{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,6,1]],"date-time":"2026-06-01T12:51:14Z","timestamp":1780318274537,"version":"3.54.1"},"reference-count":27,"publisher":"Springer Science and Business Media LLC","issue":"12","license":[{"start":{"date-parts":[[2023,5,24]],"date-time":"2023-05-24T00:00:00Z","timestamp":1684886400000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0"},{"start":{"date-parts":[[2023,5,24]],"date-time":"2023-05-24T00:00:00Z","timestamp":1684886400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0"}],"funder":[{"DOI":"10.13039\/100000065","name":"National Institute of Neurological Disorders and Stroke","doi-asserted-by":"publisher","award":["5F31NS115362"],"award-info":[{"award-number":["5F31NS115362"]}],"id":[{"id":"10.13039\/100000065","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/100000065","name":"National Institute of Neurological Disorders and Stroke","doi-asserted-by":"publisher","award":["R01NS116190"],"award-info":[{"award-number":["R01NS116190"]}],"id":[{"id":"10.13039\/100000065","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["Int J CARS"],"abstract":"<jats:title>Abstract<\/jats:title><jats:sec>\n                <jats:title>Purpose<\/jats:title>\n                <jats:p>Intraoperative infrared thermography is an emerging technique for image-guided neurosurgery, whereby physiological and pathological processes result in temperature changes over space and time. However, motion during data collection leads to downstream artifacts in thermography analyses. We develop a fast, robust technique for motion estimation and correction as a preprocessing step for brain surface thermography recordings.<\/jats:p>\n              <\/jats:sec><jats:sec>\n                <jats:title>Methods<\/jats:title>\n                <jats:p>A motion correction technique for thermography was developed which approximates the deformation field associated with motion as a grid of two-dimensional bilinear splines (Bispline registration), and a regularization function was designed to constrain motion to biomechanically feasible solutions. The performance of the proposed Bispline registration technique was compared to phase correlation, a band-stop filter, demons registration, and the Horn\u2013Schunck and Lucas\u2013Kanade optical flow techniques.<\/jats:p>\n              <\/jats:sec><jats:sec>\n                <jats:title>Results<\/jats:title>\n                <jats:p>All methods were analyzed using thermography data from ten patients undergoing awake craniotomy for brain tumor resection, and performance was compared using image quality metrics. The proposed method had the lowest mean-squared error and the highest peak-signal-to-noise ratio of all methods tested and performed slightly worse than phase correlation and Demons registration on the structural similarity index metric (<jats:italic>p<\/jats:italic>\u2009&lt;\u20090.01, Wilcoxon signed-rank test). Band-stop filtering and the Lucas\u2013Kanade method were not strong attenuators of motion, while the Horn\u2013Schunck method was well-performing initially but weakened over time.<\/jats:p>\n              <\/jats:sec><jats:sec>\n                <jats:title>Conclusion<\/jats:title>\n                <jats:p>Bispline registration had the most consistently strong performance out of all the techniques tested. It is relatively fast for a nonrigid motion correction technique, capable of processing ten frames per second, and could be a viable option for real-time use. Constraining the deformation cost function through regularization and interpolation appears sufficient for fast, monomodal motion correction of thermal data during awake craniotomy.