The Role of SYCL in the “Machine-Learning Assisted Gigantic Image Cancer Margin Scanner” Project

Опубликовано 8 января 2025, 14:01

MAGIC-SCAN is an ambitious and innovative project integrating advanced microscopy, automation, and machine learning to tackle the long-standing issue of incomplete tumor removal in cancer surgery. It aims to be the world’s fastest high-resolution tissue scanner, enabling surgeons to locate residual cancer cells within the operating room. In this presentation, Dr. Valerio Pascucci, Professor, Scientific Computing and Imaging Institute, and Kahlert School of Computing, University of Utah, and doctoral student Alper Sahistan, discuss how they address this challenge by using data management and processing techniques developed over almost two decades of high-performance computing research – including acceleration of ZFP data compression on GPUs through SYCL to manage the images – and novel strategies for lightning-fast image processing and ML inference at the edge for effective deployment in the operating room of a rural hospital.

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University of Utah – MAGIC-SCAN: Deploying AI in the Operating Room to Improve Cancer Surgery Outcomes | Intel Software