{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,8,7]],"date-time":"2026-08-07T15:55:29Z","timestamp":1786118129672,"version":"build-2736575974"},"reference-count":27,"publisher":"Wiley","issue":"4","license":[{"start":{"date-parts":[[2026,3,8]],"date-time":"2026-03-08T00:00:00Z","timestamp":1772928000000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/onlinelibrary.wiley.com\/termsAndConditions#vor"},{"start":{"date-parts":[[2026,3,8]],"date-time":"2026-03-08T00:00:00Z","timestamp":1772928000000},"content-version":"tdm","delay-in-days":0,"URL":"http:\/\/doi.wiley.com\/10.1002\/tdm_license_1.1"}],"content-domain":{"domain":["iubmb.onlinelibrary.wiley.com"],"crossmark-restriction":true},"short-container-title":["Biotech and App Biochem"],"published-print":{"date-parts":[[2026,8]]},"abstract":"<jats:title>ABSTRACT<\/jats:title>\n                  <jats:p>\n                    Accurately segmenting spinal structures from magnetic resonance imaging (MRI) is essential for diagnosing degenerative disc diseases. However, 1.5\u00a0T low\u2010field MRI often suffers from high noise and low contrast, complicating the segmentation process. This study provides a systematic comparative evaluation of four thresholding\u2010based techniques: binary\/global, Otsu, adaptive, and standard deviation\u2010based methods. Using a dataset of spinal DICOM images, we analyzed the effectiveness of these algorithms in delineating bone and soft tissue boundaries. The performance was quantitatively validated using the Dice coefficient and statistical analysis via ANOVA. Results indicate that adaptive thresholding and Otsu thresholding outperformed global methods in handling localized intensity variations, achieving a higher similarity index to expert\u2010validated reference masks. Statistical analysis using ANOVA (\n                    <jats:italic>p<\/jats:italic>\n                    \u00a0&gt;\u00a00.05) further suggests that while these traditional methods are computationally efficient, their efficacy is constrained by the signal\u2010to\u2010noise ratio (SNR) in low\u2010field imaging. This research establishes a technical benchmark for traditional segmentation limits, highlighting the specific scenarios where a transition to deep\u2010learning\u2010based models becomes necessary for clinical accuracy.\n                  <\/jats:p>","DOI":"10.1002\/bab.70146","type":"journal-article","created":{"date-parts":[[2026,3,9]],"date-time":"2026-03-09T06:21:14Z","timestamp":1773037274000},"page":"1945-1964","update-policy":"https:\/\/doi.org\/10.1002\/crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["Investigation of the Medical Image Modalities to Detect the Abnormalities in the Spinal Cord Using Thresholding Techniques"],"prefix":"10.1002","volume":"73","author":[{"given":"Manjima","family":"Saha","sequence":"first","affiliation":[{"name":"Department of Computer Application and Sciences, Institute of Engineering and Management University of Engineering &amp; Management  Kolkata India"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Goldina","family":"Ghosh","sequence":"additional","affiliation":[{"name":"Department of Computer Application and Sciences, Institute of Engineering and Management University of Engineering &amp; Management  Kolkata India"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"311","published-online":{"date-parts":[[2026,3,8]]},"reference":[{"key":"e_1_2_9_2_1","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-319-47223-2_1"},{"key":"e_1_2_9_3_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.inffus.2022.11.008"},{"key":"e_1_2_9_4_1","doi-asserted-by":"publisher","DOI":"10.1007\/s12010\u2010022\u201004012\u20105"},{"key":"e_1_2_9_5_1","doi-asserted-by":"publisher","DOI":"10.1007\/s12010\u2010022\u201004139\u20105"},{"issue":"1","key":"e_1_2_9_6_1","first-page":"2319","article-title":"Study of Image Segmentation Using Thresholding Technique on a Noisy Image","volume":"2","author":"Abubakar F. 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A.Sid\u2010Ahmed \u201cCapsule Image Segmentation in Pharmaceutical Applications Using Edge\u2010Based Techniques \u201d in2011 IEEE International Conference on Electro\/Information Technology(IEEE 2011) 1\u20135 https:\/\/doi.org\/10.1109\/EIT.2011.5978613.","DOI":"10.1109\/EIT.2011.5978613"},{"key":"e_1_2_9_16_1","doi-asserted-by":"publisher","DOI":"10.1007\/s11831\u2010019\u201009334\u2010y"},{"key":"e_1_2_9_17_1","doi-asserted-by":"crossref","unstructured":"Z.LiandC.Liu \u201cAn Image Thresholding Method Based on Standard Deviation \u201d in2009 International Joint Conference on Computational Sciences and Optimization(IEEE 2009) 835\u2013838 https:\/\/doi.org\/10.1109\/CSO.2009.177.","DOI":"10.1109\/CSO.2009.177"},{"key":"e_1_2_9_18_1","first-page":"182","volume-title":"Image Processing: Machine Vision Applications VII","author":"Sung J. 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