Automated Detection of Cell Nuclei in Histopathology Slide Images: A Comprehensive Approach for Diagnostic Support

Histopathology slide images serve as microscopic representations of tissue samples vital for disease diagnosis, staging, and treatment planning. This paper proposes an approach for automated detection of cell nuclei in histopathology slide images, aiming to assist pathologists in their diagnostic processes. The method involves a sequence of image processing steps, including resizing, grayscale conversion, noise removal, adaptive thresholding, object removal, and hole filling for image segmentation. A morphological opening is applied to eliminate small structures, followed by a Circular Hough Transform for nucleus detection with specific radii and sensitivity settings. The Watershed transform, using detected nuclei as markers, enhances the visualization of irregular shapes. Promising results are demonstrated in the detection of nuclei in colon, adrenal, and thyroid cells, offering potential support to pathologists in diagnosis and evaluation. The paper suggests future improvements and feature incorporation for a more comprehensive analysis in subsequent developments.