{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,2,21]],"date-time":"2025-02-21T13:25:30Z","timestamp":1740144330067,"version":"3.37.3"},"reference-count":61,"publisher":"Springer Science and Business Media LLC","issue":"12","license":[{"start":{"date-parts":[[2017,2,10]],"date-time":"2017-02-10T00:00:00Z","timestamp":1486684800000},"content-version":"unspecified","delay-in-days":0,"URL":"http:\/\/www.springer.com\/tdm"}],"funder":[{"DOI":"10.13039\/501100006461","name":"Agencia de Innovaci\u00f3n y Desarrollo de Andaluc\u00eda","doi-asserted-by":"publisher","award":["P11-TIC-7727"],"award-info":[{"award-number":["P11-TIC-7727"]}],"id":[{"id":"10.13039\/501100006461","id-type":"DOI","asserted-by":"publisher"}]},{"name":"Instituto de Salud Carlos III (ES)","award":["PT13\/0006\/0036"],"award-info":[{"award-number":["PT13\/0006\/0036"]}]}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["Int J CARS"],"published-print":{"date-parts":[[2017,12]]},"DOI":"10.1007\/s11548-017-1530-8","type":"journal-article","created":{"date-parts":[[2017,2,10]],"date-time":"2017-02-10T09:51:44Z","timestamp":1486720304000},"page":"2055-2067","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["Validation of a method for retroperitoneal tumor segmentation"],"prefix":"10.1007","volume":"12","author":[{"given":"Cristina","family":"Su\u00e1rez-Mej\u00edas","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Jos\u00e9 A.","family":"P\u00e9rez-Carrasco","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Carmen","family":"Serrano","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Jos\u00e9 L.","family":"L\u00f3pez-Guerra","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Tom\u00e1s","family":"G\u00f3mez-C\u00eda","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Carlos L.","family":"Parra-Calder\u00f3n","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Bego\u00f1a","family":"Acha","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2017,2,10]]},"reference":[{"key":"1530_CR1","unstructured":"AccuLite, AMIDE, Dicom2, Dicom3Tools, Offis, etc. \n                        https:\/\/www.xrayscan.com\/software-free-dicom-viewers\/\n                        \n                    . Accessed 11 Mar 2016"},{"key":"1530_CR2","unstructured":"IDICON et \n                        http:\/\/www.inf.u-szeged.hu\/~idicon\/\n                        \n                    . Accessed 11 Mar 2016"},{"key":"1530_CR3","unstructured":"Rubo Medical software et \n                        http:\/\/www.rubomedical.com\/\n                        \n                    . Accessed 11 Mar 2016"},{"key":"1530_CR4","unstructured":"Clijmans T, Gelaude F, Mommaerts M, Suetens P and Vander Sloten J (2006) Computer supported pre-operative planning of craniosynostosis surgery: a MIMICS-integrated approach. In: CMBBE2006, pp. 38\u201342, Antibes, France"},{"key":"1530_CR5","unstructured":"EuHeart Project. \n                        http:\/\/www.euHeart.eu\n                        \n                    . Accessed 11 Mar 2016"},{"key":"1530_CR6","unstructured":"PASSPORT Project. \n                        http:\/\/www.vph-institute.org\/news\/digital-agenda-new-virtual-liver-technology-helps-detect-liver-tumours.html\n                        \n                    . Accessed 11 Mar 2015"},{"key":"1530_CR7","unstructured":"Proplan CMF