Barstugan, MucahidCeylan, RahimeAsoglu, SemihCebeci, HakanKoplay, Mustafa2020-03-262020-03-262018978-1-5386-6878-8https://hdl.handle.net/20.500.12395/36647International Conference on Artificial Intelligence and Data Processing (IDAP) -- SEP 28-30, 2018 -- Inonu Univ, Malatya, TURKEYLiver segmentation process is a challenging field in computer-aided medical image analysis. This study implemented liver segmentation on Abdominal MR images. The liver was automatically segmented from images by morphological methods with high performance. Liver segmentation process was implemented on 56 MR images and the segmentation results were examined. In this study, an effective and fast method was proposed. Seven evaluation metrics (sensitivity, specificity, accuracy, precision, Dice coefficient, Jaccard rate, Structural Similarity Index (SSIM)) were used to test the performance of the proposed method. Mean Dice coefficient value was obtained as 91.701%, mean Jaccard rate value was obtained as 85.052% on 56 images. Segmentation duration for an image (T1 and T2 phases) was found as 2.828 seconds with the proposed method.eninfo:eu-repo/semantics/closedAccessEvaluation metricsliver segmentationmorphological methodsMR imagesConference ObjectN/AWOS:000458717400077N/A