Segmentation of Abdominal Organs From Mr Images Using Multi-Level Hierarchical Classification
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Date
2015
Journal Title
Journal ISSN
Volume Title
Publisher
Gazi Univ, Fac Engineering Architecture
Open Access Color
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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.
Description
Keywords
Segmentation, MR, hierarchical classification, abdomen, Combining Multiple Classifiers, Automatic Segmentation, Neural-Network, Ct, Atlas, Recognition
Fields of Science
Citation
WoS Q
Q3
Scopus Q
Q3
Source
Journal of the Faculty of Engıneerıng And Archıtecture of Gazı Unıversıty
Volume
30
Issue
3
Start Page
533
End Page
546
SCOPUS™ Citations
21
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Web of Science™ Citations
19
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2
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