{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,25]],"date-time":"2026-03-25T22:14:49Z","timestamp":1774476889627,"version":"3.50.1"},"reference-count":79,"publisher":"Elsevier BV","license":[{"start":{"date-parts":[[2023,4,1]],"date-time":"2023-04-01T00:00:00Z","timestamp":1680307200000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.elsevier.com\/tdm\/userlicense\/1.0\/"},{"start":{"date-parts":[[2023,4,1]],"date-time":"2023-04-01T00:00:00Z","timestamp":1680307200000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.elsevier.com\/legal\/tdmrep-license"},{"start":{"date-parts":[[2023,4,1]],"date-time":"2023-04-01T00:00:00Z","timestamp":1680307200000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-017"},{"start":{"date-parts":[[2023,4,1]],"date-time":"2023-04-01T00:00:00Z","timestamp":1680307200000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-037"},{"start":{"date-parts":[[2023,4,1]],"date-time":"2023-04-01T00:00:00Z","timestamp":1680307200000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-012"},{"start":{"date-parts":[[2023,4,1]],"date-time":"2023-04-01T00:00:00Z","timestamp":1680307200000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2023,4,1]],"date-time":"2023-04-01T00:00:00Z","timestamp":1680307200000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-004"}],"content-domain":{"domain":["clinicalkey.com","clinicalkey.com.au","clinicalkey.es","clinicalkey.fr","clinicalkey.jp","elsevier.com","sciencedirect.com"],"crossmark-restriction":true},"short-container-title":["Computer Methods and Programs in Biomedicine"],"published-print":{"date-parts":[[2023,4]]},"DOI":"10.1016\/j.cmpb.2023.107451","type":"journal-article","created":{"date-parts":[[2023,3,2]],"date-time":"2023-03-02T11:34:04Z","timestamp":1677756844000},"page":"107451","update-policy":"https:\/\/doi.org\/10.1016\/elsevier_cm_policy","source":"Crossref","is-referenced-by-count":17,"special_numbering":"C","title":["Monitoring of Pigmented Skin Lesions Using 3D Whole Body Imaging"],"prefix":"10.1016","volume":"232","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-1598-4930","authenticated-orcid":false,"given":"David","family":"Ahmedt-Aristizabal","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Chuong","family":"Nguyen","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Lachlan","family":"Tychsen-Smith","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Ashley","family":"Stacey","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-5516-9394","authenticated-orcid":false,"given":"Shenghong","family":"Li","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-3237-5873","authenticated-orcid":false,"given":"Joseph","family":"Pathikulangara","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-0103-1904","authenticated-orcid":false,"given":"Lars","family":"Petersson","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Dadong","family":"Wang","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"78","reference":[{"issue":"3","key":"10.1016\/j.cmpb.2023.107451_bib0001","first-page":"669","article-title":"Dermoscopy compared with naked eye examination for the diagnosis of primary melanoma: a meta-analysis of studies performed in a clinical setting","volume":"159","author":"Vestergaard","year":"2008","journal-title":"Br. J. Dermatol."},{"issue":"3","key":"10.1016\/j.cmpb.2023.107451_bib0002","doi-asserted-by":"crossref","first-page":"1096","DOI":"10.1109\/JBHI.2018.2845939","article-title":"A survey of feature extraction in dermoscopy image analysis of skin cancer","volume":"23","author":"Barata","year":"2018","journal-title":"IEEE J. Biomed. Health Inform."