristics and aiding in accurate diagnosis. The goal is to improve the interpretability of these advanced imaging techniques for better clinical adoption.
Who could benefit from this research
Good fit: Ideal candidates for this research are individuals undergoing prostate biopsies for suspected cancer.
Not a fit: Patients who have already been diagnosed and treated for prostate cancer may not benefit from this research.
Why it matters
Potential benefit: If successful, this research could lead to more accurate and reliable prostate cancer diagnoses, ultimately improving patient outcomes.
How similar studies have performed: Previous research has shown promise in using deep learning for cancer diagnosis, indicating potential success for this novel approach.
Where this research is happening
Irvine, United States
- University of California-Irvine — Irvine, United States (Active)
Researchers
- Principal investigator: Shah, Pratik — University of California-Irvine
- Study coordinator: Shah, Pratik
About this research
- This is an active NIH-funded research project — typically early-stage science, not a clinical trial accepting patient enrollment.
- Some NIH-funded labs run parallel clinical studies or seek volunteers for related work. To check, contact the principal investigator or institution listed above.
- For full project details, budget, and progress reports, visit the official NIH RePORTER page below.