{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,8,17]],"date-time":"2026-08-17T17:18:10Z","timestamp":1786987090764,"version":"build-2736575974"},"reference-count":54,"publisher":"Elsevier BV","license":[{"start":{"date-parts":[[2025,6,1]],"date-time":"2025-06-01T00:00:00Z","timestamp":1748736000000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.elsevier.com\/tdm\/userlicense\/1.0\/"},{"start":{"date-parts":[[2025,6,1]],"date-time":"2025-06-01T00:00:00Z","timestamp":1748736000000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.elsevier.com\/legal\/tdmrep-license"},{"start":{"date-parts":[[2025,3,20]],"date-time":"2025-03-20T00:00:00Z","timestamp":1742428800000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/100020098","name":"Innovative Medicines Initiative","doi-asserted-by":"publisher","id":[{"id":"10.13039\/100020098","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100000780","name":"European Commission","doi-asserted-by":"publisher","id":[{"id":"10.13039\/501100000780","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/100013322","name":"European Federation of Pharmaceutical Industries and Associations","doi-asserted-by":"publisher","id":[{"id":"10.13039\/100013322","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100010767","name":"Innovative Medicines Initiative","doi-asserted-by":"publisher","award":["101034427"],"award-info":[{"award-number":["101034427"]}],"id":[{"id":"10.13039\/501100010767","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["clinicalkey.fr","clinicalkey.jp","clinicalkey.es","clinicalkey.com.au","clinicalkey.com","elsevier.com","sciencedirect.com"],"crossmark-restriction":true},"short-container-title":["Computer Methods and Programs in Biomedicine"],"published-print":{"date-parts":[[2025,6]]},"DOI":"10.1016\/j.cmpb.2025.108733","type":"journal-article","created":{"date-parts":[[2025,3,22]],"date-time":"2025-03-22T04:45:19Z","timestamp":1742618719000},"page":"108733","update-policy":"https:\/\/doi.org\/10.1016\/elsevier_cm_policy","source":"Crossref","is-referenced-by-count":10,"special_numbering":"C","title":["A first explainable-AI-based workflow integrating forward-forward and backpropagation-trained networks of label-free multiphoton microscopy images to assess human biopsies of rare neuromuscular disease"],"prefix":"10.1016","volume":"265","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-8889-1124","authenticated-orcid":false,"given":"Riccardo","family":"Scodellaro","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-7062-5319","authenticated-orcid":false,"given":"Jana","family":"Zsch\u00fcntzsch","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Anna-Kathrin","family":"Hell","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Frauke","family":"Alves","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"78","reference":[{"issue":"6","key":"10.1016\/j.cmpb.2025.108733_bib0001","doi-asserted-by":"crossref","first-page":"919","DOI":"10.1016\/0092-8674(87)90579-4","article-title":"Dystrophin: the protein product of the Duchenne muscular dystrophy locus","volume":"51","author":"Hoffman","year":"1987","journal-title":"Cell"},{"key":"10.1016\/j.cmpb.2025.108733_bib0002","doi-asserted-by":"crossref","DOI":"10.3389\/fphys.2023.1183101","article-title":"Duchenne muscular dystrophy: Disease mechanism and therapeutic strategies","volume":"14","author":"Bez Batti Angulski","year":"2023","journal-title":"Front. Physiol."