Automated segmentation of colon gland using histology images

This paper represents an automated methodology for segmentation of colon glands using histology images. The manifestations of colorectal cancer under microscope has always been challenging as staining and sectioning leads to variation in tissue specimen, which causes conflict in gland appearance. Gland segmentation and classification is very important for the automation of the system. The presented methodology automatically segments the colon gland tissues by using intensity based thresholding which makes this methodology efficient. Unlike other segmentation methods, this methodology is entirely automated and quantifies lumen and epithelial cells only in the region of interest, which makes this method computationally efficient. This methodology is efficient for calculation of number of glands as well as for segmentation of gland area and achieves overall 93.76% accuracy for both.