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.
Stacked Sparse Autoencoder (SSAE) for Nuclei Detection on Breast Cancer Histopathology Images