},{"issue":"1","key":"10.1016\/j.cmpb.2025.108733_bib0003","doi-asserted-by":"crossref","first-page":"13","DOI":"10.1038\/s41572-021-00248-3","article-title":"Duchenne muscular dystrophy","volume":"7","author":"Duan","year":"2021","journal-title":"Nat. Rev. Dis. Primers"},{"issue":"10213","key":"10.1016\/j.cmpb.2025.108733_bib0004","doi-asserted-by":"crossref","first-page":"2025","DOI":"10.1016\/S0140-6736(19)32910-1","article-title":"Muscular dystrophies","volume":"394","author":"Mercuri","year":"2019","journal-title":"Lancet"},{"issue":"1","key":"10.1016\/j.cmpb.2025.108733_bib0005","doi-asserted-by":"crossref","first-page":"1","DOI":"10.3233\/JND-160145","article-title":"Skeletal muscle quantitative nuclear magnetic resonance imaging and spectroscopy as an outcome measure for clinical trials","volume":"3","author":"Carlier","year":"2016","journal-title":"J. Neuromuscul. Dis."},{"issue":"1","key":"10.1016\/j.cmpb.2025.108733_bib0006","first-page":"S89","article-title":"Neuromuscular diseases: diagnosis and management","volume":"104","author":"Mary","year":"2018","journal-title":"Orthop. Traumatol."},{"issue":"1","key":"10.1016\/j.cmpb.2025.108733_bib0007","doi-asserted-by":"crossref","first-page":"149","DOI":"10.1002\/mus.26083","article-title":"Dystrophinopathy muscle biopsies in the genetic testing ERA: one center's data","volume":"58","author":"Carlson","year":"2018","journal-title":"Muscle Nerve"},{"issue":"6","key":"10.1016\/j.cmpb.2025.108733_bib0008","doi-asserted-by":"crossref","first-page":"1647","DOI":"10.21873\/invivo.11427","article-title":"Diagnostic accuracy of muscle biopsy and electromyography in 123 patients with neuromuscular disorders","volume":"32","author":"Constantinides","year":"2018","journal-title":"In. Vivo (Brooklyn)"},{"issue":"11","key":"10.1016\/j.cmpb.2025.108733_bib0009","doi-asserted-by":"crossref","first-page":"e693","DOI":"10.1016\/S2589-7500(21)00216-8","article-title":"Evaluation of artificial intelligence on a reference standard based on subjective interpretation","volume":"3","author":"Chen","year":"2021","journal-title":"Lancet Digit. Health"},{"issue":"10","key":"10.1016\/j.cmpb.2025.108733_bib0010","doi-asserted-by":"crossref","first-page":"e1094","DOI":"10.1212\/WNL.0000000000009068","article-title":"Accuracy of a machine learning muscle MRI-based tool for the diagnosis of muscular dystrophies","volume":"94","author":"Verd\u00fa-D\u00edaz","year":"2020","journal-title":"Neurology."},{"issue":"10","key":"10.1016\/j.cmpb.2025.108733_bib0011","doi-asserted-by":"crossref","first-page":"421","DOI":"10.1212\/WNL.0000000000009053","article-title":"Machine learning outperforms human experts in MRI pattern analysis of muscular dystrophies","volume":"94","author":"Morrow","year":"2020","journal-title":"Neurology."},{"key":"10.1016\/j.cmpb.2025.108733_bib0012","first-page":"1","article-title":"Brain alteration patterns in children with duchenne muscular dystrophy: a machine learning approach to magnetic resonance imaging","author":"Peruzzo","year":"2024","journal-title":"J. Neuromuscul. Dis."},{"issue":"12","key":"10.1016\/j.cmpb.2025.108733_bib0013","doi-asserted-by":"crossref","first-page":"1071","DOI":"10.1038\/s42256-021-00420-0","article-title":"Physics-based machine learning for subcellular segmentation in living cells","volume":"3","author":"Sekh","year":"2021","journal-title":"Nat. Mach. Intell."},{"key":"10.1016\/j.cmpb.2025.108733_bib0014","first-page":"221","article-title":"Classification of skin cancer based on fluorescence lifetime imaging and machine learning","volume":"11553","author":"Yang","year":"2020"},{"key":"10.1016\/j.cmpb.2025.108733_bib0015","doi-asserted-by":"crossref","first-page":"34","DOI":"10.1016\/j.csbj.2018.01.001","article-title":"Machine learning methods for histopathological image analysis","volume":"16","author":"Komura","year":"2018","journal-title":"Comput. Struct. Biotechnol. J."