Sebastiano Fabio Schifano

About

Sebastiano Fabio Schifano is a researcher at the forefront of applying reconfigurable hardware to medical image analysis. His work centers on high-performance computing, field-programmable gate arrays (FPGAs), and deep neural network (DNN) acceleration, with a specific focus on cardiovascular imaging. Schifano’s major contributions lie in the real-time segmentation of aortic valve calcium lesions—a critical task for diagnosing and managing heart disease. He has pioneered the use of FPGA-based Deep Processing Units (DPUs) to deploy convolutional neural networks (CNNs) for this purpose, demonstrating that hardware acceleration can achieve the speed and efficiency needed for clinical workflows. His most cited paper, “Segmentation of Aortic Valve Calcium Lesions Using FPGA Accelerators” (2025, 2 citations), along with his benchmark study using the Vitis AI toolchain, provides a rigorous, reproducible framework for translating complex DNN models into practical, low-latency medical tools. By bridging the gap between advanced computer vision and resource-constrained medical environments, Schifano’s work is paving the way for faster, more accessible diagnostic support in cardiology.

Research Focus

Key Achievements

Top Papers

1. 1
   Segmentation of Aortic Valve Calcium Lesions Using FPGA Accelerators

   2 citations · 2025
2. 2
   Benchmarking a DNN for aortic valve calcium lesions segmentation on FPGA-based DPU using the vitis AI toolchain

   1 citations · 2025

Key Collaborators

Contact & Links