{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,1,20]],"date-time":"2026-01-20T04:58:29Z","timestamp":1768885109101,"version":"3.49.0"},"reference-count":67,"publisher":"Elsevier BV","license":[{"start":{"date-parts":[[2025,1,1]],"date-time":"2025-01-01T00:00:00Z","timestamp":1735689600000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.elsevier.com\/tdm\/userlicense\/1.0\/"},{"start":{"date-parts":[[2025,1,1]],"date-time":"2025-01-01T00:00:00Z","timestamp":1735689600000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.elsevier.com\/legal\/tdmrep-license"},{"start":{"date-parts":[[2025,1,1]],"date-time":"2025-01-01T00:00:00Z","timestamp":1735689600000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-017"},{"start":{"date-parts":[[2025,1,1]],"date-time":"2025-01-01T00:00:00Z","timestamp":1735689600000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-037"},{"start":{"date-parts":[[2025,1,1]],"date-time":"2025-01-01T00:00:00Z","timestamp":1735689600000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-012"},{"start":{"date-parts":[[2025,1,1]],"date-time":"2025-01-01T00:00:00Z","timestamp":1735689600000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2025,1,1]],"date-time":"2025-01-01T00:00:00Z","timestamp":1735689600000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-004"}],"content-domain":{"domain":["elsevier.com","sciencedirect.com"],"crossmark-restriction":true},"short-container-title":["Image and Vision Computing"],"published-print":{"date-parts":[[2025,1]]},"DOI":"10.1016\/j.imavis.2024.105333","type":"journal-article","created":{"date-parts":[[2024,11,19]],"date-time":"2024-11-19T13:23:05Z","timestamp":1732022585000},"page":"105333","update-policy":"https:\/\/doi.org\/10.1016\/elsevier_cm_policy","source":"Crossref","is-referenced-by-count":5,"special_numbering":"C","title":["Detection of fractional difference in inter vertebral disk MRI images for recognition of low back pain"],"prefix":"10.1016","volume":"153","author":[{"given":"Manvendra","family":"Singh","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-9716-7012","authenticated-orcid":false,"given":"Md. Sarfaraj Alam","family":"Ansari","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Mahesh Chandra","family":"Govil","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"78","reference":[{"key":"10.1016\/j.imavis.2024.105333_b1","series-title":"Computer Science on-Line Conference","first-page":"449","article-title":"Assessment and rehabilitation of low back pain (LBP) using artificial intelligence and machine learning\u2013a review","author":"Singh","year":"2022"},{"key":"10.1016\/j.imavis.2024.105333_b2","doi-asserted-by":"crossref","first-page":"264","DOI":"10.1016\/j.wneu.2021.09.066","article-title":"Fundamentals of intervertebral disc degeneration","volume":"157","author":"Kirnaz","year":"2022","journal-title":"World Neurosurg."},{"issue":"1","key":"10.1016\/j.imavis.2024.105333_b3","doi-asserted-by":"crossref","first-page":"17","DOI":"10.1016\/j.joca.2020.09.002","article-title":"The role of structure and function changes of sensory nervous system in intervertebral disc-related low back pain","volume":"29","author":"Zhang","year":"2021","journal-title":"Osteoarthr. Cartil."},{"key":"10.1016\/j.imavis.2024.105333_b4","series-title":"2023 14th International Conference on Computing Communication and Networking Technologies","first-page":"1","article-title":"DeepPose: An integrated deep learning model for posture detection using image and skeletal data","author":"Singh","year":"2023"},{"issue":"1","key":"10.1016\/j.imavis.2024.105333_b5","doi-asserted-by":"crossref","first-page":"277","DOI":"10.1016\/j.asjsur.2021.05.015","article-title":"Predictors of the conservative management outcomes in patients with lumbar herniated nucleus pulposus: A prospective study in Indonesia","volume":"45","author":"Azharuddin","year":"2022","journal-title":"Asian J. Surg."