<\/jats:p>\n              <\/jats:sec>","DOI":"10.1007\/s11548-023-02953-8","type":"journal-article","created":{"date-parts":[[2023,5,24]],"date-time":"2023-05-24T12:02:18Z","timestamp":1684929738000},"page":"2223-2231","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":2,"title":["A robust motion correction technique for infrared thermography during awake craniotomy"],"prefix":"10.1007","volume":"18","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-9885-6602","authenticated-orcid":false,"given":"Michael","family":"Iorga","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-0206-7722","authenticated-orcid":false,"given":"Matthew C.","family":"Tate","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-1184-1572","authenticated-orcid":false,"given":"Todd B.","family":"Parrish","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"297","published-online":{"date-parts":[[2023,5,24]]},"reference":[{"key":"2953_CR1","doi-asserted-by":"publisher","first-page":"221","DOI":"10.1016\/j.infrared.2012.03.007","volume":"55","author":"BB Lahiri","year":"2012","unstructured":"Lahiri BB, Bagavathiappan S, Jayakumar T, Philip J (2012) Medical applications of infrared thermography: a review. Infrared Phys Technol 55:221\u2013235","journal-title":"Infrared Phys Technol"},{"key":"2953_CR2","doi-asserted-by":"publisher","first-page":"307","DOI":"10.3389\/fnins.2014.00307","volume":"8","author":"H Wang","year":"2014","unstructured":"Wang H, Wang B, Normoyle KP, Jackson K, Spitler K, Sharrock MF, Miller CM, Best C, Llano D, Du R (2014) Brain temperature and its fundamental properties: a review for clinical neuroscientists. Front Neurosci 8:307","journal-title":"Front Neurosci"},{"issue":"Suppl 2","key":"2953_CR3","doi-asserted-by":"publisher","first-page":"T154","DOI":"10.1016\/j.neuroimage.2009.03.043","volume":"47","author":"B Kateb","year":"2009","unstructured":"Kateb B, Yamamoto V, Yu C, Grundfest W, Gruen JP (2009) Infrared thermal imaging: a review of the literature and case report. Neuroimage 47(Suppl 2):T154\u2013T162","journal-title":"Neuroimage"},{"key":"2953_CR4","first-page":"350","volume":"10","author":"E Naydenov","year":"2017","unstructured":"Naydenov E, Minkin K, Penkov M, Nachev S, Stummer W (2017) Infrared thermography in surgery of newly diagnosed glioblastoma multiforme: a technical case report. CRO 10:350\u2013355","journal-title":"CRO"},{"key":"2953_CR5","doi-asserted-by":"publisher","first-page":"960","DOI":"10.3171\/jns.2004.101.6.0960","volume":"101","author":"AM Gorbach","year":"2004","unstructured":"Gorbach AM, Heiss JD, Kopylev L, Oldfield EH (2004) Intraoperative infrared imaging of brain tumors. J Neurosurg 101:960\u2013969","journal-title":"J Neurosurg"},{"key":"2953_CR6","doi-asserted-by":"publisher","first-page":"1158","DOI":"10.3171\/2009.4.JNS08585","volume":"111","author":"A Nakagawa","year":"2009","unstructured":"Nakagawa A, Fujimura M, Arafune T, Sakuma I, Tominaga T (2009) Clinical implications of intraoperative infrared brain surface monitoring during superficial temporal artery-middle cerebral artery anastomosis in patients with moyamoya disease. J Neurosurg 111:1158\u20131164","journal-title":"J Neurosurg"},{"key":"2953_CR7","first-page":"362","volume":"60","author":"Y Okada","year":"2007","unstructured":"Okada Y, Kawamata T, Kawashima A, Hori T (2007) Intraoperative application of thermography in extracranial-intracranial bypass surgery. Neurosurgery 60:362\u20135 (discussion 365)","journal-title":"Neurosurgery"},{"key":"2953_CR8","doi-asserted-by":"publisher","first-page":"297","DOI":"10.1002\/ana.10646","volume":"54","author":"AM Gorbach","year":"2003","unstructured":"Gorbach AM, Heiss J, Kufta C, Sato S, Fedio P, Kammerer WA, Solomon J, Oldfield EH (2003) Intraoperative infrared functional imaging of human brain. Ann Neurol 54:297\u2013309","journal-title":"Ann Neurol"},{"key":"2953_CR9","doi-asserted-by":"publisher","first-page":"1460","DOI":"10.3171\/jns.2002.97.6.1460","volume":"97","author":"RD Ecker","year":"2002","unstructured":"Ecker RD, Goerss SJ, Meyer FB, Cohen-Gadol AA, Britton JW, Levine JA (2002) Vision of the future: initial experience with intraoperative real-time high-resolution dynamic infrared imaging. Technical note. J Neurosurg 97:1460\u20131471","journal-title":"J Neurosurg"},{"key":"2953_CR10","doi-asserted-by":"publisher","first-page":"414","DOI":"10.1016\/j.neuchi.2021.10.005","volume":"68","author":"N