Automatic diagnosis of stomach adenocarcinoma using Riesz wavelet transform
P Anishiya, M. Sasikala · International Journal of Biomedical Engineering and Technology · 2020
Adenocarcinoma originates from the glands. It causes changes in the gland architecture. The detection of adenocarcinoma requires histopathological examination of tissue specimens. At present, diagnosis and grading of the cancer depends on the visual interpretation of the biopsy samples by pathologist and thus, it may lead to a considerable amount of inter and intra-observer variability. To overcome this drawback and to reduce the reliance on the human interpretation and thereby reducing the workload of pathologists, many methods have been proposed. In this paper, a novel method to quantify a tissue for the purpose of automated stomach cancer diagnosis and grading is introduced. The stomach tissue images are preprocessed to compensate for colour variations. The Riesz wavelet transform is applied to the preprocessed stomach tissue images. From Riesz wavelet coefficients, 14 different statistical features were extracted. The wrapper-based feature selection is used. The reliability check on the final dataset is performed using ANOVA. In diagnosis, the tissue is classified into normal (non-malignant), well differentiated, moderately differentiated, poorly differentiated and tissue. The proposed system yielded a classification accuracy of 93.2% in diagnosing and 98.33% in grading.