{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2022,7,29]],"date-time":"2022-07-29T16:40:36Z","timestamp":1659112836689},"reference-count":10,"publisher":"Walter de Gruyter GmbH","issue":"1","license":[{"start":{"date-parts":[[2017,5,24]],"date-time":"2017-05-24T00:00:00Z","timestamp":1495584000000},"content-version":"unspecified","delay-in-days":0,"URL":"http:\/\/creativecommons.org\/licenses\/by-nc-nd\/4.0"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2017,5,24]]},"abstract":"<jats:title>Abstract<\/jats:title><jats:p>The method for analysing transversal plane images from computer tomography scans is considered in the paper. This method allows not only approximating ribs-bounded contour but also evaluating patient rotation around the vertical axis during a scan. In this method, a mathematical model describing the ribs-bounded contour was created and the problem of approximation has been solved by finding the optimal parameters of the mathematical model using least-squares-type objective function. The local search has been per-formed using local descent by quasi-Newton methods. The benefits of analytical derivatives of the function are disclosed in the paper.<\/jats:p>","DOI":"10.1515\/acss-2017-0009","type":"journal-article","created":{"date-parts":[[2017,6,13]],"date-time":"2017-06-13T10:01:20Z","timestamp":1497348080000},"page":"66-70","source":"Crossref","is-referenced-by-count":0,"title":["Speeding-up the Fitting of the Model Defining the Ribs-bounded Contour"],"prefix":"10.1515","volume":"21","author":[{"given":"Mykolas J.","family":"Bilinskas","sequence":"first","affiliation":[{"name":"Institute of Mathematics and Informatics, Vilnius University, Vilnius , Lithuania"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Gintautas","family":"Dzemyda","sequence":"additional","affiliation":[{"name":"Institute of Mathematics and Informatics, Vilnius University, Vilnius , Lithuania"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Martynas","family":"Sabaliauskas","sequence":"additional","affiliation":[{"name":"Institute of Mathematics and Informatics, Vilnius University, Vilnius , Lithuania"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"374","published-online":{"date-parts":[[2017,6,13]]},"reference":[{"key":"2021040805200468273_j_acss-2017-0009_ref_001_w2aab2b8b6b1b7b1ab1ab1Aa","doi-asserted-by":"crossref","unstructured":"[1] H. Nugroho, D. Ihtatho, and H. Nugroho, \u201cContrast enhancement for liver tumor identification,\u201d The MIDAS Journal - Grand Challenge Liver Tumor Segmentation (2008 MICCAI Workshop), 2008.","DOI":"10.54294\/1uhwld"},{"key":"2021040805200468273_j_acss-2017-0009_ref_002_w2aab2b8b6b1b7b1ab1ab2Aa","doi-asserted-by":"crossref","unstructured":"[2] S. Chen, D. M. Lovelock, and R. J. Radke, \u201cSegmenting the prostate and rectum in CT imagery using anatomical constraints,\u201d Medical Image Analysis, vol. 15, no. 1, pp. 1-11, Feb. 2011. https:\/\/doi.org\/10.1016\/j.media.2010.06.004","DOI":"10.1016\/j.media.2010.06.004"},{"key":"2021040805200468273_j_acss-2017-0009_ref_003_w2aab2b8b6b1b7b1ab1ab3Aa","unstructured":"[3] M. J. Bilinskas, G. Dzemyda, and M. Trakymas, \u201cComputed tomography image analysis: The model of ribs-bounded contour,\u201d vol. 2503. Plzen, Czech Republic: Vaclav Skala - UNION Agency, 2015, pp. 81-84."