Search: WFRF:(Romu Thobias)
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Automatic and quant...
Automatic and quantitative assessment of regional muscle volume by multi-atlas segmentation using whole-body water–fat MRI
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- Karlsson, Anette (author)
- Linköpings universitet,Medicinsk informatik,Tekniska högskolan,Centrum för medicinsk bildvetenskap och visualisering, CMIV
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- Rosander, Johannes (author)
- Advanced MR Analytics AB, Linköping, Sweden
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- Romu, Thobias (author)
- Linköpings universitet,Medicinsk informatik,Tekniska högskolan,Centrum för medicinsk bildvetenskap och visualisering, CMIV
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- Tallberg, Joakim (author)
- Linköpings universitet,Centrum för medicinsk bildvetenskap och visualisering, CMIV
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- Grönqvist, Anders (author)
- Linköpings universitet,Avdelningen för radiologiska vetenskaper,Hälsouniversitetet,Centrum för medicinsk bildvetenskap och visualisering, CMIV
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- Borga, Magnus (author)
- Linköpings universitet,Medicinsk informatik,Tekniska högskolan,Centrum för medicinsk bildvetenskap och visualisering, CMIV
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- Dahlqvist Leinhard, Olof (author)
- Östergötlands Läns Landsting,Linköpings universitet,Avdelningen för radiologiska vetenskaper,Hälsouniversitetet,Centrum för medicinsk bildvetenskap och visualisering, CMIV,Radiofysikavdelningen US
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(creator_code:org_t)
- 2014-08-11
- 2015
- English.
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In: Journal of Magnetic Resonance Imaging. - : John Wiley & Sons. - 1053-1807 .- 1522-2586. ; 41:6, s. 1558-1569
- Related links:
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https://urn.kb.se/re...
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https://doi.org/10.1...
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Abstract
Subject headings
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- PurposeTo develop and demonstrate a rapid whole-body magnetic resonance imaging (MRI) method for automatic quantification of total and regional skeletal muscle volume.Materials and MethodsThe method was based on a multi-atlas segmentation of intensity corrected water–fat separated image volumes. Automatic lean muscle tissue segmentations were achieved by nonrigid registration of atlas datasets with 10 different manually segmented muscle groups. Ten subjects scanned at 1.5 T and 3.0 T were used as atlases, initial validation and optimization. Further validation used 11 subjects scanned at 3.0 T. The automated and manual segmentations were compared using intraclass correlation, true positive volume fractions, and delta volumes.ResultsFor the 1.5 T datasets, the intraclass correlation, true positive volume fractions (mean ± standard deviation, SD), and delta volumes (mean ± SD) were 0.99, 0.91 ± 0.02, −0.10 ± 0.70L (whole body), 0.99, 0.93 ± 0.02, 0.01 ± 0.07L (left anterior thigh), and 0.98, 0.80 ± 0.07, −0.08 ± 0.15L (left abdomen). The corresponding values at 3.0 T were 0.97, 0.92 ± 0.03, −0.17 ± 1.37L (whole body), 0.99, 0.93 ± 0.03, 0.03 ± 0.08L (left anterior thigh), and 0.89, 0.90 ± 0.04, −0.03 ± 0.42L (left abdomen). The validation datasets showed similar results.ConclusionThe method accurately quantified the whole-body skeletal muscle volume and the volume of separate muscle groups independent of field strength and image resolution.
Subject headings
- MEDICIN OCH HÄLSOVETENSKAP -- Klinisk medicin -- Radiologi och bildbehandling (hsv//swe)
- MEDICAL AND HEALTH SCIENCES -- Clinical Medicine -- Radiology, Nuclear Medicine and Medical Imaging (hsv//eng)
- TEKNIK OCH TEKNOLOGIER -- Medicinteknik -- Medicinsk bildbehandling (hsv//swe)
- ENGINEERING AND TECHNOLOGY -- Medical Engineering -- Medical Image Processing (hsv//eng)
Keyword
- multi-atlas segmentation; muscles; registra- tion; muscle volume; classification; MRI
Publication and Content Type
- ref (subject category)
- art (subject category)
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