Tahhan","year":"2022","unstructured":"Tahhan N, Balanca B, Fierstra J, Waelchli T, Picart T, Dumot C, Eker O, Marinesco S, Radovanovic I, Cotton F, Berhouma M (2022) Intraoperative cerebral blood flow monitoring in neurosurgery: a review of contemporary technologies and emerging perspectives. Neurochirurgie 68:414\u2013425","journal-title":"Neurochirurgie"},{"key":"2953_CR11","doi-asserted-by":"publisher","first-page":"113502","DOI":"10.1118\/1.4897569","volume":"41","author":"C Faria","year":"2014","unstructured":"Faria C, Sadowsky O, Bicho E, Ferrigno G, Joskowicz L, Shoham M, Vivanti R, De Momi E (2014) Validation of a stereo camera system to quantify brain deformation due to breathing and pulsatility. Med Phys 41:113502","journal-title":"Med Phys"},{"key":"2953_CR12","doi-asserted-by":"publisher","first-page":"514","DOI":"10.1097\/00006123-199809000-00066","volume":"43","author":"DL Hill","year":"1998","unstructured":"Hill DL, Maurer CR Jr, Maciunas RJ, Barwise JA, Fitzpatrick JM, Wang MY (1998) Measurement of intraoperative brain surface deformation under a craniotomy. Neurosurgery 43:514\u201326 (discussion 527\u20138)","journal-title":"Neurosurgery"},{"key":"2953_CR13","doi-asserted-by":"crossref","unstructured":"Ding S, Miga MI, Thompson RC, Dumpuri P, Cao A, Dawant BM (2007) Estimation of intra-operative brain shift using a tracked laser range scanner. In: Conference of proceedings IEEE engineering medicine and biology society, vol 2007, pp 848\u2013851","DOI":"10.1109\/IEMBS.2007.4352423"},{"key":"2953_CR14","doi-asserted-by":"crossref","unstructured":"Parrish T, Iorga M (2018) Application of IR thermometry to understanding brain function. In: Quantum sensing and nano electronics and photonics XV. SPIE, p 1054002","DOI":"10.1117\/12.2297486"},{"key":"2953_CR15","doi-asserted-by":"publisher","first-page":"671","DOI":"10.1109\/TBCAS.2020.3005891","volume":"14","author":"F Chen","year":"2020","unstructured":"Chen F, Muller J, Muller J, Muller J, Kirsch M, Tetzlaff R (2020) Motion correction in multimodal intraoperative imaging. IEEE Trans Biomed Circuits Syst 14:671\u2013680","journal-title":"IEEE Trans Biomed Circuits Syst"},{"key":"2953_CR16","doi-asserted-by":"crossref","unstructured":"Hoffmann N, Hollmach J, Schnabel C, Radev Y, Kirsch M, Petersohn U, Koch E, Steiner G (2014) Wavelet subspace analysis of intraoperative thermal imaging for motion filtering. Lecture notes in computer science, pp 411\u2013420","DOI":"10.1007\/978-3-319-11755-3_46"},{"key":"2953_CR17","doi-asserted-by":"publisher","unstructured":"Senger V, Hoffmann N, Muller J, Hollmach J, Schnabel C, Radev Y, Muller J, Kirsch M, Petersohn U, Steiner G, Koch E, Tetzlaff R (2014) Motion correction of thermographic images in neurosurgery: Performance comparison. In: 2014 IEEE biomedical circuits and systems conference (BioCAS) proceedings. https:\/\/doi.org\/10.1109\/biocas.2014.6981660","DOI":"10.1109\/biocas.2014.6981660"},{"key":"2953_CR18","doi-asserted-by":"publisher","unstructured":"Senger V, Tetzlaff R, Muller J, Hoffman N, Hollmach J, Schnabel C, Radev Y, Kirsch M, Petersohn U, Steiner G, Koch E (2015) Motion correction of thermographic images in neurosurgery. In: 2015 European conference on circuit theory and design (ECCTD). https:\/\/doi.org\/10.1109\/ecctd.2015.7300009","DOI":"10.1109\/ecctd.2015.7300009"},{"key":"2953_CR19","doi-asserted-by":"publisher","unstructured":"Muller J, Muller J, Thaute B, Tetzlaff R (2016) Real-time artefact filter for intraoperative thermographic imaging. In: 2016 IEEE biomedical circuits and systems conference (BioCAS). https:\/\/doi.org\/10.1109\/biocas.2016.7833737","DOI":"10.1109\/biocas.2016.7833737"},{"key":"2953_CR20","doi-asserted-by":"publisher","first-page":"226","DOI":"10.1080\/17686733.2020.1766892","volume":"18","author":"Y Moshaei-Nezhad","year":"2021","unstructured":"Moshaei-Nezhad Y, M\u00fcller J, Schnabel C, Kirsch M, Tetzlaff R (2021) A robust optical flow motion estimation and correction