Towards Smarter, Continuous Urinalysis
Harnessing AI and image-based insights for early detection and better patient outcomes.
This platform is part of an evolving research effort to enhance microscopic urinalysis through image processing and artificial intelligence. We aim to improve diagnostic accuracy, enable longitudinal monitoring, and reduce missed detections during routine clinical visits.
Our central hypothesis: missed objects in urine images may represent missed opportunities for early intervention. We seek to identify, understand, and eventually prevent such oversights—through both existing techniques and novel AI methods.
Detect Missed Objects
Analyze patterns where professionals overlook diagnostically relevant objects, and explore the causes.
Assess Diagnostic Impact
Study whether missed objects relate to early indicators of disease and evaluate the consequences of oversight.
Leverage & Innovate AI
Apply and improve computer vision models to flag subtle or overlooked objects in microscopy images.
“Each clinical urinalysis should contribute to a patient's long-term diagnostic history.”
By building a longitudinal record of image-based urinalysis, we aim to support trend detection, chronic condition tracking, and a more informed diagnostic process for every patient.
Try the Demo
Upload a urine microscopy image, get AI-based detections, and generate a report.
For Researchers
Collaborate, share insights, or contribute to the knowledge base.
For Clinicians
Join the study, test the tool, or contribute sample images.