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.
Highlights
Many diseases are diagnosed based on the cellular structures in their respective tissue specimens as the cellular structures can provide quantitative information about the diseases and help in the study of disease progression
Due to a wide variety of nuclei appearances in different organs, and staining procedures, accurate and efficient segmentation of cell nuclei is an important step in most histopathology-based computer-aided diagnosis (CAD) techniques
A software implementation of the CAD technique requires a significant amount of processing time
Summary
Many diseases are diagnosed based on the cellular structures in their respective tissue specimens as the cellular structures can provide quantitative information about the diseases and help in the study of disease progression. In human intervened diagnosis procedure, histopathologists typically examine the tissue under a microscope, and the diagnostic accuracy depends on the pathologists’ personal experience, which sometimes leads to intra and inter observer variability [2]. To overcome these limitations, several computer-aided diagnosis (CAD) techniques have been proposed in the literature for the diagnosis. Due to a wide variety of nuclei appearances in different organs, and staining procedures, accurate and efficient segmentation of cell nuclei is an important step in most histopathology-based CAD techniques. The detection of cells in a histology image may be the first step towards cell segmentation
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