Biological Vision Inspired Systems in Biomedical Applications

Abstract

This Master of Philosophy thesis presents two potential biomedical applications of an event-based camera, also known as a neuromorphic vision system (camera) or silicon retina vision sensor. Event-based cameras have drawn significant interest due to their advantages over traditional cameras, including low latency, high data throughput, high dynamic range, and low power consumption. Hence endless research is actively seeking for potential applications of event-based cameras.

Flow cytometry, a highly effective technology renowned for its rapid analysis of cells or particles suspended in a solution, has been extensively utilized across diverse disciplines. These include immunology, virology, molecular biology, cancer biology, and infectious disease monitoring. Conventional imaging flow cytometers generally suffer from motion blur, low dynamic range, and trade-offs between the frame rate (speed) and image resolution. In this thesis, we conducted a feasibility study with algorithmic results to propose an event-based high-throughput flow cytometer.

Navigation devices that demonstrate the capability of guiding blind or vision-impaired people have always remained a challenge over the past decade. The reasons for this could be because of the limited data throughput, undesirable user feedback, and the requirement for power consumption. Hence we here propose a proof-of-concept blind navigation system with an event-based camera.