software. \n                        http:\/\/cranio-maxillofacial.materialise.com\/\n                        \n                    . Accessed 11 Mar 2016"},{"key":"1530_CR8","unstructured":"MIMICS. \n                        http:\/\/biomedical.materialise.com\/mimics\n                        \n                    . Accessed 11 Mar 2016"},{"key":"1530_CR9","unstructured":"AYRA. \n                        http:\/\/www.ikiria.es\/ayra_descripcion_eng.html\n                        \n                    . Accessed 11 Mar 2016"},{"issue":"2","key":"1530_CR10","doi-asserted-by":"publisher","first-page":"133","DOI":"10.1007\/s11548-009-0284-3","volume":"4","author":"C Su\u00e1rez","year":"2009","unstructured":"Su\u00e1rez C, Acha B, Serrano C, Parra C, G\u00f3mez T (2009) VirSSPA\u2014a virtual reality tool for surgical planning workflow. Int J Comput Assist Radiol Surg 4(2):133\u2013139. doi:\n                        10.1007\/s11548-009-0284-3","journal-title":"Int J Comput Assist Radiol Surg"},{"issue":"7","key":"1530_CR11","doi-asserted-by":"publisher","first-page":"1042","DOI":"10.1016\/j.burns.2008.09.005","volume":"35","author":"P Gacto","year":"2008","unstructured":"Gacto P, Barrera F, Sicilia-Castro D, Miralles F, Collell M, Leal S, De La Higuera J, Parra C, G\u00f3mez-C\u00eda T (2008) A three-dimensional virtual reality model for limb reconstruction in burned patients. BURNS J Int Soc Burn Inj 35(7):1042\u20131046. doi:\n                        10.1016\/j.burns.2008.09.005","journal-title":"BURNS J Int Soc Burn Inj"},{"issue":"4","key":"1530_CR12","doi-asserted-by":"publisher","first-page":"375","DOI":"10.1007\/s11548-009-0311-4","volume":"4","author":"T G\u00f3mez-C\u00eda","year":"2009","unstructured":"G\u00f3mez-C\u00eda T, Gacto-S\u00e1nchez P, Sicilia D, Su\u00e1rez C, Acha B, Serrano C, Parra C, De La Higuera J (2009) The virtual reality tool VirSSPA in planning DIEP microsurgical breast reconstruction. Int J Comput Assist Radiol Surg 4(4):375\u2013382. doi:\n                        10.1007\/s11548-009-0311-4","journal-title":"Int J Comput Assist Radiol Surg"},{"key":"1530_CR13","doi-asserted-by":"crossref","first-page":"24","DOI":"10.1097\/PRS.0b013e3181c4948b","volume":"125","author":"P Gacto-S\u00e1nchez","year":"2010","unstructured":"Gacto-S\u00e1nchez P, Sicilia-Castro D, G\u00f3mez-C\u00eda T, Lagares A, Collell T, Su\u00e1rez-Mej\u00edas C, Parra C, Leal S, Infante-Cossio De, la Higuera JM (2010) Computerised tomography angiography with VirSSPA 3D software for perforator navigation improves perioperative outcomes in DIEP flap breast reconstruction. Plast Reconstr Surg 125:24\u201331","journal-title":"Plast Reconstr Surg"},{"key":"1530_CR14","volume-title":"Digital image processing","author":"RC Gonzalez","year":"2008","unstructured":"Gonzalez RC, Woods RE (2008) Digital image processing. Pearson Prentice Hall, Upper Saddle River"},{"issue":"2000","key":"1530_CR15","doi-asserted-by":"crossref","first-page":"315","DOI":"10.1146\/annurev.bioeng.2.1.315","volume":"2","author":"DL Pham","year":"2000","unstructured":"Pham DL, Xu C, Prince JL (2000) Current methods in medical image segmentation. Annu Rev Biomed Eng 2(2000):315\u2013337","journal-title":"Annu Rev Biomed Eng"},{"issue":"1","key":"1530_CR16","doi-asserted-by":"publisher","first-page":"195","DOI":"10.3844\/jcssp.2015.195.203","volume":"11","author":"S