{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,9,29]],"date-time":"2026-09-29T15:53:21Z","timestamp":1790697201277,"version":"4.1.0"},"reference-count":51,"publisher":"Springer Science and Business Media LLC","issue":"5","license":[{"start":{"date-parts":[[2022,5,6]],"date-time":"2022-05-06T00:00:00Z","timestamp":1651795200000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springer.com\/tdm"},{"start":{"date-parts":[[2022,5,6]],"date-time":"2022-05-06T00:00:00Z","timestamp":1651795200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.springer.com\/tdm"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["J Digit Imaging"],"published-print":{"date-parts":[[2022,10]]},"DOI":"10.1007\/s10278-022-00632-9","type":"journal-article","created":{"date-parts":[[2022,5,6]],"date-time":"2022-05-06T17:03:32Z","timestamp":1651856612000},"page":"1207-1216","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":13,"title":["Categorization of Common Pigmented Skin Lesions (CPSL) using Multi-Deep Features and Support Vector Machine"],"prefix":"10.1007","volume":"35","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-3477-6715","authenticated-orcid":false,"given":"Prabira Kumar","family":"Sethy","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Santi Kumari","family":"Behera","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Nithiyanathan","family":"Kannan","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"297","published-online":{"date-parts":[[2022,5,6]]},"reference":[{"key":"632_CR1","volume-title":"Cancer Facts & Figures 2018","author":"A. C. Society","year":"2018","unstructured":"A. C. Society. Cancer Facts & Figures 2018. Atlanta, American Cancer Society.\u00a02018."},{"issue":"1","key":"632_CR2","doi-asserted-by":"publisher","first-page":"101","DOI":"10.1001\/archderm.143.1.101","volume":"143","author":"HK Koh","year":"2007","unstructured":"Koh HK. Melanoma screening: focusing the public health journey. Archives of Dermatology. 2007\u00a0Jan 1;143(1):101-3","journal-title":"Archives of dermatology."},{"issue":"1","key":"632_CR3","doi-asserted-by":"publisher","first-page":"11","DOI":"10.1111\/bjd.12492","volume":"170","author":"V Nikolaou","year":"2014","unstructured":"Nikolaou V, Stratigos AJ. Emerging trends in the epidemiology of melanoma. British Journal of Dermatology. 2014\u00a0Jan 1;170(1):11-9.","journal-title":"British Journal of dermatology."},{"key":"632_CR4","volume-title":"Cancer Facts & Figures 2008","author":"A. C. Society","year":"2008","unstructured":"A. C. Society. Cancer Facts & Figures 2008. Atlanta, American Cancer Society.\u00a02008."},{"issue":"9","key":"632_CR5","doi-asserted-by":"publisher","first-page":"4426","DOI":"10.1002\/mp.12335","volume":"44","author":"H Safigholi","year":"2017","unstructured":"Safigholi H, Meigooni AS, Song WY. Comparison of 192Ir, 169Yb, and 60Co high-dose-rate brachytherapy sources for skin cancer treatment. Medical Physics. 2017 Sep;44(9):4426-36.","journal-title":"Medical Physics."},{"issue":"5","key":"632_CR6","doi-asserted-by":"publisher","first-page":"219","DOI":"10.1120\/jacmp.v16i5.5407","volume":"16","author":"H Safigholi","year":"2015","unstructured":"Safigholi H, Song WY, Meigooni AS. Optimum radiation source for radiation therapy of skin cancer. Journal of applied clinical medical physics. 2015 Sep;16(5):219-27.","journal-title":"Journal of applied clinical medical physics."},{"issue":"6","key":"632_CR7","doi-asserted-by":"publisher","first-page":"840","DOI":"10.1016\/j.brachy.2015.06.005","volume":"14","author":"Z Ouhib","year":"2015","unstructured":"Ouhib Z, Kasper M, Calatayud JP, Rodriguez S, Bhatnagar A, Pai S, Strasswimmer J. Aspects of dosimetry and clinical practice of skin brachytherapy: The American Brachytherapy Society working group report. Brachytherapy. 