},{"key":"2021040805200468273_j_acss-2017-0009_ref_004_w2aab2b8b6b1b7b1ab1ab4Aa","doi-asserted-by":"crossref","unstructured":"[4] M. J. Bilinskas and G. Dzemyda, \u201cOptimization in modeling the ribsbounded contour from computer tomography scan,\u201d in Numerical computations: theory and algorithms (NUMTA-2016): proceedings of the 2nd international conference, vol. 1776. Pizzo Calabro, Italy: AIP Publishing, 2016. https:\/\/doi.org\/10.1063\/1.4965405","DOI":"10.1063\/1.4965405"},{"key":"2021040805200468273_j_acss-2017-0009_ref_005_w2aab2b8b6b1b7b1ab1ab5Aa","doi-asserted-by":"crossref","unstructured":"[5] M. J. Bilinskas and G. Dzemyda, \u201cModelling the ribs-bounded contour in computer tomography images,\u201d in Me\u017edunarodnyj kongress po informatike: Informacionnye sistemy i tehnologii : Materialy me\u017edunarodnogo nau\u010dnogo kongressa Respublika Belarus. Minsk, Belarus: BGU, 2016, pp. 198-203. [Online]. Available: http:\/\/-elib.bsu.by\/bitstream\/123456789\/159801\/1\/Dzemyda_Bilinskas.pdf","DOI":"10.1063\/1.4965405"},{"key":"2021040805200468273_j_acss-2017-0009_ref_006_w2aab2b8b6b1b7b1ab1ab6Aa","doi-asserted-by":"crossref","unstructured":"[6] P. Treigys, V. \u0160altenis, G. Dzemyda, V. Barzd\u017eiukas, and A. Paunksnis, \u201cAutomated optic nerve disc parameterization,\u201d Informatica, vol. 19, no. 3, pp. 403-420, 2008.","DOI":"10.15388\/Informatica.2008.221"},{"key":"2021040805200468273_j_acss-2017-0009_ref_007_w2aab2b8b6b1b7b1ab1ab7Aa","doi-asserted-by":"crossref","unstructured":"[7] F. Graf, H.-P. Kriegel, M. Schubert, S. P\u00f6lsterl, and A. Cavallaro, \u201c2D image registration in CT images using radial image descriptors,\u201d in Medical Image Computing and Computer-Assisted Intervention - MICCAI 2011: 14th International Conference, Toronto, Canada, September 18-22, 2011, Proceedings, Part II, G. Fichtinger, A. Martel, and T. Peters, Eds. Berlin, Heidelberg: Springer Berlin Heidelberg, 2011, pp. 607-614. https:\/\/doi.org\/10.1007\/978-3-642-23629-7_74","DOI":"10.1007\/978-3-642-23629-7_74"},{"key":"2021040805200468273_j_acss-2017-0009_ref_008_w2aab2b8b6b1b7b1ab1ab8Aa","doi-asserted-by":"crossref","unstructured":"[8] F. P. M. Oliveira and J. M. R. S. Tavares, \u201cRegistration of plantar pressure images,\u201d International Journal for Numerical Methods in Biomedical Engineering, vol. 28, no. 6-7, pp. 589-603, Aug. 2011. https:\/\/doi.org\/10.1002\/cnm.1461","DOI":"10.1002\/cnm.1461"},{"key":"2021040805200468273_j_acss-2017-0009_ref_009_w2aab2b8b6b1b7b1ab1ab9Aa","doi-asserted-by":"crossref","unstructured":"[9] \u00c1. Fern\u00e1ndez, N. Rabin, R. R. Coifman, and J. Eckstein, \u201cDiffusion methods for aligning medical datasets: Location prediction in CT scan images,\u201d Medical Image Analysis, vol. 18, no. 2, pp. 425-432, Feb. 2014. https:\/\/doi.org\/10.1016\/j.media.2013.12.009","DOI":"10.1016\/j.media.2013.12.009"},{"key":"2021040805200468273_j_acss-2017-0009_ref_010_w2aab2b8b6b1b7b1ab1ac10Aa","unstructured":"[10] Mathworks, \u201cUnconstrained Nonlinear Optimization Algorithms,\u201d 2016. [Online]. Available: http:\/\/se.mathworks.com\/help\/optim\/ug\/unconstrained-nonlinear-optimization-algorithms.html"}],"container-title":["Applied Computer Systems"],"original-title":[],"language":"en","link":[{"URL":"http:\/\/content.sciendo.com\/view\/journals\/acss\/21\/1\/article-p66.xml","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/www.sciendo.com\/article\/10.1515\/acss-2017-0009","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2022,7,29]],"date-time":"2022-07-29T16:03:53Z","timestamp":1659110633000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.sciendo.com\/article\/10.1515\/acss-2017-0009"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2017,5,24]]},"references-count":10,"journal-issue":{"issue":"1","published-online":{"date-parts":[[2017,6,13]]},"published-print":{"date-parts":[[2017,5,24]]}},"alternative-id":["10.1515\/acss-2017-0009"],"URL":"https:\/\/doi.org\/10.1515\/acss-2017-0009","relation":{},"ISSN":["2255-8691"],"issn-type":[{"value":"2255-8691","type":"electronic"}],"subject":[],"published":{"date-parts":[[2017,5,24]]}}}