Heidari","year":"2015","unstructured":"Heidari S, Abdullah MT, Abdullah LN (2015) A novel four-directional thresholding approach for lung computed-tomography images by using similarity-based segmentation technique. J Comput Sci 11(1):195\u2013203. doi:\n                        10.3844\/jcssp.2015.195.203","journal-title":"J Comput Sci"},{"issue":"4","key":"1530_CR17","doi-asserted-by":"publisher","first-page":"467","DOI":"10.1109\/TMI.2007.907555","volume":"27","author":"J Dehmeshki","year":"2008","unstructured":"Dehmeshki J, Amin H, Valdivieso M, Ye X (2008) Segmentation of pulmonary nodules in thoracic CT scans: a region growing approach. IEEE Trans Med Imaging 27(4):467\u2013480. doi:\n                        10.1109\/TMI.2007.907555","journal-title":"IEEE Trans Med Imaging"},{"issue":"5","key":"1530_CR18","doi-asserted-by":"publisher","first-page":"395","DOI":"10.1007\/s11801-015-5148-1","volume":"11","author":"XP Wang","year":"2015","unstructured":"Wang XP, Zhang W, Cui Y (2015) Tumor segmentation in lung CT images based on support vector machine and improved level set. Optoelectron Lett 11(5):395\u2013400. doi:\n                        10.1007\/s11801-015-5148-1","journal-title":"Optoelectron Lett"},{"issue":"4","key":"1530_CR19","doi-asserted-by":"publisher","first-page":"798","DOI":"10.1587\/transinf.E96.D.798","volume":"96","author":"AH Foruzan","year":"2013","unstructured":"Foruzan AH, Chen YW, Zoroofi RA, Furukawa A, Sato Y, Hori M, Tomiyama N (2013) Segmentation of liver in low-contrast images using K-means clustering and geodesic active contour algorithms. IEICE Trans Inf Syst 96(4):798\u2013807. doi:\n                        10.1587\/transinf.E96.D.798","journal-title":"IEICE Trans Inf Syst"},{"issue":"4","key":"1530_CR20","doi-asserted-by":"publisher","first-page":"637","DOI":"10.1109\/TMI.2012.2219589","volume":"32","author":"AB Ashraf","year":"2013","unstructured":"Ashraf AB, Gavenonis SC, Daye D, Mies C, Rosen MA, Kontos DA (2013) Multichannel Markov random field framework for tumor segmentation with an application to classification of gene expression-based breast cancer recurrence risk. IEEE Trans Med Imaging 32(4):637\u2013648. doi:\n                        10.1109\/TMI.2012.2219589","journal-title":"IEEE Trans Med Imaging"},{"issue":"8","key":"1530_CR21","doi-asserted-by":"publisher","first-page":"617","DOI":"10.1016\/j.compmedimag.2010.07.003","volume":"34","author":"J Jiang","year":"2010","unstructured":"Jiang J, Trundle P, Ren J (2010) Medical image analysis with artificial neural networks. Comput Med Imaging Graph 34(8):617\u2013631. doi:\n                        10.1016\/j.compmedimag.2010.07.003","journal-title":"Comput Med Imaging Graph"},{"key":"1530_CR22","doi-asserted-by":"publisher","DOI":"10.4015\/S1016237215500477","author":"G Sethi","year":"2015","unstructured":"Sethi G, Saini BS (2015) Segmentation of abdomen diseases using active contour models in CT images. Biomed Eng Appl Basis Commun. doi:\n                        10.4015\/S1016237215500477","journal-title":"Biomed Eng Appl Basis Commun"},{"issue":"1","key":"1530_CR23","doi-asserted-by":"publisher","first-page":"262","DOI":"10.1016\/j.cmpb.2012.04.006","volume":"108","author":"S Ghose","year":"2012","unstructured":"Ghose S, Oliver A, Mart\u00ed R, Llad\u00f3 