},{"key":"10.1016\/j.imavis.2024.105333_b6","series-title":"International Conference on Communication, Devices and Computing","first-page":"263","article-title":"Deep learning approach to recognize yoga posture for the ailment of the low back pain","author":"Uday Kiran","year":"2023"},{"key":"10.1016\/j.imavis.2024.105333_b7","first-page":"753","article-title":"A sequential geometry reconstruction based deep learning approach to improve accuracy and consistence of lumbar spine MRI image segmentation","volume":"vol. 12926","author":"Qian","year":"2024"},{"key":"10.1016\/j.imavis.2024.105333_b8","series-title":"2024 International Conference on Advances in Computing, Communication and Applied Informatics","first-page":"1","article-title":"Diagnosis of central canal spinal stenosis from lumbar mid-sagittal mr images","author":"Beulah","year":"2024"},{"key":"10.1016\/j.imavis.2024.105333_b9","doi-asserted-by":"crossref","DOI":"10.1016\/j.bea.2021.100014","article-title":"Magnetic resonance elastography: A non-invasive biomarker for low back pain studies","volume":"2","author":"Tavakoli","year":"2021","journal-title":"Biomed. Eng. Adv."},{"issue":"1","key":"10.1016\/j.imavis.2024.105333_b10","doi-asserted-by":"crossref","first-page":"841","DOI":"10.1038\/s41467-022-28387-5","article-title":"Deep learning-based high-accuracy quantitation for lumbar intervertebral disc degeneration from MRI","volume":"13","author":"Zheng","year":"2022","journal-title":"Nature Commun."},{"issue":"1","key":"10.1016\/j.imavis.2024.105333_b11","doi-asserted-by":"crossref","DOI":"10.1002\/jsp2.1230","article-title":"An update on animal models of intervertebral disc degeneration and low back pain: Exploring the potential of artificial intelligence to improve research analysis and development of prospective therapeutics","volume":"6","author":"Alini","year":"2023","journal-title":"JOR Spine"},{"key":"10.1016\/j.imavis.2024.105333_b12","doi-asserted-by":"crossref","first-page":"32315","DOI":"10.1109\/ACCESS.2022.3158682","article-title":"Deep learning-based disk herniation computer aided diagnosis system from mri axial scans","volume":"10","author":"Alsmirat","year":"2022","journal-title":"IEEE Access"},{"key":"10.1016\/j.imavis.2024.105333_b13","doi-asserted-by":"crossref","DOI":"10.1016\/j.cmpb.2021.106265","article-title":"Computer auxiliary diagnosis technique of detecting cholangiocarcinoma based on medical imaging: A review","volume":"208","author":"Wang","year":"2021","journal-title":"Comput. Methods Programs Biomed."},{"issue":"10","key":"10.1016\/j.imavis.2024.105333_b14","doi-asserted-by":"crossref","first-page":"14471","DOI":"10.1007\/s11042-022-13841-9","article-title":"Recent developments on computer aided systems for diagnosis of diabetic retinopathy: a review","volume":"82","author":"Dubey","year":"2023","journal-title":"Multimedia Tools Appl."},{"issue":"8","key":"10.1016\/j.imavis.2024.105333_b15","doi-asserted-by":"crossref","first-page":"982","DOI":"10.3390\/electronics10080982","article-title":"Herniated lumbar disc generation and classification using cycle generative adversarial networks on axial view MRI","volume":"10","author":"Mbarki","year":"2021","journal-title":"Electronics"},{"key":"10.1016\/j.imavis.2024.105333_b16","doi-asserted-by":"crossref","DOI":"10.1016\/j.inat.2020.100837","article-title":"Lumbar spine discs classification based on deep convolutional neural networks using axial view MRI","volume":"22","author":"Mbarki","year":"2020","journal-title":"Interdiscip. Neurosurg."},{"key":"10.1016\/j.imavis.2024.105333_b17","doi-asserted-by":"crossref","DOI":"10.1016\/j.bspc.2023.105291","article-title":"Automatic localization and classification of intervertebral disc herniation using hybrid classifier","volume":"86","author":"Valarmathi","year":"2023","journal-title":"Biomed. Signal Process. Control"},{"issue":"4","key":"10.1016\/j.imavis.2024.105333_b18","doi-asserted-by":"crossref","first-page":"543","DOI":"10.1016\/j.media.2009.05.004","article-title":"Statistical shape models for 3D medical image segmentation: a review","volume":"13","author":"Heimann","year":"2009","journal-title":"Med. Image Anal."},{"key":"10.1016\/j.imavis.2024.105333_b19","doi-asserted-by":"crossref","first-page":"165","DOI":"10.1016\/j.cmpb.2016.12.008","article-title":"Automatic segmentation of supraspinatus from MRI by internal shape fitting and autocorrection","volume":"140","author":"Kim","year":"2017","journal-title":"Comput. Methods Programs Biomed."