},{"issue":"1","key":"10.1016\/j.cmpb.2023.107451_bib0003","first-page":"1","article-title":"A patient-centric dataset of images and metadata for identifying melanomas using clinical context","volume":"8","author":"Rotemberg","year":"2021","journal-title":"Sci. Data"},{"issue":"1","key":"10.1016\/j.cmpb.2023.107451_bib0004","doi-asserted-by":"crossref","first-page":"155","DOI":"10.1111\/bjd.17189","article-title":"Diagnostic accuracy of content-based dermatoscopic image retrieval with deep classification features","volume":"181","author":"Tschandl","year":"2019","journal-title":"Br. J. Dermatol."},{"issue":"1","key":"10.1016\/j.cmpb.2023.107451_bib0005","doi-asserted-by":"crossref","first-page":"e13376","DOI":"10.2196\/13376","article-title":"Development of smartphone apps for skin cancer risk assessment: progress and promise","volume":"2","author":"de Carvalho","year":"2019","journal-title":"JMIR Dermatol."},{"key":"10.1016\/j.cmpb.2023.107451_bib0006","doi-asserted-by":"crossref","first-page":"105631","DOI":"10.1016\/j.cmpb.2020.105631","article-title":"Computer-aided classification of suspicious pigmented lesions using wide-field images","volume":"195","author":"Birkenfeld","year":"2020","journal-title":"Comput. Methods Programs Biomed."},{"issue":"1","key":"10.1016\/j.cmpb.2023.107451_bib0007","doi-asserted-by":"crossref","first-page":"135","DOI":"10.1016\/j.jaad.2016.02.1152","article-title":"Reduction in nevus biopsies in patients monitored by total body photography","volume":"75","author":"Truong","year":"2016","journal-title":"J. Am. Acad. Dermatol."},{"issue":"581","key":"10.1016\/j.cmpb.2023.107451_bib0008","doi-asserted-by":"crossref","DOI":"10.1126\/scitranslmed.abb3652","article-title":"Using deep learning for dermatologist-level detection of suspicious pigmented skin lesions from wide-field images","volume":"13","author":"Soenksen","year":"2021","journal-title":"Sci Transl Med"},{"key":"10.1016\/j.cmpb.2023.107451_bib0009","series-title":"Proc. IEEE Conf. Comput. Vis. Pattern Recognit.","first-page":"1829","article-title":"Can self-training identify suspicious ugly duckling lesions?","author":"Mohseni","year":"2021"},{"key":"10.1016\/j.cmpb.2023.107451_bib0010","unstructured":"Dermengine, Dermengine total body photography, 2021, (https:\/\/www.dermengine.com\/en-ca\/total-body-photography)."},{"issue":"2","key":"10.1016\/j.cmpb.2023.107451_bib0011","doi-asserted-by":"crossref","first-page":"586","DOI":"10.1109\/JBHI.2018.2855409","article-title":"An improved skin lesion matching scheme in total body photography","volume":"23","author":"Korotkov","year":"2018","journal-title":"IEEE J. Biomed. Health. Inform."},{"issue":"19","key":"10.1016\/j.cmpb.2023.107451_bib0012","doi-asserted-by":"crossref","first-page":"6639","DOI":"10.3390\/s21196639","article-title":"Skin lesion detection algorithms in whole body images","volume":"21","author":"Strzelecki","year":"2021","journal-title":"Sensors"},{"key":"10.1016\/j.cmpb.2023.107451_bib0013","doi-asserted-by":"crossref","first-page":"152","DOI":"10.3389\/fmed.2018.00152","article-title":"Clinical perspective of 3D total body photography for early detection and screening of melanoma","volume":"5","author":"Rayner","year":"2018","journal-title":"Front. Med."