X, Vilanova JC, Freixenet J, Mitra J, Sidib\u00e9 D, Meriaudeau F (2012) A survey of prostate segmentation methodologies in ultrasound, magnetic resonance and computed tomography images. Comput Methods Programs Biomed 108(1):262\u2013287. doi:\n                        10.1016\/j.cmpb.2012.04.006","journal-title":"Comput Methods Programs Biomed"},{"issue":"2","key":"1530_CR24","doi-asserted-by":"publisher","first-page":"542","DOI":"10.1016\/j.ultrasmedbio.2014.09.019","volume":"41","author":"W Qiu","year":"2015","unstructured":"Qiu W, Yuan J, Kishimoto J, McLeod J, Chen Y, de Ribaupierre S, Fenster A (2015) User-guided segmentation of preterm neonate ventricular system from 3-D ultrasound images using convex optimization. Ultrasound Med Biol 41(2):542\u2013556. doi:\n                        10.1016\/j.ultrasmedbio.2014.09.019","journal-title":"Ultrasound Med Biol"},{"issue":"1","key":"1530_CR25","doi-asserted-by":"publisher","first-page":"81","DOI":"10.1016\/j.patrec.2013.07.010","volume":"43","author":"J Peng","year":"2013","unstructured":"Peng J, Wang Y, Kong D (2013) Liver segmentation with constrained convex variational model. Pattern Recogn Lett 43(1):81\u201388. doi:\n                        10.1016\/j.patrec.2013.07.010","journal-title":"Pattern Recogn Lett"},{"key":"1530_CR26","doi-asserted-by":"publisher","first-page":"199","DOI":"10.1016\/j.neucom.2014.12.061","volume":"156","author":"Y Zhou","year":"2015","unstructured":"Zhou Y, Shi WR, Chen W, Chen YL, Li Y, Tan LW, Chen DQ (2015) Active contours driven by localizing region and edge-based intensity fitting energy with application to segmentation of the left ventricle in cardiac CT images. Neurocomputing 156:199\u2013210. doi:\n                        10.1016\/j.neucom.2014.12.061","journal-title":"Neurocomputing"},{"issue":"12","key":"1530_CR27","doi-asserted-by":"publisher","first-page":"5854","DOI":"10.1109\/TIP.2015.2488902","volume":"24","author":"W Ju","year":"2015","unstructured":"Ju W, Xiang D, Zhang B, Wang L, Kopriva I, Chen X (2015) Random walk and graph cut for co-segmentation of lung tumor on PET-CT images. IEEE Trans Image Process 24(12):5854\u20135867. doi:\n                        10.1109\/TIP.2015.2488902","journal-title":"IEEE Trans Image Process"},{"issue":"3","key":"1530_CR28","doi-asserted-by":"publisher","first-page":"464","DOI":"10.1109\/JSEN.2011.2108281","volume":"12","author":"S Casciaro","year":"2012","unstructured":"Casciaro S, Franchini R, Massoptier L, Casciaro E, Conversano F, Malvasi A, Lay-Ekuakille A (2012) Fully automatic segmentations of liver and hepatic tumors from 3-D computed tomography abdominal images: comparative evaluation of two automatic methods. IEEE Sens J 12(3):464\u2013473. doi:\n                        10.1109\/JSEN.2011.2108281","journal-title":"IEEE Sens J"},{"issue":"4","key":"1530_CR29","doi-asserted-by":"publisher","first-page":"543","DOI":"10.1016\/j.media.2009.05.004","volume":"13","author":"T Heimann","year":"2009","unstructured":"Heimann T, Meinzer HP (2009) Statistical shape models for 3D medical image segmentation: a review. Med Image Anal 13(4):543\u2013563. doi:\n                        10.1016\/j.media.2009.05.004","journal-title":"Med Image Anal"},{"issue":"7","key":"1530_CR30","doi-asserted-by":"publisher","first-page":"1017","DOI":"10.1016\/S0301-5629(03)00059-0","volume":"29","author":"DR