Hardware-based neural network accelerators for onboard computational imaging offer immense potential to enhance the efficiency, speed, and quality of imaging processes directly within devices. These cutting-edge solutions are poised to significantly impact medical technology. At RPI, we are leading the co-design and implementation of innovative onboard neural network accelerators to develop the first smart fluorescence camera. This breakthrough technology will enable real-time assessment of novel drug therapies and enhance fluorescence-guided surgeries. This effort is a collaborative initiative involving IBM and Dr. Charbon's group at EPFL, who are at the forefront of manufacturing the next generation of highly sensitive time-resolved cameras.

Lead PI: Dr. Xavier Intes