},{"issue":"7","key":"10.1016\/j.cmpb.2023.107451_bib0014","doi-asserted-by":"crossref","first-page":"28","DOI":"10.1109\/MC.2007.225","article-title":"3d body scanning and healthcare applications","volume":"40","author":"Treleaven","year":"2007","journal-title":"Computer"},{"key":"10.1016\/j.cmpb.2023.107451_bib0015","series-title":"Proc. Int. Conf. Med. Image Comput. Comput. Assist. Interv.","first-page":"593","article-title":"Automated detection of new or evolving melanocytic lesions using a 3d body model","author":"Bogo","year":"2014"},{"key":"10.1016\/j.cmpb.2023.107451_bib0016","first-page":"1","article-title":"The additive value of 3d total body imaging for sequential monitoring of skin lesions: a case series","author":"Grochulska","year":"2021","journal-title":"Dermatol."},{"key":"10.1016\/j.cmpb.2023.107451_bib0017","first-page":"1","article-title":"Describing the skin surface ecosystem using 3d total body photography","author":"Janda","year":"2021","journal-title":"Dermatol."},{"key":"10.1016\/j.cmpb.2023.107451_bib0018","article-title":"Detection and longitudinal tracking of pigmented skin lesions in 3d total-body skin textured meshes","author":"Zhao","year":"2021","journal-title":"arXiv preprint arXiv:2105.00374"},{"key":"10.1016\/j.cmpb.2023.107451_bib0019","series-title":"Photogr. Clin. Med.","first-page":"253","article-title":"Total body photography as an aid for the early detection of skin cancer","author":"Navarrete-Dechent","year":"2020"},{"key":"10.1016\/j.cmpb.2023.107451_bib0020","first-page":"1","article-title":"Reproducible naevus counts using 3d total body photography and convolutional neural networks","author":"Betz-Stablein","year":"2021","journal-title":"Dermatol."},{"issue":"11","key":"10.1016\/j.cmpb.2023.107451_bib0021","doi-asserted-by":"crossref","first-page":"e032969","DOI":"10.1136\/bmjopen-2019-032969","article-title":"Evaluation of the efficacy of 3d total-body photography with sequential digital dermoscopy in a high-risk melanoma cohort: protocol for a randomised controlled trial","volume":"9","author":"Primiero","year":"2019","journal-title":"BMJ open"},{"key":"10.1016\/j.cmpb.2023.107451_bib0022","unstructured":"Canfield Scientific Imaging Systems, Canfield 3D Vectra system, 2021, (https:\/\/www.canfieldsci.com\/imaging-systems\/vectra-wb360-imaging-system\/)."},{"key":"10.1016\/j.cmpb.2023.107451_bib0023","series-title":"Proc. Int. Conf. 3D Vis.","first-page":"495","article-title":"3dbodytex: Textured 3d body dataset","author":"Saint","year":"2018"},{"key":"10.1016\/j.cmpb.2023.107451_bib0024","unstructured":"Artec3D, Artec shapify booth, 2022, (https:\/\/www.artec3d.com\/portable-3d-scanners\/shapifybooth)."},{"issue":"4","key":"10.1016\/j.cmpb.2023.107451_bib0025","doi-asserted-by":"crossref","first-page":"509","DOI":"10.1001\/archderm.144.4.509","article-title":"Time required for a complete skin examination with and without dermoscopy: a prospective, randomized multicenter study","volume":"144","author":"Zalaudek","year":"2008","journal-title":"Arch. Dermatol."},{"issue":"5","key":"10.1016\/j.cmpb.2023.107451_bib0026","doi-asserted-by":"crossref","first-page":"886","DOI":"10.1016\/j.jaad.2009.03.024","article-title":"Estimating the time required for a complete skin examination","volume":"62","author":"Hantirah","year":"2010","journal-title":"J. Am. Acad. Dermatol."},{"issue":"4","key":"10.1016\/j.cmpb.2023.107451_bib0027","doi-asserted-by":"crossref","first-page":"653","DOI":"10.1016\/j.jaad.2017.05.040","article-title":"Recommendations for improving the patient experience in specialty encounters","volume":"78","author":"Golda","year":"2018","journal-title":"J. Am. Acad. Dermatol."