Chen","year":"2003","unstructured":"Chen DR, Chang RF, Wu WJ, Moon WK, Wu WL (2003) 3-D breast ultrasound segmentation using active contour model. Ultrasound Med Biol 29(7):1017\u20131026. doi:\n                        10.1016\/S0301-5629(03)00059-0","journal-title":"Ultrasound Med Biol"},{"issue":"4","key":"1530_CR31","doi-asserted-by":"publisher","first-page":"363","DOI":"10.1179\/016164105X48842","volume":"27","author":"M Droske","year":"2005","unstructured":"Droske M, Meyer B, Rumpf M, Schaller C (2005) An adaptive level set method for interactive segmentation of intracranial tumors. Neurol Res 27(4):363\u2013370. doi:\n                        10.1179\/016164105X48842","journal-title":"Neurol Res"},{"issue":"4","key":"1530_CR32","doi-asserted-by":"publisher","first-page":"947","DOI":"10.1109\/TMI.2014.2300694","volume":"33","author":"W Qiu","year":"2014","unstructured":"Qiu W, Yuan J, Ukwatta E, Sun Y, Rajchl M, Fenster A (2014) Prostate segmentation: an efficient convex optimization approach with axial symmetry using 3-D tRUS and MR images. IEEE Trans Med Imaging 33(4):947\u2013960. doi:\n                        10.1109\/TMI.2014.2300694","journal-title":"IEEE Trans Med Imaging"},{"key":"1530_CR33","doi-asserted-by":"publisher","unstructured":"Yuan J, Bae E, Tai XC (2010) A study on continuous max-flow and min-cut approaches. In: Proceedings of the IEEE Computer Society conference on computer vision and pattern recognition, pp 2217\u20132224. doi:\n                        10.1109\/CVPR.2010.5539903","DOI":"10.1109\/CVPR.2010.5539903"},{"key":"1530_CR34","unstructured":"Yuan J, Ukwatta E, Tai XC, Fenster A, Schnoerr C (2012) A fast global optimization-based approach to evolving contours with generic shape prior. UCLA technical report CAM: 12-38"},{"issue":"12","key":"1530_CR35","doi-asserted-by":"publisher","first-page":"3243","DOI":"10.1109\/TIP.2010.2069690","volume":"19","author":"C Li","year":"2010","unstructured":"Li C, Xu C, Gui C, Fox MD (2010) Distance regularized level set evolution and its application to image segmentation. IEEE Trans Image Process 19(12):3243\u20133254. doi:\n                        10.1109\/TIP.2010.2069690","journal-title":"IEEE Trans Image Process"},{"issue":"2","key":"1530_CR36","doi-asserted-by":"publisher","first-page":"109","DOI":"10.1007\/s11263-006-7934-5","volume":"70","author":"Y Boykov","year":"2006","unstructured":"Boykov Y, Funka-Lea G (2006) Graph cuts and efficient N-D image segmentation. Int J Comput Vis 70(2):109\u2013131. doi:\n                        10.1007\/s11263-006-7934-5","journal-title":"Int J Comput Vis"},{"issue":"2","key":"1530_CR37","doi-asserted-by":"publisher","first-page":"266","DOI":"10.1109\/83.902291","volume":"10","author":"TF Chan","year":"2001","unstructured":"Chan TF, Vese LA (2001) Active contours without edges. IEEE Trans Image Process 10(2):266\u2013277. doi:\n                        10.1109\/83.902291","journal-title":"IEEE Trans Image Process"},{"key":"1530_CR38","doi-asserted-by":"publisher","unstructured":"Yousefi H, Fatehi M, Amian M, Zoroofi RA (2013) A fully automated segmentation of radius bone based on active contour in wrist MRI data set. In: 2013 20th Iranian conference on biomedical engineering, ICBME 2013. doi:\n                        