International Journal of Aquatic Science ISSN: 2008-8019 Vol 12, Issue 03, 2021 1581 Detection Of Abnormal Liver In Ultrasonic Images From Fcm Features Harikumar Rajaguru 1 , R.Karthikamani 2 1 Professor, Department of Electronics and Communication Engineering, Bannari Amman Institute of Technology, Sathyamangalam, India 2 Assistant Professor, Electronics and Instrumentation Engineering, Bannari Amman Institute of Technology, Sathyamangalam, India Email: harikumarr@bitsathy.ac.in 1 , karthikamani@bitsathy.ac.in 2 Abstract.. The objective of this paper is to detect the liver abnormalities from ultrasonic image database. The liver cancer is one of the major health issuesnow a day. Medical Imaging techniques are proposed to diagnose the abnormalities in the earlier stage. In this paper extracted Fuzzy C means (FCM) Clustering features of liver images and five classifiers like Expectation maximization, Gaussian Mixture Model, Linear Discriminant Analysis,Bayesian Linear Discriminant Analysis Classifier, Logistic regression classifier are used to detect the normal or abnormal condition of the liver. The classifier performance are analyzed by the bench mark parameters Sensitivity, Specificity, Accuracy, Precision, Error Rate, Mathew Correlation Coefficient (MCC), and Classifier Success Index (CSI) and compared. The Logistic regression achieved a higher accuracy of 80.95% and outperformed other four classifiers. Keywords:FCM, GMM, LDA, BLDC. 1. INTRODUCTION The liver is most essential organ in the human body that performs various function such as eradicating waste materials from the blood, maintains blood sugar and producing important nutrient for the human body. Unlike other diseases liver abnormalities will not have noticeable symptoms in the initial level [1]. According to the analysis of WHO, liver cancer is also one of the major reasons of the death around the world. More over liver cirrhosis is the second prominent type of cancer in men and the seventh cancer type in women. Therefore, earlier identification of disease plays a vital role for proper treatment. Several imaging techniques are available for the diagnosis of liver diseases but most frequently used modality is ultrasound imaging, because of low cost and it does not produce any radiation. So the image processing and classification algorithms are mostly used in the detection of liver abnormalities [2]. The following is the structure of the paper: The paper is introduced in subdivision 1. The materials and processes are explained in subdivision 2. The classifiers are discussed in Subdivision 3. Subdivision 4 gives insight into the results. This article concluded in Subdivision 5. 2. MATERIALS AND METHODS