{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,9,24]],"date-time":"2026-09-24T21:31:09Z","timestamp":1790285469824,"version":"4.1.0"},"reference-count":51,"publisher":"Public Library of Science (PLoS)","issue":"5","license":[{"start":{"date-parts":[[2019,5,9]],"date-time":"2019-05-09T00:00:00Z","timestamp":1557360000000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/100007028","name":"Leona M. and Harry B. Helmsley Charitable Trust","doi-asserted-by":"publisher","id":[{"id":"10.13039\/100007028","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["www.plosone.org"],"crossmark-restriction":false},"short-container-title":["PLoS ONE"],"DOI":"10.1371\/journal.pone.0216487","type":"journal-article","created":{"date-parts":[[2019,5,9]],"date-time":"2019-05-09T17:40:15Z","timestamp":1557423615000},"page":"e0216487","update-policy":"https:\/\/doi.org\/10.1371\/journal.pone.corrections_policy","source":"Crossref","is-referenced-by-count":18,"title":["Novel stochastic framework for automatic segmentation of human thigh MRI volumes and its applications in spinal cord injured individuals"],"prefix":"10.1371","volume":"14","author":[{"given":"Samineh","family":"Mesbah","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Ahmed M.","family":"Shalaby","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Sean","family":"Stills","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Ahmed M.","family":"Soliman","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Andrea","family":"Willhite","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Susan J.","family":"Harkema","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Enrico","family":"Rejc","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-7264-1323","authenticated-orcid":true,"given":"Ayman S.","family":"El-Baz","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"340","published-online":{"date-parts":[[2019,5,9]]},"reference":[{"key":"ref1","first-page":"2018","article-title":"SCI Facts and Figures at a Glance"},{"issue":"260","key":"ref2","doi-asserted-by":"crossref","first-page":"287","DOI":"10.1097\/00003086-199011000-00045","article-title":"Long-term morphology of spastic or flaccid muscles in spinal cord-transected rabbits","author":"Y Hiraizumi","year":"1990","journal-title":"Clin Orthop Relat Res"},{"issue":"10","key":"ref3","doi-asserted-by":"crossref","first-page":"1561","DOI":"10.1002\/1097-4598(200010)23:10<1561::AID-MUS13>3.0.CO;2-X","article-title":"Metabolism of rat skeletal muscle after spinal cord transection","volume":"23","author":"D Durozard","year":"2000","journal-title":"Muscle Nerve"},{"issue":"8","key":"ref4","doi-asserted-by":"crossref","first-page":"1008","DOI":"10.1089\/0897715041651060","article-title":"Body weight, limb size, and muscular properties of early paraplegic mice","volume":"21","author":"E Landry","year":"2004","journal-title":"J Neurotrauma"},{"issue":"6","key":"ref5","doi-asserted-by":"crossref","first-page":"772","DOI":"10.1016\/j.apmr.2006.02.028","article-title":"Lower-extremity muscle cross-sectional area after incomplete spinal cord injury","volume":"87","author":"PK Shah","year":"2006","journal-title":"Arch Phys Med Rehabil"},{"key":"ref6","doi-asserted-by":"crossref","first-page":"304","DOI":"10.1038\/sj.sc.3101968","article-title":"Skeletal muscle atrophy and increased intramuscular fat after incomplete spinal cord injury","volume":"45","author":"A Gorgey","year":"2007","journal-title":"Spinal Cord"},{"issue":"10","key":"ref7","doi-asserted-by":"crossref","first-page":"2027","DOI":"10.1016\/j.apmr.2013.04.016","article-title":"Systematic Framework to Classify the Status of Research on Spinal Cord Injury and Physical Activity","volume":"94","author":"M Nery","year":"2013","journal-title":"Archives of Physical Medicine and Rehabilitation"},{"issue":"6","key":"ref8","doi-asserted-by":"crossref","first-page":"2195","DOI":"10.1152\/jn.1995.73.6.2195","article-title":"Fatigability, relaxation properties, and electromyographic responses of the human paralyzed soleus muscle","volume":"73","author":"RK Shields","year":"1995","journal-title":"J Neurophysiol"},{"issue":"2","key":"ref9","doi-asserted-by":"crossref","first-page":"65","DOI":"10.2519\/jospt.2002.32.2.65","article-title":"Muscular, skeletal, and neural adaptations following spinal cord injury","volume":"32","author":"RK