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Updated: Jul 7, 2026

Area-based Image Analysis Algorithm for Quantification of Macrophage-fibroblast Cocultures
Published on: February 15, 2022
Optoelectronic region of interest detection: an application in automated cytology
Abstract:
Diagnostic cytology, which is used to screen for cervical cancer, involves characterizing cellular features such as shape, size, and texture. Automated screening of cervical smear slides is desirable but computationally challenging since each slide requires processing 2 x 10(9) pixels at a resolution of 0.8 mum per pixel. We demonstrate that the throughput of optical processors can be exploited in automated cervical smear-screening systems. In particular, we identify a morphological shape detector to perform the initial region of interest (ROI) detection and to demonstrate experimentally its optoelectronic implementation. The ROI detector is tested on 200 images, and its performance is characterized as a receiver operating characteristic (ROC). The area under the ROC curve is as high as 96.4% of the total area. The simulation and the experimental results are found comparable, and the discrepancy between the two results is determined to be a function of the number of bits represented in the filter plane device.

