Please use this identifier to cite or link to this item:
https://hdl.handle.net/20.500.14365/2900
Title: | Segmentation of abdominal organs from MR images using multi-level hierarchical classification | Other Titles: | Batin bölgesi organlarinin mr görüntülerinden çok aşamali hiyerarşik siniflama ile bölütlenmesi | Authors: | Selvi, Esref Selver, M. Alper Kavur, Ali Emre Guzelis, Cuneyt Dicle, Oguz |
Keywords: | Segmentation MR hierarchical classification abdomen Combining Multiple Classifiers Automatic Segmentation Neural-Network Ct Atlas Recognition |
Publisher: | Gazi Univ, Fac Engineering Architecture | Abstract: | Medical imaging modalities can provide very detailed and informative mappings of the anatomy of a subject. These detailed and informative mappings can be processed to extract the information of interest instead of dealing with whole data (segmentation). Since manual segmentation on each slice is time consuming, tedious and operator dependent, automatic tools and techniques are needed. Segmentation of abdominal organs is a very challenging field of application due to overlapping intensity ranges of the organs, variations in human anatomy and pathology and the number of studies is very limited for Magnetic Resonance (MR), which is a relatively newer and rapidly developing imaging modality. Since it is obligatory to analyze and visualize MR images of abdominal organs (i.e. liver, right/left kidneys, spleen, pancreas, gall bladder) for several medical procedures, the main goal of this paper is to design and develop a segmentation system (method+software), which is robust to the challenges mentioned above, adaptive to the properties of the abdominal organs as well as to the interrelationships of these organs. | URI: | https://hdl.handle.net/20.500.14365/2900 | ISSN: | 1300-1884 1304-4915 |
Appears in Collections: | Scopus İndeksli Yayınlar Koleksiyonu / Scopus Indexed Publications Collection WoS İndeksli Yayınlar Koleksiyonu / WoS Indexed Publications Collection |
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