2015 Nov 1;14(6):840-58.","journal-title":"Brachytherapy."},{"issue":"8","key":"632_CR8","doi-asserted-by":"publisher","first-page":"9909","DOI":"10.1007\/s11042-018-5714-1","volume":"77","author":"UO Dorj","year":"2018","unstructured":"Dorj UO, Lee KK, Choi JY, Lee M. The skin cancer classification using deep convolutional neural network. Multimedia Tools and Applications. 2018 Apr 1;77(8):9909-24.","journal-title":"Multimedia Tools and Applications."},{"issue":"7639","key":"632_CR9","doi-asserted-by":"publisher","first-page":"115","DOI":"10.1038\/nature21056","volume":"542","author":"A Esteva","year":"2017","unstructured":"Esteva A, Kuprel B, Novoa RA, Ko J, Swetter SM, Blau HM, Thrun S. Dermatologist-level classification of skin cancer with deep neural networks. Nature. 2017 Feb;542(7639):115-8.","journal-title":"Nature."},{"issue":"12","key":"632_CR10","doi-asserted-by":"publisher","first-page":"15217","DOI":"10.1016\/j.eswa.2011.05.079","volume":"38","author":"D Ruiz","year":"2011","unstructured":"Ruiz D, Berenguer V, Soriano A, S\u00e1Nchez B. A decision support system for the diagnosis of melanoma: A comparative approach. Expert Systems with Applications. 2011 Nov 1;38(12):15217-23.","journal-title":"Expert Systems with Applications."},{"issue":"1","key":"632_CR11","doi-asserted-by":"publisher","first-page":"40","DOI":"10.1007\/s13671-014-0069-y","volume":"3","author":"SV Mohan","year":"2014","unstructured":"Mohan SV, Chang AL. Advanced basal cell carcinoma: epidemiology and therapeutic innovations. Current dermatology reports. 2014 Mar 1;3(1):40-5.","journal-title":"Current dermatology reports."},{"issue":"7","key":"632_CR12","doi-asserted-by":"publisher","first-page":"461","DOI":"10.1111\/j.1346-8138.1994.tb01775.x","volume":"21","author":"B Lindel\u00f6f","year":"1994","unstructured":"Lindel\u00f6f B, Hedblad MA. Accuracy in the clinical diagnosis and pattern of malignant melanoma at a dermatological clinic. The Journal of dermatology. 1994 Jul;21(7):461-4.","journal-title":"The Journal of dermatology."},{"issue":"2","key":"632_CR13","doi-asserted-by":"publisher","first-page":"283","DOI":"10.1046\/j.1365-2133.1998.02075.x","volume":"138","author":"CA Morton","year":"1998","unstructured":"Morton CA, Mackie RM. Clinical accuracy of the diagnosis of cutaneous malignant melanoma. The British Journal of dermatology. 1998 Feb;138(2):283-7.","journal-title":"The British Journal of dermatology."},{"issue":"7","key":"632_CR14","doi-asserted-by":"publisher","first-page":"443","DOI":"10.1016\/S1470-2045(00)00422-8","volume":"2","author":"G Argenziano","year":"2001","unstructured":"Argenziano G, Soyer HP. Dermoscopy of pigmented skin lesions\u2013a valuable tool for early. The lancet oncology. 2001 Jul 1;2(7):443-9.","journal-title":"The lancet oncology."},{"issue":"10","key":"632_CR15","doi-asserted-by":"publisher","first-page":"1343","DOI":"10.1001\/archderm.137.10.1343","volume":"137","author":"ML Bafounta","year":"2001","unstructured":"Bafounta ML, Beauchet A, Aegerter P, Saiag P. Is dermoscopy (epiluminescence microscopy) useful for the diagnosis of melanoma? Results of a meta-analysis using techniques adapted to the evaluation of diagnostic tests. Archives of dermatology. 2001 Oct 1;137(10):1343-50.","journal-title":"Archives of dermatology."},{"issue":"3","key":"632_CR16","first-page":"669","volume":"159","author":"ME Vestergaard","year":"2008","unstructured":"Vestergaard ME, Macaskill PH, Holt PE, Menzies SW. Dermoscopy compared with naked eye examination for the diagnosis of primary melanoma: a meta\u2010analysis of studies performed in a clinical setting. British Journal of Dermatology. 