},{"key":"10.1016\/j.cmpb.2023.107451_bib0028","unstructured":"DigiCamControl, DigiCamControl, 2021, (http:\/\/digicamcontrol.com\/)."},{"key":"10.1016\/j.cmpb.2023.107451_bib0029","unstructured":"Renderpeople, Bundle swimwear rigged 002, 2020, (https:\/\/renderpeople.com\/3d-people\/bundle-swimwear-rigged-002\/)."},{"key":"10.1016\/j.cmpb.2023.107451_bib0030","series-title":"Proc. Int. Conf. Image Process.","first-page":"484","article-title":"Bodyfitr: Robust automatic 3d human body fitting","author":"Saint","year":"2019"},{"key":"10.1016\/j.cmpb.2023.107451_bib0031","unstructured":"M. Mat, Pyrender, 2021, (https:\/\/pypi.org\/project\/pyrender\/)."},{"key":"10.1016\/j.cmpb.2023.107451_sbref0026","series-title":"Blender-a 3D modelling and rendering package","author":"Community","year":"2020"},{"key":"10.1016\/j.cmpb.2023.107451_bib0033","article-title":"Skin lesion analysis: A state-of-the-art survey, systematic review, and future trends","author":"Hasan","year":"2022","journal-title":"arXiv preprint arXiv:2208.12232"},{"issue":"22","key":"10.1016\/j.cmpb.2023.107451_bib0034","doi-asserted-by":"crossref","first-page":"2771","DOI":"10.1001\/jama.292.22.2771","article-title":"Early diagnosis of cutaneous melanoma: revisiting the abcd criteria","volume":"292","author":"Abbasi","year":"2004","journal-title":"Jama"},{"issue":"1","key":"10.1016\/j.cmpb.2023.107451_bib0035","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1038\/s41598-021-87064-7","article-title":"Predicting the clinical management of skin lesions using deep learning","volume":"11","author":"Abhishek","year":"2021","journal-title":"Sci. Rep."},{"key":"10.1016\/j.cmpb.2023.107451_bib0036","article-title":"Siim-isic 2020 challenge dataset","author":"Collaboration","year":"2020","journal-title":"International Skin Imaging Collaboration"},{"key":"10.1016\/j.cmpb.2023.107451_bib0037","series-title":"Color Med. Image Anal.","first-page":"63","article-title":"A color and texture based hierarchical k-nn approach to the classification of non-melanoma skin lesions","author":"Ballerini","year":"2013"},{"issue":"19","key":"10.1016\/j.cmpb.2023.107451_bib0038","doi-asserted-by":"crossref","first-page":"6578","DOI":"10.1016\/j.eswa.2015.04.034","article-title":"Med-node: A computer-assisted melanoma diagnosis system using non-dermoscopic images","volume":"42","author":"Giotis","year":"2015","journal-title":"Expert Syst. Appl."},{"key":"10.1016\/j.cmpb.2023.107451_bib0039","series-title":"Proc. Eur. Conf. Comput. Vis.","first-page":"206","article-title":"A benchmark for automatic visual classification of clinical skin disease images","author":"Sun","year":"2016"},{"issue":"8","key":"10.1016\/j.cmpb.2023.107451_bib0040","doi-asserted-by":"crossref","first-page":"2832","DOI":"10.1109\/TNNLS.2019.2917524","article-title":"Self-paced balance learning for clinical skin disease recognition","volume":"31","author":"Yang","year":"2019","journal-title":"IEEE Trans Neural Netw Learn Syst"},{"key":"10.1016\/j.cmpb.2023.107451_bib0041","doi-asserted-by":"crossref","first-page":"106221","DOI":"10.1016\/j.dib.2020.106221","article-title":"Pad-ufes-20: a skin lesion dataset composed of patient data and clinical images collected from smartphones","volume":"32","author":"Pacheco","year":"2020","journal-title":"Data Brief"},{"key":"10.1016\/j.cmpb.2023.107451_bib0042","series-title":"Proc. IEEE Conf. Comput. Vis. Pattern Recognit.","first-page":"1820","article-title":"Evaluating deep neural networks trained on clinical images in dermatology with the fitzpatrick 17k dataset","author":"Groh","year":"2021"},{"key":"10.1016\/j.cmpb.2023.107451_bib0043","unstructured":"J.A. AlKattash, Dermaamin, 2021, (https:\/\/www.dermaamin.com\/site\/)."