Shields","year":"2002","journal-title":"J Orthop Sports Phys Ther"},{"issue":"1","key":"ref10","doi-asserted-by":"crossref","first-page":"23","DOI":"10.1179\/2045772314Y.0000000244","article-title":"The effects of electrical stimulation on body composition and metabolic profile after spinal cord injury\u2013Part II","volume":"38","author":"AS Gorgey","year":"2015","journal-title":"The Journal of Spinal Cord Medicine"},{"key":"ref11","doi-asserted-by":"crossref","first-page":"977","DOI":"10.1016\/j.jelekin.2013.04.007","article-title":"Neuromuscular electrical stimulation attenuates thigh skeletal muscles atrophy but not trunk muscles after spinal cord injury","author":"AS Gorgey","year":"2013","journal-title":"Journal of Electromyography and Kinesiology"},{"issue":"2","key":"ref12","doi-asserted-by":"crossref","first-page":"89","DOI":"10.1007\/s10334-016-0549-0","article-title":"Tissue segmentation: a crucial tool for quantitative MRI and visualization of anatomical structures","volume":"29","author":"F Schick","year":"2016","journal-title":"Magn Reson Mater Phys Biol Med"},{"issue":"2","key":"ref13","doi-asserted-by":"crossref","first-page":"96","DOI":"10.1038\/sj.sc.3102087","article-title":"Spasticity may defend skeletal muscle size and composition after incomplete spinal cord injury","volume":"46","author":"AS Gorgey","year":"2008","journal-title":"Spinal Cord"},{"key":"ref14","unstructured":"Barra V, Morio B, Colin A, Vermorel M, Boire J, editors. Automatic assessment of muscle\/fat temporal variations on MR images of the thigh. Proceedings of 18th Annual International Conference of the IEEE Engineering in Medicine and Biology Society; 1996; Amsterdam."},{"issue":"3","key":"ref15","doi-asserted-by":"crossref","first-page":"185","DOI":"10.1016\/S0169-2607(01)00172-9","article-title":"egmentation of fat and muscle from MR images of the thigh by a possibilistic clustering algorithm","volume":"68","author":"V Barra","year":"2002","journal-title":"Computer Methods and Programs in Biomedicine"},{"issue":"29","key":"ref16","doi-asserted-by":"crossref","first-page":"677","DOI":"10.1002\/jmri.21699","article-title":"Accurate Segmentation of Subcutaneous and Intermuscular Adipose Tissue From MR Images of the Thigh","author":"V Positano","year":"2009","journal-title":"JOURNAL OF MAGNETIC RESONANCE IMAGING"},{"issue":"10","key":"ref17","first-page":"314","article-title":"Automatic segmentation of thigh magnetic resonance images","volume":"3","author":"L Urricelqui","year":"2009","journal-title":"International Journal of Medical, Health, Biomedical, Bioengineering and Pharmaceutical Engineering"},{"key":"ref18","article-title":"A Novel Extension to Fuzzy Connectivity for Body Composition Analysis: Applications in Thigh, Brain, and Whole Body Tissue Segmentation","author":"I Irmakci","year":"2018","journal-title":"IEEE Trans Biomed Eng"},{"key":"ref19","article-title":"Medical Image Computing and Computer-Assisted Intervention (MICCAI)","author":"P Baudin","year":"2013"},{"issue":"9","key":"ref20","doi-asserted-by":"crossref","first-page":"1773","DOI":"10.1109\/TMI.2015.2403299","article-title":"The Generalized Log-Ratio Transformation: Learning Shape and Adjacency Priors for Simultaneous Thigh Muscle Segmentation","volume":"34","author":"S Andrews","year":"2015","journal-title":"IEEE TRANSACTIONS ON MEDICAL IMAGING"},{"key":"ref21","article-title":"Proceedings of SPIE","author":"E Ahmad","year":"2014"},{"key":"ref22","doi-asserted-by":"crossref","first-page":"245","DOI":"10.1007\/s10334-016-0535-6","article-title":"Volume measurements of individual muscles in human quadriceps femoris using atlas\u2011based segmentation approaches","volume":"29","author":"A Le Troter","year":"2016","journal-title":"J of Magn Reson MAter Phy"},{"issue":"8","key":"ref23","doi-asserted-by":"crossref","DOI":"10.1371\/journal.pone.0183825","article-title":"Long-term follow-up of MRI changes in thigh muscles of patients with Facioscapulohumeral dystrophy: A quantitative study","volume":"12","author":"F Fatehi","year":"2017","journal-title":"PLoS ONE"},{"key":"ref24","doi-asserted-by":"crossref","first-page":"489","DOI":"10.1007\/s10334-017-0622-3","article-title":"Validation of an active shape model\u2011based semi\u2011automated segmentation algorithm for the analysis of thigh muscle and adipose tissue cross\u2011sectional areas","volume":"30","author":"J Kemnitz","year":"2017","journal-title":"Magn Reson Mater Phy"},{"key":"ref25","unstructured":"Hinton GE, Srivastava, N., Krizhevsky, A., Sutskever, I., Salakhutdinov. Improving neural networks by preventing co-adaptation of feature detectors. arXiv. 