},{"issue":"1","key":"10.1016\/j.cmpb.2025.108733_bib0016","doi-asserted-by":"crossref","first-page":"43","DOI":"10.1186\/s40644-023-00559-6","article-title":"Three-dimensional analysis of human pancreatic cancer specimens by phase-contrast based X-ray tomography\u2013the next dimension of diagnosis","volume":"23","author":"Pinkert-Leetsch","year":"2023","journal-title":"Cancer ImAging"},{"issue":"4","key":"10.1016\/j.cmpb.2025.108733_bib0017","doi-asserted-by":"crossref","first-page":"1009","DOI":"10.1007\/s10439-023-03437-1","article-title":"Functional assessment of human articular cartilage using second harmonic generation (SHG) imaging: a feasibility study","volume":"52","author":"Abusara","year":"2024","journal-title":"Ann. Biomed. Eng."},{"issue":"3","key":"10.1016\/j.cmpb.2025.108733_bib0018","article-title":"Discontinuity third harmonic generation microscopy for label-free imaging and quantification of intraepidermal nerve fibers","volume":"4","author":"Wu","year":"2024","journal-title":"Cell Rep. Methods"},{"issue":"12","key":"10.1016\/j.cmpb.2025.108733_bib0019","doi-asserted-by":"crossref","first-page":"2365","DOI":"10.1038\/s41433-024-03165-3","article-title":"Imaging the optic nerve with optical coherence tomography","volume":"38","author":"Shin","year":"2024","journal-title":"Eye"},{"key":"10.1016\/j.cmpb.2025.108733_bib0020","first-page":"1","article-title":"Clinical translation of photoacoustic imaging","author":"Park","year":"2024","journal-title":"Nat. Rev. Bioeng."},{"key":"10.1016\/j.cmpb.2025.108733_bib0021","doi-asserted-by":"crossref","DOI":"10.3389\/fgstr.2023.1283052","article-title":"X-ray phase-contrast 3D virtual histology characterises complex tissue architecture in colorectal cancer","volume":"2","author":"Svetlove","year":"2023","journal-title":"Front. Gastroenterol."},{"issue":"8","key":"10.1016\/j.cmpb.2025.108733_bib0022","doi-asserted-by":"crossref","first-page":"3988","DOI":"10.1364\/BOE.488453","article-title":"Effect of tissue fixation on the optical properties of structural components assessed by non-linear microscopy imaging","volume":"14","author":"Markus","year":"2023","journal-title":"Biomed. Opt. Express."},{"key":"10.1016\/j.cmpb.2025.108733_bib0023","doi-asserted-by":"crossref","first-page":"527","DOI":"10.3389\/fonc.2019.00527","article-title":"Whole-section tumor micro-architecture analysis by a two-dimensional phasor-based approach applied to polarization-dependent second harmonic imaging","volume":"9","author":"Scodellaro","year":"2019","journal-title":"Front. Oncol."},{"key":"10.1016\/j.cmpb.2025.108733_bib0024","first-page":"6","article-title":"Automated detection of corneal edema with deep learning-assisted second harmonic generation microscopy","volume":"29","author":"Anton","year":"2023","journal-title":"IEEE J. Sel. Top. Quantum Electr."},{"issue":"4-5","key":"10.1016\/j.cmpb.2025.108733_bib0025","first-page":"1","article-title":"Collagen micro-architecture investigation in tumor sections by means of second-harmonic generation signal multiphasor analysis coupled with non-supervised machine learning techniques","volume":"44","author":"Scodellaro","year":"2021","journal-title":"Il nuovo cimento C"},{"issue":"3","key":"10.1016\/j.cmpb.2025.108733_bib0026","doi-asserted-by":"crossref","first-page":"1188","DOI":"10.1109\/JBHI.2021.3104002","article-title":"Application of a deep-learning technique to non-linear images from human tissue biopsies for shedding new light on breast cancer diagnosis","volume":"26","author":"Tsafas","year":"2021","journal-title":"IEEe J. Biomed. Health Inform."},{"issue":"1","key":"10.1016\/j.cmpb.2025.108733_bib0027","doi-asserted-by":"crossref","first-page":"11334","DOI":"10.1038\/s41598-022-15423-z","article-title":"Fast intraoperative histology-based diagnosis of gliomas with third harmonic generation microscopy and deep learning","volume":"12","author":"Blokker","year":"2022","journal-title":"Sci. Rep."