method for IRT imaging in brain surgery. Quant Infrared Thermogr J 18:226\u2013251","journal-title":"Quant Infrared Thermogr J"},{"key":"2953_CR21","doi-asserted-by":"publisher","unstructured":"Moshaei-Nezhad Y, Muller J, Muller J, Tetzlaff R (2017) Motion estimation and correction for thermographic imaging in brain surgery. In: 2017 European conference on circuit theory and design (ECCTD). https:\/\/doi.org\/10.1109\/ecctd.2017.8093336","DOI":"10.1109\/ecctd.2017.8093336"},{"key":"2953_CR22","doi-asserted-by":"publisher","unstructured":"Chen F, Muller J, Muller J, Muller J, Kirsch M, Tetzlaff R (2019) Motion correction for thermography using co-registered visual-light images. In: 2019 IEEE biomedical circuits and systems conference (BioCAS). https:\/\/doi.org\/10.1109\/biocas.2019.8918761","DOI":"10.1109\/biocas.2019.8918761"},{"key":"2953_CR23","doi-asserted-by":"publisher","first-page":"683","DOI":"10.1007\/s11548-022-02562-x","volume":"17","author":"Y Moshaei-Nezhad","year":"2022","unstructured":"Moshaei-Nezhad Y, M\u00fcller J, Oelschl\u00e4gel M, Kirsch M, Tetzlaff R (2022) Registration of IRT and visible light images in neurosurgery: analysis and comparison of automatic intensity-based registration approaches. Int J Comput Assist Radiol Surg 17:683\u2013697","journal-title":"Int J Comput Assist Radiol Surg"},{"key":"2953_CR24","doi-asserted-by":"publisher","first-page":"103804","DOI":"10.1016\/j.infrared.2021.103804","volume":"117","author":"Y Moshaei-Nezhad","year":"2021","unstructured":"Moshaei-Nezhad Y, M\u00fcller J, Schnabel C, Kirsch M, Tetzlaff R (2021) Motion correction for IRT imaging in neurosurgery: Analysis and comparison of frequency-\/filter- and intensity-based approaches. Infrared Phys Technol 117:103804","journal-title":"Infrared Phys Technol"},{"key":"2953_CR25","doi-asserted-by":"publisher","first-page":"S61","DOI":"10.1016\/j.neuroimage.2008.10.040","volume":"45","author":"T Vercauteren","year":"2009","unstructured":"Vercauteren T, Pennec X, Perchant A, Ayache N (2009) Diffeomorphic demons: efficient non-parametric image registration. Neuroimage 45:S61-72","journal-title":"Neuroimage"},{"key":"2953_CR26","doi-asserted-by":"publisher","unstructured":"Muller J, Muller J, Koch B, Tetzlaff R, Bohl E, Schnabel C, Koch E (2017) An intraoperative imaging system for neurosurgical thermography. In: 2017 European conference on circuit theory and design (ECCTD). https:\/\/doi.org\/10.1109\/ecctd.2017.8093307","DOI":"10.1109\/ecctd.2017.8093307"},{"key":"2953_CR27","doi-asserted-by":"publisher","first-page":"600","DOI":"10.1109\/TIP.2003.819861","volume":"13","author":"Z Wang","year":"2004","unstructured":"Wang Z, Bovik AC, Sheikh HR, Simoncelli EP (2004) Image quality assessment: from error visibility to structural similarity. IEEE Trans Image Process 13:600\u2013612","journal-title":"IEEE Trans Image Process"}],"container-title":["International Journal of Computer Assisted Radiology and Surgery"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s11548-023-02953-8.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/article\/10.1007\/s11548-023-02953-8\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s11548-023-02953-8.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2023,11,8]],"date-time":"2023-11-08T15:12:31Z","timestamp":1699456351000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/s11548-023-02953-8"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2023,5,24]]},"references-count":27,"journal-issue":{"issue":"12","published-online":{"date-parts":[[2023,12]]}},"alternative-id":["2953"],"URL":"https:\/\/doi.org\/10.1007\/s11548-023-02953-8","relation":{},"ISSN":["1861-6429"],"issn-type":[{"value":"1861-6429","type":"electronic"}],"subject":[],"published":{"date-parts":[[2023,5,24]]},"assertion":[{"value":"28 November 2022","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"5 May 2023","order":2,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"24 May 2023","order":3,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}}]}}