A Framework for Automatic Morphological Feature Extraction and Analysis of Abdominal Organs in MRI Volumes.
The accurate 3D reconstruction of organs from radiological scans is an essential tool in computer-aided diagnosis (CADx) and plays a critical role in clinical, biomedical and forensic science research. The structure and shape of the organ, combined with morphological measurements such as volume and...
| Published in: | Journal of Medical Systems Vol. 43; no. 12; pp. 1 - 11 |
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| Main Authors: | , , , |
| Format: | diagnostic images equations & formulas pictorial research tables/charts Journal Article |
| Published: |
Springer Nature
Dec2019
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| Online Access: | View this record in EBSCOhost |
| fields | @attributes: recordID: 1 pdfLink: plink: https://search.ebscohost.com/login.aspx?direct=true&db=ccm&AN=140292674&site=ehost-live header: @attributes: shortDbName: ccm uiTerm: 140292674 longDbName: CINAHL Complete uiTag: AN controlInfo: bkinfo: dissinfo: jinfo: jid: 01485598 4N0 jtl: Journal of Medical Systems issn: 01485598 maglogo: N pubinfo: dt: Dec2019 vid: 43 iid: 12 pid: 237 pub: Springer Nature place: New York, New York artinfo: ui: 140292674 140292674 140292674 10.1007/s10916-019-1474-3 140292674 ppf: 1 ppct: 10 formats: fmt: – @attributes: type: T – @attributes: type: P tig: atl: A Framework for Automatic Morphological Feature Extraction and Analysis of Abdominal Organs in MRI Volumes. aug: au: Asaturyan, Hykoush Thomas, E. Louise Bell, Jimmy D. Villarini, Barbara affil: School of Computer Science and Engineering, University of Westminster, London, UK sug: subj: Abdomen Anatomy and Histology Imaging, Three-Dimensional Methods Magnetic Resonance Imaging Human Adult Conceptual Framework Pancreas Liver Descriptive Statistics Computing Methodologies Abdominal Fat Nonalcoholic Fatty Liver Disease Adult: 19-44 years ab: The accurate 3D reconstruction of organs from radiological scans is an essential tool in computer-aided diagnosis (CADx) and plays a critical role in clinical, biomedical and forensic science research. The structure and shape of the organ, combined with morphological measurements such as volume and curvature, can provide significant guidance towards establishing progression or severity of a condition, and thus support improved diagnosis and therapy planning. Furthermore, the classification and stratification of organ abnormalities aim to explore and investigate organ deformations following injury, trauma and illness. This paper presents a framework for automatic morphological feature extraction in computer-aided 3D organ reconstructions following organ segmentation in 3D radiological scans. Two different magnetic resonance imaging (MRI) datasets are evaluated. Using the MRI scans of 85 adult volunteers, the overall mean volume for the pancreas organ is 69.30 ± 32.50cm3, and the 3D global curvature is (35.23 ± 6.83) × 10−3. Another experiment evaluates the MRI scans of 30 volunteers, and achieves mean liver volume of 1547.48 ± 204.19cm3 and 3D global curvature (19.87 ± 3.62) × 10− 3. Both experiments highlight a negative correlation between 3D curvature and volume with a statistical difference (p < 0.0001). Such a tool can support the investigation into organ related conditions such as obesity, type 2 diabetes mellitus and liver disease. pubtype: Academic Journal doctype: diagnostic images equations & formulas pictorial research tables/charts Journal Article ougenre: Article language: English refInfo: holdings: @attributes: islocal: N |
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