2008 Sep;159(3):669-76.","journal-title":"British Journal of Dermatology."},{"issue":"7","key":"632_CR17","doi-asserted-by":"publisher","first-page":"805","DOI":"10.1111\/jdv.12032","volume":"27","author":"G Salerni","year":"2013","unstructured":"Salerni G, Ter\u00e1n T, Puig S, Malvehy J, Zalaudek I, Argenziano G, Kittler H. Meta\u2010analysis of digital dermoscopy follow\u2010up of melanocytic skin lesions: a study on behalf of the International Dermoscopy Society. Journal of the European Academy of Dermatology and Venereology. 2013 Jul;27(7):805-14.","journal-title":"Journal of the European Academy of Dermatology and Venereology."},{"issue":"3","key":"632_CR18","doi-asserted-by":"publisher","first-page":"286","DOI":"10.1001\/archderm.1995.01690150050011","volume":"131","author":"M Binder","year":"1995","unstructured":"Binder M, Schwarz M, Winkler A, Steiner A, Kaider A, Wolff K, Pehamberger H. Epiluminescence microscopy: a useful tool for the diagnosis of pigmented skin lesions for formally trained dermatologists. Archives of dermatology. 1995 Mar 1;131(3):286-91.","journal-title":"Archives of dermatology."},{"issue":"1","key":"632_CR19","doi-asserted-by":"publisher","first-page":"109","DOI":"10.1016\/j.jaad.2001.11.001","volume":"52","author":"RP Braun","year":"2005","unstructured":"Braun RP, Rabinovitz HS, Oliviero M, Kopf AW, Saurat JH. Dermoscopy of pigmented skin lesions. Journal of the American Academy of Dermatology. 2005 Jan 1;52(1):109-21.","journal-title":"Journal of the American Academy of Dermatology."},{"issue":"3","key":"632_CR20","doi-asserted-by":"publisher","first-page":"159","DOI":"10.1016\/S1470-2045(02)00679-4","volume":"3","author":"H Kittler","year":"2002","unstructured":"Kittler H, Pehamberger H, Wolff K, Binder MJ. Diagnostic accuracy of dermoscopy. The lancet oncology. 2002 Mar 1;3(3):159-65.","journal-title":"The lancet oncology."},{"issue":"3","key":"632_CR21","doi-asserted-by":"publisher","first-page":"481","DOI":"10.1046\/j.1365-2133.2002.04978.x","volume":"147","author":"D Piccolo","year":"2002","unstructured":"Piccolo D, Ferrari A, Peris KE, Daidone R, Ruggeri B, Chimenti S. Dermoscopic diagnosis by a trained clinician vs a clinician with minimal dermoscopy training vs computer\u2010aided diagnosis of 341 pigmented skin lesions: a comparative study. British Journal of Dermatology. 2002 ;147(3):481-6.","journal-title":"British Journal of Dermatology."},{"issue":"4","key":"632_CR22","doi-asserted-by":"publisher","first-page":"571","DOI":"10.1016\/S0190-9622(87)70239-4","volume":"17","author":"H Pehamberger","year":"1987","unstructured":"Pehamberger H, Steiner A, Wolff K. In vivo epiluminescence microscopy of pigmented skin lesions I Pattern analysis of pigmented skin lesions. Journal of the American Academy of Dermatology. 1987 17(4):571-83.","journal-title":"Journal of the American Academy of Dermatology."},{"issue":"3 Pt B","key":"632_CR23","first-page":"433","volume":"7","author":"A Steiner","year":"1987","unstructured":"Steiner A, Pehamberger H, Wolff K. Improvement of the diagnostic accuracy in pigmented skin lesions by epiluminescent light microscopy. Anticancer research. 1987;7(3):433-4.","journal-title":"Anticancer research."},{"issue":"8","key":"632_CR24","doi-asserted-by":"publisher","first-page":"1008","DOI":"10.1001\/archderm.141.8.1008","volume":"141","author":"C Dolianitis","year":"2005","unstructured":"Dolianitis C, Kelly J, Wolfe R, Simpson P. Comparative performance of 4 dermoscopic algorithms by nonexperts for the diagnosis of melanocytic lesions. Archives of dermatology. 2005;141(8):1008-14.","journal-title":"Archives of dermatology."