},{"key":"10.1016\/j.cmpb.2023.107451_bib0044","unstructured":"S.F. da Silva, Atlas dermatologico, 2021, (http:\/\/atlasdermatologico.com.br\/)."},{"key":"10.1016\/j.cmpb.2023.107451_bib0045","unstructured":"D.N.Z. Trust, Dermnet, 2021, (https:\/\/dermnetnz.org\/)."},{"key":"10.1016\/j.cmpb.2023.107451_bib0046","series-title":"Proc. IEEE Conf. Comput. Vis. Pattern Recognit.","first-page":"1847","article-title":"Gan-based data augmentation and anonymization for skin-lesion analysis: A critical review","author":"Bissoto","year":"2021"},{"key":"10.1016\/j.cmpb.2023.107451_bib0047","series-title":"Proc. IEEE Conf. Comput. Vis. Pattern Recognit.","first-page":"1125","article-title":"Image-to-image translation with conditional adversarial networks","author":"Isola","year":"2017"},{"key":"10.1016\/j.cmpb.2023.107451_bib0048","unstructured":"B. Sekachev, N. Manovich, M. Zhiltsov, A. Zhavoronkov, D. Kalinin, B. Hoff, TOsmanov, D. Kruchinin, A. Zankevich, DmitriySidnev, M. Markelov, Johannes222, M. Chenuet, a andre, telenachos, A. Melnikov, J. Kim, L. Ilouz, N. Glazov, Priya4607, R. Tehrani, S. Jeong, V. Skubriev, S. Yonekura, vugia truong, zliang7, lizhming, T. Truong, opencv\/cvat: v1.1.0, 202010.5281\/zenodo.4009388"},{"key":"10.1016\/j.cmpb.2023.107451_bib0049","unstructured":"AliceVision, Meshroom: A 3D reconstruction software., 2018, (https:\/\/github.com\/alicevision\/meshroom)."},{"key":"10.1016\/j.cmpb.2023.107451_bib0050","series-title":"Proc. ACM Multimed. Syst. Conf.","first-page":"241","article-title":"Alicevision meshroom: An open-source 3d reconstruction pipeline","author":"Griwodz","year":"2021"},{"key":"10.1016\/j.cmpb.2023.107451_bib0051","unstructured":"RealityCapture, Realitycapture: Mapping and 3d modelling photogrammetry, 2021, (https:\/\/www.capturingreality.com\/)."},{"key":"10.1016\/j.cmpb.2023.107451_bib0052","series-title":"Proc. IEEE Conf. Comput. Vis. Pattern Recognit.","first-page":"248","article-title":"Imagenet: A large-scale hierarchical image database","author":"Deng","year":"2009"},{"key":"10.1016\/j.cmpb.2023.107451_bib0053","series-title":"Proc. Eur. Conf. Comput. Vis.","first-page":"740","article-title":"Microsoft coco: Common objects in context","author":"Lin","year":"2014"},{"key":"10.1016\/j.cmpb.2023.107451_bib0054","article-title":"A survey on deep learning for skin lesion segmentation","author":"Mirikharaji","year":"2022","journal-title":"arXiv preprint arXiv:2206.00356"},{"issue":"2","key":"10.1016\/j.cmpb.2023.107451_bib0055","doi-asserted-by":"crossref","first-page":"261","DOI":"10.1007\/s11263-019-01247-4","article-title":"Deep learning for generic object detection: A survey","volume":"128","author":"Liu","year":"2020","journal-title":"Int. J Comput Vis"},{"key":"10.1016\/j.cmpb.2023.107451_bib0056","doi-asserted-by":"crossref","first-page":"100301","DOI":"10.1016\/j.cosrev.2020.100301","article-title":"A comprehensive and systematic look up into deep learning based object detection techniques: A review","volume":"38","author":"Sharma","year":"2020","journal-title":"Comput. Sci. Rev."