Please use this identifier to cite or link to this item: https://hdl.handle.net/20.500.13091/228
Title: Full-Automatic Liver Segmentation on Abdominal MR Images
Authors: Barstuğan, Mücahid
Ceylan, Rahime
Asoğlu, Semih
Cebeci, Hakan
Koplay, Mustafa
Keywords: Evaluation metrics
liver segmentation
morphological methods
MR images
Issue Date: 2018
Publisher: IEEE
Abstract: Liver 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.
Description: International Conference on Artificial Intelligence and Data Processing (IDAP) -- SEP 28-30, 2018 -- Inonu Univ, Malatya, TURKEY
URI: https://hdl.handle.net/20.500.13091/228
ISBN: 978-1-5386-6878-8
Appears in Collections:Mühendislik ve Doğa Bilimleri Fakültesi Koleksiyonu
Scopus İndeksli Yayınlar Koleksiyonu / Scopus Indexed Publications Collections
WoS İndeksli Yayınlar Koleksiyonu / WoS Indexed Publications Collections

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