},{"issue":"5","key":"632_CR25","doi-asserted-by":"publisher","first-page":"981","DOI":"10.1046\/j.1365-2133.2003.05023.x","volume":"148","author":"P Carli","year":"2003","unstructured":"Carli P, Quercioli E, Sestini S, Stante M, Ricci L, Brunasso G, De Giorgi V. Pattern analysis, not simplified algorithms, is the most reliable method for teaching dermoscopy for melanoma diagnosis to residents in dermatology. British Journal of Dermatology. 2003 May;148(5):981-4.","journal-title":"British Journal of Dermatology."},{"issue":"6","key":"632_CR26","doi-asserted-by":"publisher","first-page":"1881","DOI":"10.1158\/1078-0432.CCR-03-0039","volume":"10","author":"M Burroni","year":"2004","unstructured":"Burroni M, Corona R, Dell\u2019Eva G, Sera F, Bono R, Puddu P, Perotti R, Nobile F, Andreassi L, Rubegni P. Melanoma computer-aided diagnosis: reliability and feasibility study. Clinical cancer research. 2004 Mar 15;10(6):1881-6.","journal-title":"Clinical cancer research."},{"key":"632_CR27","unstructured":"Gutman D et al. Skin lesion analysis toward melanoma detection: A challenge at the international symposium on biomedical imaging (ISBI) 2016, hosted by the international skin imaging collaboration (ISIC). 2016."},{"issue":"3","key":"632_CR28","doi-asserted-by":"publisher","first-page":"361","DOI":"10.1001\/archderm.139.3.361","volume":"139","author":"B Rosado","year":"2003","unstructured":"Rosado B, Menzies S, Harbauer A, Pehamberger H, Wolff K, Binder M, Kittler H. Accuracy of computer diagnosis of melanoma: a quantitative meta-analysis. Archives of Dermatology. 2003 Mar 1;139(3):361-7.","journal-title":"Archives of Dermatology."},{"key":"632_CR29","first-page":"2013","volume":"30","author":"A Masood","year":"2013","unstructured":"Masood A, Ali Al-Jumaily A. Computer-aided diagnostic support system for skin cancer: a review of techniques and algorithms. International Journal of biomedical imaging. 2013 Oct 30;2013.","journal-title":"International Journal of biomedical imaging."},{"issue":"3","key":"632_CR30","first-page":"1146","volume":"19","author":"C Barata","year":"2014","unstructured":"Barata C, Celebi ME, Marques JS. Improving dermoscopy image classification using color constancy. IEEE Journal of biomedical and health informatics. 2014 Jul 25;19(3):1146-52.","journal-title":"IEEE Journal of biomedical and health informatics."},{"issue":"6","key":"632_CR31","doi-asserted-by":"publisher","first-page":"1239","DOI":"10.1109\/TITB.2012.2212282","volume":"16","author":"R Garnavi","year":"2012","unstructured":"Garnavi R, Aldeen M, Bailey J. Computer-aided diagnosis of melanoma using border-and wavelet-based texture analysis. IEEE Transactions on Information Technology in Biomedicine. 2012 Aug 8;16(6):1239-52.","journal-title":"IEEE Transactions on Information Technology in Biomedicine."},{"issue":"4","key":"632_CR32","doi-asserted-by":"publisher","first-page":"1220","DOI":"10.1109\/TBME.2013.2297622","volume":"61","author":"J Glaister","year":"2014","unstructured":"Glaister J, Wong A, Clausi DA. Segmentation of skin lesions from digital images using joint statistical texture distinctiveness. IEEE transactions on biomedical engineering. 2014 Jan 2;61(4):1220-30.","journal-title":"IEEE transactions on biomedical engineering."},{"key":"632_CR33","doi-asserted-by":"crossref","unstructured":"Kaya S, Bayraktar M, Kockara S, Mete M, Halic T, Field HE, Wong HK. Abrupt skin lesion border cutoff measurement for malignancy detection in dermoscopy images. InBMC bioinformatics 2016 Oct 1 (Vol. 17, No. 13, p. 367). BioMed Central.","DOI":"10.1186\/s12859-016-1221-4"},{"key":"632_CR34","doi-asserted-by":"crossref","unstructured":"Haroon M, Gallaghar P, Ahmad M, FitzGerald O. Elevated CRP even at the first visit to a rheumatologist is associated with long-term poor outcomes in patients with psoriatic arthritis. Clinical Rheumatology. 