},{"key":"10.1016\/j.cmpb.2023.107451_bib0057","article-title":"Yolov4: Optimal speed and accuracy of object detection","author":"Bochkovskiy","year":"2020","journal-title":"arXiv preprint arXiv:2004.10934"},{"key":"10.1016\/j.cmpb.2023.107451_bib0058","series-title":"Proc. IEEE Conf. Comput. Vis. Pattern Recognit.","first-page":"13029","article-title":"Scaled-yolov4: Scaling cross stage partial network","author":"Wang","year":"2021"},{"key":"10.1016\/j.cmpb.2023.107451_bib0059","series-title":"Proc. IEEE Conf. Comput. Vis. Pattern Recognit.","first-page":"779","article-title":"You only look once: Unified, real-time object detection","author":"Redmon","year":"2016"},{"key":"10.1016\/j.cmpb.2023.107451_bib0060","unstructured":"AlexeyAB, Darknet: Open source neural networks in c, 2021, (https:\/\/github.com\/AlexeyAB\/darknet)."},{"key":"10.1016\/j.cmpb.2023.107451_bib0061","article-title":"Yolov3: An incremental improvement","author":"Redmon","year":"2018","journal-title":"arXiv preprint arXiv:1804.02767"},{"key":"10.1016\/j.cmpb.2023.107451_bib0062","article-title":"Cspnet: A new backbone that can enhance learning capability of cnn","author":"Wang","year":"2019","journal-title":"arXiv preprint arXiv:1911.11929"},{"issue":"9","key":"10.1016\/j.cmpb.2023.107451_bib0063","doi-asserted-by":"crossref","first-page":"1904","DOI":"10.1109\/TPAMI.2015.2389824","article-title":"Spatial pyramid pooling in deep convolutional networks for visual recognition","volume":"37","author":"He","year":"2015","journal-title":"IEEE Trans. Pattern Anal. Mach. Intell."},{"key":"10.1016\/j.cmpb.2023.107451_bib0064","series-title":"Proc. IEEE Conf. Comput. Vis. Pattern Recognit.","first-page":"8759","article-title":"Path aggregation network for instance segmentation","author":"Liu","year":"2018"},{"key":"10.1016\/j.cmpb.2023.107451_bib0065","series-title":"Proc. Conf. AAAI Artif. Intell.","first-page":"12993","article-title":"Distance-iou loss: Faster and better learning for bounding box regression","volume":"volume\u00a034","author":"Zheng","year":"2020"},{"key":"10.1016\/j.cmpb.2023.107451_bib0066","series-title":"Proc. Int. Conf. Comput. Vis.","first-page":"5561","article-title":"Soft-nms\u2013improving object detection with one line of code","author":"Bodla","year":"2017"},{"key":"10.1016\/j.cmpb.2023.107451_bib0067","first-page":"2825","article-title":"Scikit-learn: Machine learning in Python","volume":"12","author":"Pedregosa","year":"2011","journal-title":"J. Mach. Learn. Res."},{"key":"10.1016\/j.cmpb.2023.107451_bib0068","doi-asserted-by":"crossref","first-page":"84","DOI":"10.1016\/j.media.2015.03.001","article-title":"Skin lesion tracking using structured graphical models","volume":"27","author":"Mirzaalian","year":"2016","journal-title":"Med. Image Anal."},{"key":"10.1016\/j.cmpb.2023.107451_bib0069","series-title":"Proc. Adv. Neural Inf. Process. Syst.","article-title":"Learning elementary structures for 3d shape generation and matching","volume":"volume\u00a032","author":"Deprelle","year":"2019"},{"key":"10.1016\/j.cmpb.2023.107451_bib0070","series-title":"Proc. Adv. Neural Inf. Process. Syst.","first-page":"12909","article-title":"Loopreg: Self-supervised learning of implicit surface correspondences, pose and shape for 3d human mesh registration","volume":"volume\u00a033","author":"Bhatnagar","year":"2020"},{"key":"10.1016\/j.cmpb.2023.107451_bib0071","series-title":"Proc. IEEE Conf. Comput. Vis. Pattern Recognit.","first-page":"3794","article-title":"Faust: Dataset and evaluation for 3d mesh registration","author":"Bogo","year":"2014"},{"issue":"6","key":"10.1016\/j.cmpb.2023.107451_bib0072","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1145\/2816795.2818013","article-title":"Smpl: A skinned multi-person linear model","volume":"34","author":"Loper","year":"2015","journal-title":"ACM Trans. Graph."