2012."},{"key":"ref26","doi-asserted-by":"crossref","first-page":"61","DOI":"10.1016\/j.media.2016.10.004","article-title":"Efficient multi-scale 3D CNN with fully connected CRF for accurate brain lesion segmentation","volume":"36","author":"K Kamnitsas","year":"2017","journal-title":"Med Image Anal"},{"issue":"1","key":"ref27","doi-asserted-by":"crossref","first-page":"16485","DOI":"10.1038\/s41598-018-34817-6","article-title":"Segmentation of the Proximal Femur from MR Images using Deep Convolutional Neural Networks","volume":"8","author":"CM Deniz","year":"2018","journal-title":"Scientific Reports"},{"issue":"4","key":"ref28","doi-asserted-by":"crossref","first-page":"2379","DOI":"10.1002\/mrm.26841","article-title":"Deep convolutional neural network and 3D deformable approach for tissue segmentation in musculoskeletal magnetic resonance imaging","volume":"79","author":"F Liu","year":"2018","journal-title":"Magn Reson Med"},{"issue":"1","key":"ref29","doi-asserted-by":"crossref","first-page":"177","DOI":"10.1148\/radiol.2018172322","article-title":"Use of 2D U-Net Convolutional Neural Networks for Automated Cartilage and Meniscus Segmentation of Knee MR Imaging Data to Determine Relaxometry and Morphometry","volume":"288","author":"B Norman","year":"2018","journal-title":"Radiology"},{"key":"ref30","article-title":"Medical Image Computing and Computer-Assisted Interven- tion\u2013MICCAI","author":"A Prasoon","year":"2013"},{"key":"ref31","article-title":"Medical Image Computing and Computer-Assisted Intervention\u2013MICCAI","author":"HR Roth","year":"2014"},{"key":"ref32","article-title":"Medical Image Computing and Computer-Assisted Intervention\u2013MICCAI","author":"R Li","year":"2014"},{"issue":"4","key":"ref33","doi-asserted-by":"crossref","first-page":"346","DOI":"10.1080\/10790268.2010.11689712","article-title":"_ 2009 review and revisions of the international standards for the neurological classification of spinal cord injury","volume":"33","author":"WP Waring 3rd","year":"2010","journal-title":"J Spinal Cord Med"},{"issue":"4","key":"ref34","doi-asserted-by":"crossref","first-page":"952","DOI":"10.1109\/TIP.2005.863949","article-title":"Precise segmentation of multi-modal images","volume":"15","author":"A Farag","year":"2006","journal-title":"IEEE Trans Image Process"},{"key":"ref35","doi-asserted-by":"crossref","first-page":"219","DOI":"10.1146\/annurev-bioeng-071910-124649","article-title":"Deformable medical image registration: Setting the state of the art with discrete methods","volume":"13","author":"B Glocker","year":"2011","journal-title":"Annual Review of Biomedical Engineering"},{"key":"ref36","article-title":"Stochastic Modeling for Medical Image Analysis","author":"A El-Baz","year":"2016"},{"issue":"2","key":"ref37","doi-asserted-by":"crossref","first-page":"445","DOI":"10.1109\/TBME.2011.2174235","article-title":"Accurate automatic analysis of cardiac cine images","volume":"59","author":"F Khalifa","year":"2012","journal-title":"IEEE Trans Biomed Eng"},{"issue":"3","key":"ref38","doi-asserted-by":"crossref","first-page":"297","DOI":"10.2307\/1932409","article-title":"Measures of the Amount of Ecologic Association Between Species","volume":"26","author":"LR Dice","year":"1945","journal-title":"Ecology"},{"key":"ref39","doi-asserted-by":"crossref","unstructured":"Huttenlocher DP, Rucklidge WJ, editors. A multi-resolution technique for comparing images using the Hausdorff distance. Proceedings of IEEE Conference on Computer Vision and Pattern Recognition; 1993 15\u201317 Jun 1993.","DOI":"10.1109\/34.232073"},{"issue":"3","key":"ref40","doi-asserted-by":"crossref","first-page":"2033","DOI":"10.1016\/j.neuroimage.2010.09.025","article-title":"A reproducible evaluation of ANTs similarity metric performance in brain image registration","volume":"54","author":"BB Avants","year":"2011","journal-title":"Neuroimage"},{"issue":"10","key":"ref41","doi-asserted-by":"crossref","first-page":"1840","DOI":"10.1109\/TMI.2013.2266258","article-title":"Simultaneous