10.1109\/ICBME.2013.6782190","DOI":"10.1109\/ICBME.2013.6782190"},{"issue":"1","key":"1530_CR39","doi-asserted-by":"publisher","first-page":"205","DOI":"10.1016\/j.media.2015.06.012","volume":"24","author":"JE Iglesias","year":"2015","unstructured":"Iglesias JE, Sabuncu MR (2015) Multi-atlas segmentation of biomedical images: a survey. Med Image Anal 24(1):205\u2013219. doi:\n                        10.1016\/j.media.2015.06.012","journal-title":"Med Image Anal"},{"issue":"10","key":"1530_CR40","doi-asserted-by":"publisher","first-page":"9661","DOI":"10.1016\/j.eswa.2012.02.095","volume":"39","author":"BN Li","year":"2012","unstructured":"Li BN, Chui CK, Chang S, Ong SH (2012) A new unified level set method for semi-automatic liver tumor segmentation on contrast-enhanced CT images. Expert Syst Appl 39(10):9661\u20139668. doi:\n                        10.1016\/j.eswa.2012.02.095","journal-title":"Expert Syst Appl"},{"issue":"6","key":"1530_CR41","first-page":"2681","volume":"10","author":"R Rajagopal","year":"2015","unstructured":"Rajagopal R, Subbaiah P (2015) A survey on liver tumor detection and segmentation methods. ARPN J Eng Appl Sci 10(6):2681\u20132685","journal-title":"ARPN J Eng Appl Sci"},{"issue":"4","key":"1530_CR42","doi-asserted-by":"publisher","first-page":"476","DOI":"10.1007\/s10278-016-9859-z","volume":"29","author":"J Kalpathy-Cramer","year":"2016","unstructured":"Kalpathy-Cramer J, Zhao B, Goldgof D, Gu Y, Wang X, Yang H, Tan Y, Gillies R, Napel S (2016) A comparison of lung nodule segmentation algorithms: methods and results from a multi-institutional study. J Digit Imaging 29(4):476\u2013487. doi:\n                        10.1007\/s10278-016-9859-z","journal-title":"J Digit Imaging"},{"issue":"2","key":"1530_CR43","doi-asserted-by":"publisher","first-page":"359","DOI":"10.1016\/j.media.2013.12.002","volume":"18","author":"G Litjens","year":"2014","unstructured":"Litjens G, Toth R, van de Ven W, Hoeks C, Kerkstra S, van Ginneken B, Vincent G, Guillard G, Birbeck N, Zhang J, Strand R, Malmberg F, Ou Y, Davatzikos C, Kirschner M, Jung F, Yuan J, Qiu W, Gao Q, Edwards PE, Maan B, van der Heijden F, Ghose S, Mitra J, Dowling J, Barratt D, Huisman H, Madabhushi A (2014) Evaluation of prostate segmentation algorithms for MRI: the PROMISE12 challenge (2014). Med Image Anal 18(2):359\u2013373. doi:\n                        10.1016\/j.media.2013.12.002","journal-title":"Med Image Anal"},{"issue":"9","key":"1530_CR44","doi-asserted-by":"publisher","first-page":"966","DOI":"10.1016\/j.cviu.2012.11.017","volume":"117","author":"V Tavakoli","year":"2013","unstructured":"Tavakoli V, Amini AA (2013) A survey of shaped-based registration and segmentation techniques for cardiac images. Comput Vis Image Underst 117(9):966\u2013989. doi:\n                        10.1016\/j.cviu.2012.11.017","journal-title":"Comput Vis Image Underst"},{"issue":"4","key":"1530_CR45","doi-asserted-by":"publisher","first-page":"1333","DOI":"10.1137\/110850372","volume":"5","author":"K Punithakumar","year":"2012","unstructured":"Punithakumar K, Yuan J, Ben Ayed I, Li S, Boykov Y (2012) A convex max-flow approach to distribution-based figure-ground separation. SIAM J Imaging Sci 5(4):1333\u20131354. doi:\n                        10.1137\/110850372","journal-title":"SIAM J Imaging