Zhou H, Machupalli R, Mandal M. Efficient FPGA Implementation of Automatic Nuclei Detection in Histopathology Images.
J Imaging 2019;
5:jimaging5010021. [PMID:
34465711 PMCID:
PMC8320863 DOI:
10.3390/jimaging5010021]
[Citation(s) in RCA: 3] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/30/2018] [Revised: 12/27/2018] [Accepted: 01/11/2019] [Indexed: 11/17/2022] Open
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.
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