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

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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.

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Keywords

Segmentation, MR, hierarchical classification, abdomen, Combining Multiple Classifiers, Automatic Segmentation, Neural-Network, Ct, Atlas, Recognition

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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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