U of T Technology & Startup Explorer

An optical sensing technology that offers greater sensitivity, bandwidth, and dynamic range than existing sensors.

Machine learning architecture offers a novel, high-fidelity means of assessing lung physiology during the performance of (monofrequency) oscillometry tests.

Pulmonary Embolism (PE) diagnosis using machine learning (ML) techniques on CT pulmonary angiography (CTPA) is transforming the field of medical imaging. PE is a life-threatening condition where blood clots block the pulmonary arteries, requiring timely and accurate detection to improve patient outcomes. Traditional training and development of ML models for PE diagnosis involve extensive annotation, which is resource-intensive. To make these applications practical, the team has developed optimized training strategies, model architectures, and deployment pipelines for efficient PE detection.

This technology includes a suite of inventions, including a fully-functional coded-exposure-pixel (CEP) camera prototype, a novel programmable CMOS sensor, and a method for adaptive adjustment of exposure of every pixel, based on changes in the brightness of the scene for that pixel to extend dynamic range at native sensor resolution.

Toronto Annotation Suite (TORAS) is a web-based AI-powered annotation platform.

Based on thermal and optical sensing analysis of digital imaging, this technology allows for rapid measurement of photoplethysmogram (PPG), temperature, respiratory rate, and heart rate beyond conventional distance limitations (e.g. at distances more than 1m), with the ability to add other components (e.g. tissue oxygenation and blood pressure) in the future.

A DCE-MRI acquisition and reconstruction package that enables more accurate quantification of physiological parameters in larger volumes than any state-of-the-art method. By first performing a high-temporal (rapid), high spatial (hifi) acquisition of anatomical details in the image set, each time frame is reconstructed with a high degree of precision and accuracy.

Hippocamera is a memory augmentation technology that aides in the recall and storage of memories. The technology features novel methods to tag and replay recorded moments to promote rich reliving and storage of experiences.

Centivizer is a modular system that physically, cognitively, and socially stimulates individuals with dementia by providing self-initiated, reward-based activities that can be used 24/7 without needing caregiver support.