title: 3D multimodal spatial fuzzy segmentation of intramuscular connective and adipose tissue from ultrashort TE MR images of calf muscle.
abstract: To develop and evaluate an automated algorithm to segment intramuscular adipose (IMAT) and connective (IMCT) tissue from musculoskeletal MRI images acquired with a dual echo Ultrashort TE (UTE) sequence.
  
  
  
  The dual echo images and calculated structure tensor images are the inputs to the multichannel fuzzy cluster mean (MCFCM) algorithm. Modifications to the basic multichannel fuzzy cluster mean include an adaptive spatial term and bias shading correction. The algorithm was tested on digital phantoms simulating IMAT/IMCT tissue under varying conditions of image noise and bias and on ten subjects with varying amounts of IMAT/IMCT.
  
  
  
  The MCFCM including the adaptive spatial term and bias shading correction performed better than the original MCFCM and adaptive spatial MCFCM algorithms. IMAT/IMCT was segmented from the unsmoothed simulated phantom data with a mean Dice coefficient of 0.933 ±0.001 when contrast-to-noise (CNR) was 140 and bias was varied between 30% and 65%. The algorithm yielded accurate in vivo segmentations of IMAT/IMCT with a mean Dice coefficient of 0.977 ±0.066.
  
  
  
  The proposed algorithm is completely automated and yielded accurate segmentation of intramuscular adipose and connective tissue in the digital phantom and in human calf data. Magn Reson Med 77:870-883, 2017. © 2016 International Society for Magnetic Resonance in Medicine.
authors.affiliation: Department of Physics, San Diego State University, San Diego, California, USA.
authors.forename: Vincent
authors.initials: V
authors.lastname: Ugarte
authors.affiliation: Department of Physics, San Diego State University, San Diego, California, USA.
authors.forename: Usha
authors.initials: U
authors.lastname: Sinha
authors.affiliation: Muscle Imaging and Modeling Lab, Department Of Radiology, University of California, San Diego, California, USA.
authors.forename: Vadim
authors.initials: V
authors.lastname: Malis
authors.affiliation: Muscle Imaging and Modeling Lab, Department Of Radiology, University of California, San Diego, California, USA.
authors.forename: Robert
authors.initials: R
authors.lastname: Csapo
authors.affiliation: Muscle Imaging and Modeling Lab, Department Of Radiology, University of California, San Diego, California, USA.
authors.forename: Shantanu
authors.initials: S
authors.lastname: Sinha
mesh_terms: D000273:Adipose Tissue / Q000000981:diagnostic imaging*; D000328:Adult; D000369:Aged, 80 and over; D000465:Algorithms; D016000:Cluster Analysis; D003238:Connective Tissue / Q000000981:diagnostic imaging*; D017143:Fuzzy Logic; D006801:Humans; D021621:Imaging, Three-Dimensional / Q000379:methods*; D008279:Magnetic Resonance Imaging / Q000379:methods*; D064847:Multimodal Imaging / Q000379:methods*; D018482:Muscle, Skeletal / Q000000981:diagnostic imaging*
keywords: fuzzy cluster mean segmentation; intramuscular adipose tissue; intramuscular connective tissue; structure tensor maps; ultrashort TE