},{"key":"10.1016\/j.imavis.2024.105333_b20","series-title":"2005 IEEE Engineering in Medicine and Biology 27th Annual Conference","first-page":"2527","article-title":"Automated vertebra detection and segmentation from the whole spine MR images","author":"Peng","year":"2006"},{"issue":"1","key":"10.1016\/j.imavis.2024.105333_b21","first-page":"1","article-title":"Labeling of lumbar discs using both pixel-and object-level features with a two-level probabilistic model","volume":"30","author":"Raja\u2019S","year":"2010","journal-title":"IEEE Trans. Med. Imaging"},{"issue":"10","key":"10.1016\/j.imavis.2024.105333_b22","doi-asserted-by":"crossref","first-page":"1595","DOI":"10.1109\/TMI.2009.2023362","article-title":"Learning-based vertebra detection and iterative normalized-cut segmentation for spinal MRI","volume":"28","author":"Huang","year":"2009","journal-title":"IEEE Trans. Med. Imaging"},{"key":"10.1016\/j.imavis.2024.105333_b23","series-title":"Medical Image Computing and Computer-Assisted Intervention\u2013MICCAI 2012: 15th International Conference, Nice, France, October 1-5, 2012, Proceedings, Part III 15","first-page":"590","article-title":"Automatic localization and identification of vertebrae in arbitrary field-of-view CT scans","author":"Glocker","year":"2012"},{"issue":"9","key":"10.1016\/j.imavis.2024.105333_b24","doi-asserted-by":"crossref","first-page":"2375","DOI":"10.1109\/TBME.2013.2256460","article-title":"Simultaneous localization of lumbar vertebrae and intervertebral discs with SVM-based MRF","volume":"60","author":"Oktay","year":"2013","journal-title":"IEEE Trans. Biomed. Eng."},{"issue":"8","key":"10.1016\/j.imavis.2024.105333_b25","doi-asserted-by":"crossref","first-page":"1676","DOI":"10.1109\/TMI.2015.2392054","article-title":"Multi-modality vertebra recognition in arbitrary views using 3D deformable hierarchical model","volume":"34","author":"Cai","year":"2015","journal-title":"IEEE Trans. Med. Imaging"},{"key":"10.1016\/j.imavis.2024.105333_b26","first-page":"269","article-title":"Deep learning for automatic localization, identification, and segmentation of vertebral bodies in volumetric MR images","volume":"vol. 9415","author":"Suzani","year":"2015"},{"key":"10.1016\/j.imavis.2024.105333_b27","doi-asserted-by":"crossref","DOI":"10.12785\/ijcds\/1001117","article-title":"Ensemble machine learning for P2P traffic identification","author":"Ansari","year":"2021","journal-title":"Int. J. Comput. Digit. Syst."},{"key":"10.1016\/j.imavis.2024.105333_b28","doi-asserted-by":"crossref","DOI":"10.1016\/j.cose.2023.103438","article-title":"Nature-inspired intrusion detection system for protecting software-defined networks controller","volume":"134","author":"Kumar","year":"2023","journal-title":"Comput. Secur."},{"issue":"24","key":"10.1016\/j.imavis.2024.105333_b29","doi-asserted-by":"crossref","first-page":"8357","DOI":"10.1088\/0031-9155\/57\/24\/8357","article-title":"Automated detection, 3D segmentation and analysis of high resolution spine MR images using statistical shape models","volume":"57","author":"Neubert","year":"2012","journal-title":"Phys. Med. Biol."},{"key":"10.1016\/j.imavis.2024.105333_b30","doi-asserted-by":"crossref","first-page":"327","DOI":"10.1016\/j.media.2016.08.005","article-title":"Evaluation and comparison of 3D intervertebral disc localization and segmentation methods for 3D T2 MR data: A grand challenge","volume":"35","author":"Zheng","year":"2017","journal-title":"Med. Image Anal."},{"issue":"1","key":"10.1016\/j.imavis.2024.105333_b31","doi-asserted-by":"crossref","first-page":"18","DOI":"10.3390\/s18010018","article-title":"Comparison of random forest, k-nearest neighbor, and support vector machine classifiers for land cover classification using sentinel-2 imagery","volume":"18","author":"Thanh Noi","year":"2017","journal-title":"Sensors"},{"key":"10.1016\/j.imavis.2024.105333_b32","doi-asserted-by":"crossref","DOI":"10.1016\/j.ijmedinf.2023.105151","article-title":"Prediction of prognosis in COVID-19 patients using machine learning: a systematic review and meta-analysis","author":"Chen","year":"2023","journal-title":"Int. J. Med. Inform."