},{"key":"10.1016\/j.cmpb.2023.107451_bib0073","series-title":"Proc. Eur. Conf. Comput. Vis.","first-page":"230","article-title":"3d-coded: 3d correspondences by deep deformation","author":"Groueix","year":"2018"},{"key":"10.1016\/j.cmpb.2023.107451_bib0074","article-title":"A survey of algorithms for geodesic paths and distances","author":"Crane","year":"2020","journal-title":"arXiv preprint arXiv:2007.10430"},{"key":"10.1016\/j.cmpb.2023.107451_bib0075","series-title":"Proc. Eurograph. Ital. Chapter Conf.","first-page":"129","article-title":"Meshlab: an open-source mesh processing tool","volume":"volume 2008","author":"Cignoni","year":"2008"},{"issue":"2","key":"10.1016\/j.cmpb.2023.107451_bib0076","doi-asserted-by":"crossref","first-page":"e37034","DOI":"10.2196\/37034","article-title":"The experience of 3d total-body photography to monitor nevi: Results from an australian general population-based cohort study","volume":"5","author":"Horsham","year":"2022","journal-title":"JMIR Dermatol."},{"issue":"10","key":"10.1016\/j.cmpb.2023.107451_bib0077","doi-asserted-by":"crossref","first-page":"5479","DOI":"10.3390\/ijerph18105479","article-title":"Skin cancer detection: a review using deep learning techniques","volume":"18","author":"Dildar","year":"2021","journal-title":"International journal of environmental research and public health"},{"issue":"9","key":"10.1016\/j.cmpb.2023.107451_bib0078","doi-asserted-by":"crossref","first-page":"e025857","DOI":"10.1136\/bmjopen-2018-025857","article-title":"\u2018mind your moles\u2019 study: protocol of a prospective cohort study of melanocytic naevi","volume":"8","author":"Koh","year":"2018","journal-title":"BMJ Open"},{"key":"10.1016\/j.cmpb.2023.107451_bib0079","unstructured":"NCCN, (NCCN), Nccn clinical practice guidelines in oncology. cutaneous melanoma. version 3.2021., 2022, (https:\/\/www.nccn.org\/professionals\/physician_gls\/pdf\/melanoma_blocks.pdf)."}],"container-title":["Computer Methods and Programs in Biomedicine"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/api.elsevier.com\/content\/article\/PII:S0169260723001177?httpAccept=text\/xml","content-type":"text\/xml","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/api.elsevier.com\/content\/article\/PII:S0169260723001177?httpAccept=text\/plain","content-type":"text\/plain","content-version":"vor","intended-application":"text-mining"}],"deposited":{"date-parts":[[2025,9,30]],"date-time":"2025-09-30T04:17:28Z","timestamp":1759205848000},"score":1,"resource":{"primary":{"URL":"https:\/\/linkinghub.elsevier.com\/retrieve\/pii\/S0169260723001177"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2023,4]]},"references-count":79,"alternative-id":["S0169260723001177"],"URL":"https:\/\/doi.org\/10.1016\/j.cmpb.2023.107451","relation":{},"ISSN":["0169-2607"],"issn-type":[{"value":"0169-2607","type":"print"}],"subject":[],"published":{"date-parts":[[2023,4]]},"assertion":[{"value":"Elsevier","name":"publisher","label":"This article is maintained by"},{"value":"Monitoring of Pigmented Skin Lesions Using 3D Whole Body Imaging","name":"articletitle","label":"Article Title"},{"value":"Computer Methods and Programs in Biomedicine","name":"journaltitle","label":"Journal Title"},{"value":"https:\/\/doi.org\/10.1016\/j.cmpb.2023.107451","name":"articlelink","label":"CrossRef DOI link to publisher maintained version"},{"value":"article","name":"content_type","label":"Content Type"},{"value":"\u00a9 2023 Elsevier B.V. All rights reserved.","name":"copyright","label":"Copyright"}],"article-number":"107451"}}