Sci"},{"issue":"4","key":"1530_CR46","doi-asserted-by":"publisher","first-page":"275","DOI":"10.1308\/003588411X571944","volume":"93","author":"DC Strauss","year":"2011","unstructured":"Strauss DC, Hayes AJ, Thomas JM (2011) Retroperitoneal tumours: review of management. Ann R Coll Surg Engl 93(4):275\u2013280. doi:\n                        10.1308\/003588411X571944","journal-title":"Ann R Coll Surg Engl"},{"issue":"1","key":"1530_CR47","doi-asserted-by":"publisher","first-page":"53","DOI":"10.1007\/s13244-013-0294-0","volume":"5","author":"C Brennan","year":"2014","unstructured":"Brennan C, Kajal D, Khalili K, Ghai S (2014) Solid malignant retroperitoneal masses\u2014a pictorial review. Insights Imaging 5(1):53\u201365. doi:\n                        10.1007\/s13244-013-0294-0","journal-title":"Insights Imaging"},{"issue":"4","key":"1530_CR48","doi-asserted-by":"publisher","first-page":"949","DOI":"10.1148\/rg.314095132","volume":"31","author":"P Rajiah","year":"2011","unstructured":"Rajiah P, Sinha R, Cuevas C, Dubinsky TJ, Bush WH, Kolokythas O (2011) Imaging of uncommon retroperitoneal masses. RadioGraphics 31(4):949\u2013976. doi:\n                        10.1148\/rg.314095132","journal-title":"RadioGraphics"},{"issue":"11","key":"1530_CR49","first-page":"4951","volume":"32","author":"WL Monsky","year":"2012","unstructured":"Monsky WL, Jin B, Molloy C, Canter RJ, Li CS, Lin TC, Borys D, Mack W, Kim I, Buonocore MH, Chaudhari AJ (2012) Semi-automated volumetric quantification of tumor necrosis in soft tissue sarcoma using contrast-enhanced MRI. Anticancer Res 32(11):4951\u20134962","journal-title":"Anticancer Res"},{"key":"1530_CR50","doi-asserted-by":"publisher","unstructured":"Su\u00e1rez-Mej\u00edas C, P\u00e9rez-Carrasco JA, Serrano C, L\u00f3pez-Guerra JL, Parra-Calder\u00f3n C, G\u00f3mez-C\u00eda T, Acha B (2016) Three dimensional segmentation of retroperitoneal masses using continuous convex relaxation and accumulated gradient distance for radiotherapy planning. Med Biol Eng Comput (MBEC). doi:\n                        10.1007\/s11517-016-1505-x","DOI":"10.1007\/s11517-016-1505-x"},{"key":"1530_CR51","doi-asserted-by":"publisher","first-page":"360","DOI":"10.1007\/978-3-319-00846-2_89","volume":"41","author":"JA P\u00e9rez-Carrasco","year":"2014","unstructured":"P\u00e9rez-Carrasco JA, Su\u00e1rez-Mej\u00edas C, Serrano C, L\u00f3pez-Guerra JL, Acha B (2014) Segmentation of retroperitoneal tumors using fast continuous max-flow algorithm. IFMBE Proc 41:360\u2013363. doi:\n                        10.1007\/978-3-319-00846-2_89","journal-title":"IFMBE Proc"},{"key":"1530_CR52","doi-asserted-by":"crossref","unstructured":"Yuan J, Bae E, Xue-Cheng T, Yuri B (2010) A continuous max-flow approach to Potts model. In: ECCV 2010, Part VI, LNCS 6316, pp 379\u2013392","DOI":"10.1007\/978-3-642-15567-3_28"},{"key":"1530_CR53","unstructured":"Vincent L (1998) Minimal path algorithms for the robust detection of linear features in gray images. In: ISSM, pp 331\u2013338"},{"key":"1530_CR54","doi-asserted-by":"crossref","unstructured":"Mendoza C, Acha Pi\u00f1ero B, Serrano Gotarredona MC, G\u00f3mez C\u00eda PT (2009) Self-assessed contrast-maximizing adaptive region growing. Lecture Notes in Computer Science, vol 580, pp 652\u2013663","DOI":"10.1007\/978-3-642-04697-1_61"},{"issue":"1","key":"1530_CR55","doi-asserted-by":"crossref","first-page":"165","DOI":"10.1007\/s00138-010-0274-z","volume":"23","author":"C