},{"key":"10.1016\/j.imavis.2024.105333_b33","doi-asserted-by":"crossref","DOI":"10.1016\/j.inat.2020.100837","article-title":"Lumbar spine discs classification based on deep convolutional neural networks using axial view MRI","volume":"22","author":"Mbarki","year":"2020","journal-title":"Interdiscip. Neurosurg."},{"key":"10.1016\/j.imavis.2024.105333_b34","first-page":"177","article-title":"Examination of retinal anatomical structures\u2014A study with spider monkey optimization algorithm","author":"Rajinikanth","year":"2020","journal-title":"Appl. Nature-Inspired Comput.: Algorithms Case Stud."},{"issue":"2","key":"10.1016\/j.imavis.2024.105333_b35","first-page":"3","article-title":"Lumbosacral angle variations in middle aged patients with chronic low back pain-a retrospective study","volume":"1","author":"Mukherjee","year":"2021","journal-title":"Pain"},{"key":"10.1016\/j.imavis.2024.105333_b36","doi-asserted-by":"crossref","first-page":"301","DOI":"10.1016\/j.cogsys.2018.07.022","article-title":"A bare bones bacterial foraging optimization algorithm","volume":"52","author":"Wang","year":"2018","journal-title":"Cogn. Syst. Res."},{"key":"10.1016\/j.imavis.2024.105333_b37","doi-asserted-by":"crossref","DOI":"10.1155\/2016\/3267307","article-title":"Interspinous process decompression: expanding treatment options for lumbar spinal stenosis","volume":"2016","author":"Nunley","year":"2016","journal-title":"BioMed. Res. Int."},{"key":"10.1016\/j.imavis.2024.105333_b38","series-title":"Medical Image Computing and Computer-Assisted Intervention\u2013MICCAI 2011: 14th International Conference, Toronto, Canada, September 18-22, 2011, Proceedings, Part III 14","first-page":"158","article-title":"Localization of the lumbar discs using machine learning and exact probabilistic inference","author":"Oktay","year":"2011"},{"issue":"4","key":"10.1016\/j.imavis.2024.105333_b39","doi-asserted-by":"crossref","first-page":"421","DOI":"10.1515\/bmt-2018-0013","article-title":"Non-invasive improved technique for lumbar discus hernia classification based on fuzzy logic","volume":"64","author":"Peuli\u0107","year":"2019","journal-title":"Biomed. Eng.\/Biomed. Tech."},{"key":"10.1016\/j.imavis.2024.105333_b40","doi-asserted-by":"crossref","DOI":"10.1016\/j.media.2023.102841","article-title":"Bolt: Fused window transformers for fMRI time series analysis","volume":"88","author":"Bedel","year":"2023","journal-title":"Med. Image Anal."},{"issue":"6","key":"10.1016\/j.imavis.2024.105333_b41","doi-asserted-by":"crossref","first-page":"8507","DOI":"10.1007\/s11042-022-13556-x","article-title":"A statistical analysis of SAMPARK dataset for peer-to-peer traffic and selfish-peer identification","volume":"82","author":"Ansari","year":"2023","journal-title":"Multimedia Tools Appl."},{"key":"10.1016\/j.imavis.2024.105333_b42","series-title":"International Conference on Advanced Computational and Communication Paradigms","first-page":"99","article-title":"NITSDN: Development of SDN dataset for ML-based intrusion detection system","author":"Khanal","year":"2023"},{"key":"10.1016\/j.imavis.2024.105333_b43","doi-asserted-by":"crossref","DOI":"10.1016\/j.bspc.2023.105311","article-title":"Segmentation and classification of intervertebral disc using capsule stacked autoencoder","volume":"86","author":"Adibatti","year":"2023","journal-title":"Biomed. Signal Process. Control"},{"issue":"3","key":"10.1016\/j.imavis.2024.105333_b44","doi-asserted-by":"crossref","DOI":"10.1016\/j.ocarto.2023.100378","article-title":"Automated segmentation and prediction of intervertebral disc morphology and uniaxial deformations from MRI","volume":"5","author":"Coppock","year":"2023","journal-title":"Osteoarthr. Cartil. Open"},{"issue":"7","key":"10.1016\/j.imavis.2024.105333_b45","article-title":"Lumbar intervertebral disc detection and classification with novel deep learning models","volume":"36","author":"Nisar","year":"2024","journal-title":"J. King Saud Univ.-Comput. Inf. Sci."