},{"key":"10.1016\/j.cmpb.2025.108733_bib0028","series-title":"Biomedical Texture Analysis","first-page":"281","article-title":"Analysis of histopathology images: From traditional machine learning to deep learning","author":"Jimenez-del-Toro","year":"2017"},{"issue":"4","key":"10.1016\/j.cmpb.2025.108733_bib0029","doi-asserted-by":"crossref","first-page":"e25759","DOI":"10.2196\/25759","article-title":"Role of artificial intelligence applications in real-life clinical practice: systematic review","volume":"23","author":"Yin","year":"2021","journal-title":"J. Med. Internet. Res."},{"issue":"6088","key":"10.1016\/j.cmpb.2025.108733_bib0030","doi-asserted-by":"crossref","first-page":"533","DOI":"10.1038\/323533a0","article-title":"Learning representations by back-propagating errors","volume":"323","author":"Rumelhart","year":"1986","journal-title":"Nature"},{"key":"10.1016\/j.cmpb.2025.108733_bib0031","doi-asserted-by":"crossref","first-page":"973","DOI":"10.1007\/s11227-020-03321-y","article-title":"A new deep convolutional neural network model for classifying breast cancer histopathological images and the hyperparameter optimisation of the proposed model","volume":"77","author":"Burcak","year":"2021","journal-title":"J. Supercomput."},{"key":"10.1016\/j.cmpb.2025.108733_bib0032","article-title":"Laplacian-guided hierarchical transformer: a network for medical image segmentation","author":"Chen","year":"2024","journal-title":"Comput. Methods Programs Biomed."},{"key":"10.1016\/j.cmpb.2025.108733_bib0033","series-title":"Advances in Neural Information Processing Systems","first-page":"31","article-title":"Which neural net architectures give rise to exploding and vanishing gradients?","author":"Hanin","year":"2018"},{"key":"10.1016\/j.cmpb.2025.108733_bib0034","series-title":"Proceedings of the IEEE-INNS-ENNS International Joint Conference on Neural Networks. IJCNN 2000. Neural Computing: New Challenges and Perspectives for the New Millennium","first-page":"114","article-title":"Overfitting and neural networks: conjugate gradient and backpropagation","volume":"1","author":"Lawrence","year":"2000"},{"issue":"1","key":"10.1016\/j.cmpb.2025.108733_bib0035","doi-asserted-by":"crossref","first-page":"53","DOI":"10.1016\/0893-6080(89)90014-2","article-title":"Neural networks and principal component analysis: learning from examples without local minima","volume":"2","author":"Baldi","year":"1989","journal-title":"Neural Netw."},{"key":"10.1016\/j.cmpb.2025.108733_bib0036","doi-asserted-by":"crossref","first-page":"335","DOI":"10.1038\/s41583-020-0277-3","article-title":"Backpropagation and the brain","volume":"21","author":"Lillicrap","year":"2020","journal-title":"Nat. Rev. Neurosci."},{"key":"10.1016\/j.cmpb.2025.108733_bib0037","unstructured":"Hinton, G. (2022). The forward-forward algorithm: some preliminary investigations. arXiv preprint. arXiv:2212.13345."},{"key":"10.1016\/j.cmpb.2025.108733_bib0038","series-title":"2023 IEEE International Conference on Smart Computing (SMARTCOMP)","first-page":"49","article-title":"\u00b5-ff: On-device forward-forward training algorithm for microcontrollers","author":"De Vita","year":"2023"},{"key":"10.1016\/j.cmpb.2025.108733_bib0039","unstructured":"Scodellaro, R., Kulkarni, A., Alves, F., & Schr\u00f6ter, M. (2023). Training convolutional neural networks with the forward-forward algorithm. arXiv preprint. arXiv:2312.14924."},{"issue":"1","key":"10.1016\/j.cmpb.2025.108733_bib0040","doi-asserted-by":"crossref","first-page":"210","DOI":"10.1038\/s41746-024-01213-6","article-title":"Navigating the European union artificial intelligence act for healthcare","volume":"7","author":"Busch","year":"2024","journal-title":"Digit. Med."