2020.","DOI":"10.1007\/s10067-020-05065-9"},{"issue":"178","key":"632_CR35","doi-asserted-by":"publisher","first-page":"201","DOI":"10.1016\/j.cmpb.2019.06.018","volume":"1","author":"S Chatterjee","year":"2019","unstructured":"Chatterjee S, Dey D, Munshi S. Integration of morphological preprocessing and fractal-based feature extraction with recursive feature elimination for skin lesion types classification. Computer methods and programs in biomedicine. 2019 Sep 1; 178:201-18.","journal-title":"Computer Methods and Programs in Biomedicine."},{"key":"632_CR36","doi-asserted-by":"crossref","unstructured":"Birkenfeld JS, Tucker-Schwartz JM, Soenksen LR, Avil\u00e9s-Izquierdo JA, Marti-Fuster B. Computer-aided classification of suspicious pigmented lesions using wide-field images. Computer Methods and Programs in Biomedicine. 2020;195:105631.","DOI":"10.1016\/j.cmpb.2020.105631"},{"key":"632_CR37","doi-asserted-by":"crossref","unstructured":"Balaji, V. R., S. T. Suganthi, R. Rajadevi, V. Krishna Kumar, B. Saravana Balaji, and Sanjeevi Pandiyan. (2020) Skin disease detection and segmentation using dynamic graph cut algorithm and classification through Naive Bayes Classifier. Measurement pp.107922","DOI":"10.1016\/j.measurement.2020.107922"},{"key":"632_CR38","doi-asserted-by":"crossref","unstructured":"Al-Masni, M. A., Kim, D. H., & Kim, T. S. (2020). Multiple skin lesions diagnostics via integrated deep convolutional networks for segmentation and classification. Computer Methods and Programs in Biomedicine, 190, 105351","DOI":"10.1016\/j.cmpb.2020.105351"},{"key":"632_CR39","doi-asserted-by":"crossref","unstructured":"Chatterjee, Saptarshi, Debangshu Dey, Sugata Munshi, and Surajit Gorai. (2019) Extraction of features from cross-correlation in space and frequency domains for classification of skin lesions. Biomedical Signal Processing and Control 53, 101581","DOI":"10.1016\/j.bspc.2019.101581"},{"key":"632_CR40","doi-asserted-by":"crossref","unstructured":"Qin, Zhiwei, Zhao Liu, Ping Zhu, and Yongbo Xue. (2020) A GAN-based image synthesis method for skin lesion classification. Computer Methods and Programs in Biomedicine, pp.105568","DOI":"10.1016\/j.cmpb.2020.105568"},{"key":"632_CR41","doi-asserted-by":"crossref","unstructured":"Tschandl P, Rosendahl C, Kittler H. The HAM10000 dataset, a large collection of multi-source dermatoscopic images of common pigmented skin lesions. Scientific data. 2018 Aug 14; 5:180161","DOI":"10.1038\/sdata.2018.161"},{"key":"632_CR42","doi-asserted-by":"crossref","unstructured":"Manohar N, Kumar YS, Rani R, Kumar GH. Convolutional Neural Network with SVM for Classification of Animal Images. In Emerging Research in Electronics, Computer Science and Technology 2019 (pp. 527\u2013537). Springer, Singapore","DOI":"10.1007\/978-981-13-5802-9_48"},{"key":"632_CR43","unstructured":"Agarap AF. An architecture combining convolutional neural network (CNN) and support vector machine (SVM) for image classification. arXiv preprint\u00a0arXiv:1712.03541.\u00a02017 Dec 10."},{"key":"632_CR44","doi-asserted-by":"crossref","unstructured":"Codella NC, Gutman D, Celebi ME, Helba B, Marchetti MA, Dusza SW, Kalloo A, Liopyris K, Mishra N, Kittler H, Halpern A. Skin lesion analysis toward melanoma detection: A challenge at the 2017 international symposium on biomedical imaging (isbi), hosted by the international skin imaging collaboration (ISIC). In\u00a02018 IEEE 15th International Symposium on Biomedical Imaging (ISBI 2018) 2018 Apr 4 (pp. 168\u2013172). IEEE.","DOI":"10.1109\/ISBI.2018.8363547"},{"key":"632_CR45","unstructured":"Milton MA. Automated skin lesion classification using ensemble of deep neural networks in isic 2018: Skin lesion analysis towards melanoma detection challenge. arXiv preprint\u00a0arXiv:1901.10802.