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Updated: Oct 22, 2025

Using Computer Vision Libraries to Streamline Nuclei Quantification
Published on: June 6, 2025
Efficient FPGA Implementation of Automatic Nuclei Detection in Histopathology Images
Haonan Zhou1, Raju Machupalli1, Mrinal Mandal1
1Department of Electrical and Computer Engineering, University of Alberta, Edmonton, AB T6G 2R3, Canada.
Abstract:
Accurate and efficient detection of cell nuclei is an important step towards the development of a pathology-based Computer Aided Diagnosis. Generally, high-resolution histopathology images are very large, in the order of billion pixels, therefore nuclei detection is a highly compute intensive task, and software implementation requires a significant amount of processing time. To assist the doctors in real time, special hardware accelerators, which can reduce the processing time, are required. In this paper, we propose a Field Programmable Gate Array (FPGA) implementation of automated nuclei detection algorithm using generalized Laplacian of Gaussian filters. The experimental results show that the implemented architecture has the potential to provide a significant improvement in processing time without losing detection accuracy.