},{"issue":"4","key":"10.1016\/j.imavis.2024.105333_b46","article-title":"Quantifying dysfunction of the lumbar multifidus muscle after radiofrequency neurotomy and fusion surgery: a preliminary study","volume":"3","author":"Sadeghi","year":"2020","journal-title":"J. Eng. Sci. Med. Diagn. Ther."},{"key":"10.1016\/j.imavis.2024.105333_b47","doi-asserted-by":"crossref","DOI":"10.1155\/2022\/7459260","article-title":"Diagnosis of lumbar spondylolisthesis using optimized pretrained CNN models","volume":"2022","author":"Saravagi","year":"2022","journal-title":"Comput. Intell. Neurosci."},{"issue":"5","key":"10.1016\/j.imavis.2024.105333_b48","doi-asserted-by":"crossref","first-page":"3435","DOI":"10.1007\/s00330-023-09483-6","article-title":"Deep learning for automated, interpretable classification of lumbar spinal stenosis and facet arthropathy from axial MRI","volume":"33","author":"Bharadwaj","year":"2023","journal-title":"Eur. Radiol."},{"key":"10.1016\/j.imavis.2024.105333_b49","series-title":"Biennial International Conference on Information Processing in Medical Imaging","first-page":"221","article-title":"Graph cuts with invariant object-interaction priors: application to intervertebral disc segmentation","author":"Ben Ayed","year":"2011"},{"issue":"1","key":"10.1016\/j.imavis.2024.105333_b50","first-page":"1","article-title":"A machine learning-based method in order to diagnose lumbar disc herniation disease by MR image processing","volume":"1","author":"Ebrahimzadeh","year":"2018","journal-title":"MedLife Open Access"},{"key":"10.1016\/j.imavis.2024.105333_b51","series-title":"2009 IEEE International Symposium on Biomedical Imaging: From Nano To Macro","first-page":"546","article-title":"Desiccation diagnosis in lumbar discs from clinical MRI with a probabilistic model","author":"Raja\u2019S","year":"2009"},{"key":"10.1016\/j.imavis.2024.105333_b52","series-title":"2011 International Symposium on Innovations in Intelligent Systems and Applications","first-page":"490","article-title":"A comparison of feature extraction techniques for diagnosis of lumbar intervertebral degenerative disc disease","author":"Unal","year":"2011"},{"issue":"6","key":"10.1016\/j.imavis.2024.105333_b53","doi-asserted-by":"crossref","first-page":"1082","DOI":"10.1136\/amiajnl-2012-001547","article-title":"Three-dimensional morphological and signal intensity features for detection of intervertebral disc degeneration from magnetic resonance images","volume":"20","author":"Neubert","year":"2013","journal-title":"J. Am. Med. Inform. Assoc."},{"issue":"7","key":"10.1016\/j.imavis.2024.105333_b54","doi-asserted-by":"crossref","first-page":"613","DOI":"10.1016\/j.compmedimag.2014.04.006","article-title":"Computer aided diagnosis of degenerative intervertebral disc diseases from lumbar MR images","volume":"38","author":"Oktay","year":"2014","journal-title":"Comput. Med. Imaging Graph."},{"key":"10.1016\/j.imavis.2024.105333_b55","series-title":"5th ISSNIP-IEEE Biosignals and Biorobotics Conference (2014): Biosignals and Robotics for Better and Safer Living","first-page":"1","article-title":"Semiautomatic classification of intervertebral disc degeneration in magnetic resonance images of the spine","author":"da Silva Barreiro","year":"2014"},{"key":"10.1016\/j.imavis.2024.105333_b56","unstructured":"Y. Unal, H. Kocer, H. Akkurt, Automatic diagnosis of intervertebral degenerative disk disease using artificial neural network, in: 6th International Advanced Technologies Symposium, IATS\u201911, 2011, pp. 16\u201318."},{"key":"10.1016\/j.imavis.2024.105333_b57","doi-asserted-by":"crossref","first-page":"2721","DOI":"10.1007\/s00586-016-4654-6","article-title":"Intervertebral disc classification by its degree of degeneration from T2-weighted magnetic resonance images","volume":"25","author":"Castro-Mateos","year":"2016","journal-title":"Eur. Spine J."},{"key":"10.1016\/j.imavis.2024.105333_b58","doi-asserted-by":"crossref","first-page":"244","DOI":"10.1016\/j.isatra.2018.07.006","article-title":"Automatic detection system for degenerative disk and simulation for artificial disc replacement surgery in the spine","volume":"81","author":"Mahdy","year":"2018","journal-title":"ISA Trans."