truth and performance level estimation through fusion of probabilistic segmentations","volume":"32","author":"A Akhondi-Asl","year":"2013","journal-title":"IEEE Trans Med Imaging"},{"issue":"7","key":"ref42","doi-asserted-by":"crossref","first-page":"903","DOI":"10.1109\/TMI.2004.828354","article-title":"Simultaneous truth and performance level estimation (STAPLE): an algorithm for the validation of image segmentation","volume":"23","author":"SK Warfield","year":"2004","journal-title":"IEEE Transactions on Medical Imaging"},{"issue":"12","key":"ref43","doi-asserted-by":"crossref","first-page":"2100","DOI":"10.4103\/1673-5374.221170","article-title":"Quantification of intermuscular and intramuscular adipose tissue using magnetic resonance imaging after neurodegenerative disorders","volume":"12","author":"M Ogawa","year":"2017","journal-title":"Neural regeneration research"},{"key":"ref44","doi-asserted-by":"crossref","unstructured":"Imamoglu N, Gomez-Tames J, He S, Gu DY, Kita K, Yu W, editors. Unsupervised muscle region extraction by fuzzy decision based saliency feature integration on thigh MRI for 3D modeling. 2015 14th IAPR International Conference on Machine Vision Applications (MVA); 2015 18\u201322 May 2015.","DOI":"10.1109\/MVA.2015.7153155"},{"key":"ref45","doi-asserted-by":"crossref","unstructured":"Kovacs W, Liu CY, Summers R, Yao J, editors. Identification of muscle and subcutaneous and intermuscular adipose tissue on thigh MRI of muscular dystrophy. 2016 IEEE 13th International Symposium on Biomedical Imaging (ISBI); 2016 13\u201316 April 2016.","DOI":"10.1109\/ISBI.2016.7493238"},{"key":"ref46","article-title":"Prior knowledge, random walks and human skeletal muscle segmentation. MICCAI","author":"PY Baudin","year":"2012"},{"key":"ref47","doi-asserted-by":"crossref","unstructured":"Ogier A, Sdika M, Four\u00e9 A, Le Troter A, Bendahan D, editors. Individual muscle segmentation in MR images: A 3D propagation through 2D non-linear registration approaches. 39th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC); 2017.","DOI":"10.1109\/EMBC.2017.8036826"},{"issue":"2","key":"ref48","first-page":"147","article-title":"Quetelet&apos;s index (W\/H2) as a measure of fatness","volume":"9","author":"JS Garrow","year":"1985","journal-title":"Int J Obes"},{"issue":"5","key":"ref49","doi-asserted-by":"crossref","first-page":"1285","DOI":"10.1109\/TMI.2016.2528162","article-title":"Deep Convolutional Neural Networks for Computer-Aided Detection: CNN Architectures, Dataset Characteristics and Transfer Learning","volume":"35","author":"HC Shin","year":"2016","journal-title":"IEEE Trans Med Imaging"},{"key":"ref50","doi-asserted-by":"crossref","first-page":"711","DOI":"10.1038\/sj.sc.3101652","article-title":"Intramuscular fat and glucose tolerance after spinal cord injury\u2013a cross-sectional study","author":"C Elder","year":"2004","journal-title":"Spinal Cord"},{"key":"ref51","doi-asserted-by":"crossref","first-page":"309570","DOI":"10.1155\/2014\/309570","article-title":"Intermuscular fat: a review of the consequences and causes","volume":"2014","author":"O Addison","year":"2014","journal-title":"International journal of endocrinology"}],"updated-by":[{"DOI":"10.1371\/journal.pone.0219810","type":"correction","label":"Correction","source":"publisher","updated":{"date-parts":[[2019,7,16]],"date-time":"2019-07-16T00:00:00Z","timestamp":1563235200000}}],"container-title":["PLOS ONE"],"original-title":[],"language":"en","link":[{"URL":"http:\/\/dx.plos.org\/10.1371\/journal.pone.0216487","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2022,9,17]],"date-time":"2022-09-17T19:13:34Z","timestamp":1663442014000},"score":1,"resource":{"primary":{"URL":"https:\/\/dx.plos.org\/10.1371\/journal.pone.0216487"}},"subtitle":[],"editor":[{"given":"Dzung","family":"Pham","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"editor"}]}],"short-title":[],"issued":{"date-parts":[[2019,5,9]]},"references-count":51,"journal-issue":{"issue":"5","published-online":{"date-parts":[[2019,5,9]]}},"URL":"https:\/\/doi.org\/10.1371\/journal.pone.0216487","relation":{"correction":[{"id-type":"doi","id":"10.1371\/journal.pone.0219810","asserted-by":"object"}]},"ISSN":["1932-6203"],"issn-type":[{"value":"1932-6203","type":"electronic"}],"subject":[],"published":{"date-parts":[[2019,5,9]]}}}