\u00a02019 Jan 30."},{"key":"632_CR46","doi-asserted-by":"crossref","unstructured":"Cohen JF, Korevaar DA, Altman DG, Bruns DE, Gatsonis CA, Hooft L, Irwig L, Levine D, Reitsma JB, de Vet HCW, Bossuyt PMM. STARD 2015 guidelines for reporting diagnostic accuracy studies: explanation and elaboration. BMJ Open 2016;6: e012799. http:\/\/bmjopen.bmj.com\/content\/6\/11\/e012799.abstract","DOI":"10.1136\/bmjopen-2016-012799"},{"key":"632_CR47","doi-asserted-by":"crossref","unstructured":"Oliveira, R. B., Marranghello, N., Pereira, A. S., & Tavares, J. M. R. (2016). A computational approach for detecting pigmented skin lesions in macroscopic images. Expert Systems with Applications, 61, 53-63.","DOI":"10.1016\/j.eswa.2016.05.017"},{"key":"632_CR48","doi-asserted-by":"crossref","unstructured":"Kasmi, R., & Mokrani, K. (2016). Classification of malignant melanoma and benign skin lesions: implementation of automatic ABCD rule. IET Image Processing, 10(6), 448-455.","DOI":"10.1049\/iet-ipr.2015.0385"},{"key":"632_CR49","doi-asserted-by":"crossref","unstructured":"Rastgoo, M., Garcia, R., Morel, O., & Marzani, F. (2015). Automatic differentiation of melanoma from dysplastic nevi. Computerized Medical Imaging and Graphics, 43, 44-52.","DOI":"10.1016\/j.compmedimag.2015.02.011"},{"key":"632_CR50","doi-asserted-by":"crossref","unstructured":"Shimizu, K., Iyatomi, H., Celebi, M. E., Norton, K. A., & Tanaka, M. (2014). Four-class classification of skin lesions with task decomposition strategy. IEEE transactions on biomedical engineering, 62(1), 274-283.","DOI":"10.1109\/TBME.2014.2348323"},{"key":"632_CR51","doi-asserted-by":"crossref","unstructured":"Gonzalez-Diaz, I. (2018). Dermaknet: Incorporating the knowledge of dermatologists to convolutional neural networks for skin lesion diagnosis. IEEE journal of biomedical and health informatics, 23(2), 547-559.","DOI":"10.1109\/JBHI.2018.2806962"}],"container-title":["Journal of Digital Imaging"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s10278-022-00632-9.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/article\/10.1007\/s10278-022-00632-9\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s10278-022-00632-9.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2022,10,20]],"date-time":"2022-10-20T05:17:07Z","timestamp":1666243027000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/s10278-022-00632-9"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2022,5,6]]},"references-count":51,"journal-issue":{"issue":"5","published-print":{"date-parts":[[2022,10]]}},"alternative-id":["632"],"URL":"https:\/\/doi.org\/10.1007\/s10278-022-00632-9","relation":{},"ISSN":["0897-1889","1618-727X"],"issn-type":[{"value":"0897-1889","type":"print"},{"value":"1618-727X","type":"electronic"}],"subject":[],"published":{"date-parts":[[2022,5,6]]},"assertion":[{"value":"28 January 2021","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"9 February 2022","order":2,"name":"revised","label":"Revised","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"6 April 2022","order":3,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"6 May 2022","order":4,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}},{"order":1,"name":"Ethics","group":{"name":"EthicsHeading","label":"Declarations"}},{"value":"This article does not contain any studies with human participants or animals performed by any authors.","order":2,"name":"Ethics","group":{"name":"EthicsHeading","label":"Ethical Approval"}},{"value":"The authors declare that they have no conflict of interest.","order":3,"name":"Ethics","group":{"name":"EthicsHeading","label":"Conflict of Interest"}}]}}