},{"key":"10.1016\/j.imavis.2024.105333_b59","first-page":"1","article-title":"Automated detection of microfilariae parasite in blood smear using OCR-NURBS image segmentation","author":"Kumar","year":"2024","journal-title":"Multimedia Tools Appl."},{"key":"10.1016\/j.imavis.2024.105333_b60","doi-asserted-by":"crossref","DOI":"10.1109\/ACCESS.2024.3386826","article-title":"A comprehensive systematic review of YOLO for medical object detection (2018 to 2023)","author":"Ragab","year":"2024","journal-title":"IEEE Access"},{"key":"10.1016\/j.imavis.2024.105333_b61","article-title":"Analysis of subfeature for classification in data mining","author":"Bhuyan","year":"2021","journal-title":"IEEE Trans. Eng. Manage."},{"key":"10.1016\/j.imavis.2024.105333_b62","doi-asserted-by":"crossref","DOI":"10.1016\/j.asoc.2019.105524","article-title":"Investigating the impact of data normalization on classification performance","volume":"97","author":"Singh","year":"2020","journal-title":"Appl. Soft Comput."},{"issue":"3","key":"10.1016\/j.imavis.2024.105333_b63","doi-asserted-by":"crossref","first-page":"1464","DOI":"10.1109\/23.589532","article-title":"Importance of input data normalization for the application of neural networks to complex industrial problems","volume":"44","author":"Sola","year":"1997","journal-title":"IEEE Trans. Nucl. Sci."},{"issue":"1","key":"10.1016\/j.imavis.2024.105333_b64","doi-asserted-by":"crossref","first-page":"183","DOI":"10.1016\/j.aej.2020.06.054","article-title":"AN OTSU image segmentation based on fruitfly optimization algorithm","volume":"60","author":"Huang","year":"2021","journal-title":"Alex. Eng. J."},{"key":"10.1016\/j.imavis.2024.105333_b65","series-title":"2023 14th International Conference on Computing Communication and Networking Technologies","first-page":"1","article-title":"Automated diagnosis of lymphatic filariasis: A robust approach for microfilariae detection using image processing and stacking classifier","author":"Kumar","year":"2023"},{"issue":"2","key":"10.1016\/j.imavis.2024.105333_b66","first-page":"899","article-title":"A new image thresholding method based on Gaussian mixture model","volume":"205","author":"Huang","year":"2008","journal-title":"Appl. Math. Comput."},{"key":"10.1016\/j.imavis.2024.105333_b67","doi-asserted-by":"crossref","DOI":"10.1016\/j.bspc.2021.103225","article-title":"Noise estimation in 2D MRI using DWT coefficients and optimized neural network","volume":"71","author":"Shukla","year":"2022","journal-title":"Biomed. Signal Process. Control"}],"container-title":["Image and Vision Computing"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/api.elsevier.com\/content\/article\/PII:S0262885624004384?httpAccept=text\/xml","content-type":"text\/xml","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/api.elsevier.com\/content\/article\/PII:S0262885624004384?httpAccept=text\/plain","content-type":"text\/plain","content-version":"vor","intended-application":"text-mining"}],"deposited":{"date-parts":[[2024,12,9]],"date-time":"2024-12-09T19:14:41Z","timestamp":1733771681000},"score":1,"resource":{"primary":{"URL":"https:\/\/linkinghub.elsevier.com\/retrieve\/pii\/S0262885624004384"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025,1]]},"references-count":67,"alternative-id":["S0262885624004384"],"URL":"https:\/\/doi.org\/10.1016\/j.imavis.2024.105333","relation":{},"ISSN":["0262-8856"],"issn-type":[{"value":"0262-8856","type":"print"}],"subject":[],"published":{"date-parts":[[2025,1]]},"assertion":[{"value":"Elsevier","name":"publisher","label":"This article is maintained by"},{"value":"Detection of fractional difference in inter vertebral disk MRI images for recognition of low back pain","name":"articletitle","label":"Article Title"},{"value":"Image and Vision Computing","name":"journaltitle","label":"Journal Title"},{"value":"https:\/\/doi.org\/10.1016\/j.imavis.2024.105333","name":"articlelink","label":"CrossRef DOI link to publisher maintained version"},{"value":"article","name":"content_type","label":"Content Type"},{"value":"\u00a9 2024 Elsevier B.V. All rights are reserved, including those for text and data mining, AI training, and similar technologies.","name":"copyright","label":"Copyright"}],"article-number":"105333"}}