Mendoza","year":"2012","unstructured":"Mendoza C, Acha Pi\u00f1ero B, Serrano Gotarredona MC, G\u00f3mez C\u00eda PT (2012) Fast parameter-free region growing segmentation with application to surgical planning. Mach Vis Appl 23(1):165\u2013177","journal-title":"Mach Vis Appl"},{"key":"1530_CR56","unstructured":"Pinnacle 9.8 at \n                        http:\/\/www.healthcare.philips.com\/main\/products\/ros\/products\/pinnacle3_98\/\n                        \n                    . Accessed 11 Mar 2016"},{"key":"1530_CR57","first-page":"547","volume":"37","author":"P Jaccard","year":"1901","unstructured":"Jaccard P (1901) \u00c9tude comparative de la distribution florale dans une portion des Alpes et des Jura. Bull Soc Vaud Sci Nat 37:547\u2013579","journal-title":"Bull Soc Vaud Sci Nat"},{"key":"1530_CR58","unstructured":"DICE coefficient at \n                        http:\/\/sve.loni.ucla.edu\/instructions\/metrics\/dice\/\n                        \n                    . Accessed 20 Nov 2015"},{"key":"1530_CR59","doi-asserted-by":"publisher","first-page":"122","DOI":"10.1016\/j.neuroimage.2009.03.068","volume":"47","author":"H Chang","year":"2009","unstructured":"Chang H, Zhuang AH, Valentino DJ, Chi WC (2009) Performance measure characterization for evaluating neuroimage segmentation algorithms. NeuroImage 47:122\u2013135. doi:\n                        10.1016\/j.neuroimage.2009.03.068","journal-title":"NeuroImage"},{"key":"1530_CR60","doi-asserted-by":"crossref","unstructured":"Estrada J, Jepson A (2005) Quantitative evaluation of a novel image segmentation algorithm. In: IEEE Computer Society conference on computer vision and pattern recognition, CVPR, pp 1132\u20131139","DOI":"10.1109\/CVPR.2005.284"},{"issue":"3","key":"1530_CR61","doi-asserted-by":"publisher","first-page":"473","DOI":"10.1109\/TBME.2006.888831.63","volume":"54","author":"J Xu","year":"2007","unstructured":"Xu J, Chutatape O, Chew P (2007) Automated optic disk boundary detection by modified active contour model. IEEE Trans Biomed Eng 54(3):473\u2013482. doi:\n                        10.1109\/TBME.2006.888831.63","journal-title":"IEEE Trans Biomed Eng"}],"container-title":["International Journal of Computer Assisted Radiology and Surgery"],"original-title":[],"language":"en","link":[{"URL":"http:\/\/link.springer.com\/article\/10.1007\/s11548-017-1530-8\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"http:\/\/link.springer.com\/content\/pdf\/10.1007\/s11548-017-1530-8.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"http:\/\/link.springer.com\/content\/pdf\/10.1007\/s11548-017-1530-8.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2017,11,25]],"date-time":"2017-11-25T02:22:37Z","timestamp":1511576557000},"score":1,"resource":{"primary":{"URL":"http:\/\/link.springer.com\/10.1007\/s11548-017-1530-8"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2017,2,10]]},"references-count":61,"journal-issue":{"issue":"12","published-print":{"date-parts":[[2017,12]]}},"alternative-id":["1530"],"URL":"https:\/\/doi.org\/10.1007\/s11548-017-1530-8","relation":{},"ISSN":["1861-6410","1861-6429"],"issn-type":[{"type":"print","value":"1861-6410"},{"type":"electronic","value":"1861-6429"}],"subject":[],"published":{"date-parts":[[2017,2,10]]}}}