Auto Segmentation of Lymph Node Microscopy Images

Abstract

The manual histology assessment on the biopsy tissue sample still remains the gold standard procedure for cancer  and its progression in human body. Auto nuclei segmentation is an important method to measure cellularity but often suffered an issue due to the  present of overlapping nuclei. The implementation of auto segmentation of cells could speed up the process of histology assessment for cancer cases. The first step to implement, a wide data profile of normal and cancerous need to be compile and analyze further as a reference guide. Tissue data profile can be collected based on cellularity property of the tissue which can be automatically segmented using MATLAB software. The objective of the study is to develop an auto nuclei segmentation using MATLAB software to measure cellularity between normal and cancerous cells of lymph node tissue. Histological images of the tissue were analyzed using MATLAB software by using thresholding method and the result was compared with ImageJ. The pre-processing part of the image processing incudes converting the image into 8-bit grayscale image. The segmentation parts include adaptive filtering to remove the noise using Wiener filter and the thresholding Otsu method. Results from the ImajeJ and manual counting on the cellularity shows a comparable results to the automated cellularity measured using MATLAB. The cellularity of the cancerous lymph nodes was found lower than normal lymph nodes.