Grading of colorectal cancer using histology images
Namita Sengar, Neeraj Mishra, Malay Kishore Dutta, Jiří Přinosil, Radim Bürget · 2016
This paper proposed an automated system for grading of colorectal cancer using image processing method. Almost, half a million people die every year due to colon cancer. Histopathological tissue analysis is a common method for its detection, which needs an expert pathologist. Screening for this cancer is effective for prevention as well as early detection. The method proposed segment the glands automatically by using intensity based thresholding and organizational properties for classification. In existing literature, the majority of studies based on gland segmentation in healthy or benign samples, but rarely on intermediate or high grade cancer. Unlike most of the existing methods this system is fully automated and grades the images as benign healthy, benign adenomatous, moderately differentiated malignant and poorly differentiated malignant. The proposed method achieves overall accuracy of 81% when tested on 165 histology images.