},{"key":"10.1016\/j.cmpb.2025.108733_bib0041","series-title":"International Workshop On Extending Explainable AI Beyond Deep Models and Classifiers","first-page":"13","article-title":"Explainable AI methods-a brief overview","author":"Holzinger","year":"2022"},{"issue":"2","key":"10.1016\/j.cmpb.2025.108733_bib0042","doi-asserted-by":"crossref","first-page":"237","DOI":"10.3390\/diagnostics12020237","article-title":"Applications of explainable artificial intelligence in diagnosis and surgery","volume":"12","author":"Zhang","year":"2022","journal-title":"Diagnostics"},{"issue":"1","key":"10.1016\/j.cmpb.2025.108733_bib0043","doi-asserted-by":"crossref","first-page":"310","DOI":"10.1186\/s13023-023-02916-x","article-title":"Rare diseases' genetic newborn screening as the gateway to future genomic medicine: the Screen4Care EU-IMI project","volume":"18","author":"Ferlini","year":"2023","journal-title":"Orphanet. J. Rare Dis."},{"issue":"1","key":"10.1016\/j.cmpb.2025.108733_bib0044","doi-asserted-by":"crossref","first-page":"2125","DOI":"10.1038\/s41467-018-04470-8","article-title":"Intravital imaging by simultaneous label-free autofluorescence-multiharmonic microscopy","volume":"9","author":"You","year":"2018","journal-title":"Nat. Commun."},{"key":"10.1016\/j.cmpb.2025.108733_bib0045","doi-asserted-by":"crossref","first-page":"e622","DOI":"10.7717\/peerj-cs.622","article-title":"Predictive and discriminative localization of pathology using high resolution class activation maps with CNNs","volume":"7","author":"Shinde","year":"2021","journal-title":"PeerJ Comput. Sci."},{"key":"10.1016\/j.cmpb.2025.108733_bib0046","article-title":"Sources: Backpropagation and Forward-Forward algorithms unveil different insights of Duchenne Muscular Dystrophy from human-derived label-free multiphoton microscopy data","author":"Scodellaro","year":"2024","journal-title":"Zenodo"},{"issue":"4","key":"10.1016\/j.cmpb.2025.108733_bib0047","doi-asserted-by":"crossref","DOI":"10.1117\/1.2967536","article-title":"Measurement of muscle disease by quantitative second-harmonic generation imaging","volume":"13","author":"Plotnikov","year":"2008","journal-title":"J. Biomed. Opt."},{"issue":"1","key":"10.1016\/j.cmpb.2025.108733_bib0048","doi-asserted-by":"crossref","first-page":"10","DOI":"10.1186\/s41231-024-00170-2","article-title":"Characterization of lamina propria remodeling in pediatric eosinophilic esophagitis using second harmonic generation microscopy","volume":"9","author":"Haugen","year":"2024","journal-title":"Transl. Med. Commun."},{"issue":"3","key":"10.1016\/j.cmpb.2025.108733_bib0049","doi-asserted-by":"crossref","first-page":"91","DOI":"10.1111\/boc.202100056","article-title":"Label-free 3D characterization of cardiac fibrosis in muscular dystrophy using SHG imaging of cleared tissue","volume":"114","author":"Pichon","year":"2022","journal-title":"Biol. Cell"},{"key":"10.1016\/j.cmpb.2025.108733_bib0050","doi-asserted-by":"crossref","first-page":"e62760","DOI":"10.7554\/eLife.62760","article-title":"Beneficial impacts of neuromuscular electrical stimulation on muscle structure and function in the zebrafish model of Duchenne muscular dystrophy","volume":"11","author":"Kilroy","year":"2022","journal-title":"Elife"},{"issue":"4","key":"10.1016\/j.cmpb.2025.108733_bib0051","doi-asserted-by":"crossref","DOI":"10.1002\/tbio.202000009","article-title":"Compact portable multiphoton microscopy reveals histopathological hallmarks of unprocessed lung tumor tissue in real time","volume":"2","author":"Van Huizen","year":"2020","journal-title":"Transl. Biophotonics."},{"issue":"2","key":"10.1016\/j.cmpb.2025.108733_bib0052","article-title":"Toward next-generation endoscopes integrating biomimetic video systems, nonlinear optical microscopy, and deep learning","volume":"4","author":"Stanciu","year":"2023","journal-title":"Biophys. Rev. (Melville)"},{"issue":"12","key":"10.1016\/j.cmpb.2025.108733_bib0053","article-title":"Roadmap on label-free super-resolution imaging","volume":"17","author":"Astratov","year":"2023","journal-title":"Laser Photonics Rev."},{"key":"10.1016\/j.cmpb.2025.108733_bib0054","doi-asserted-by":"crossref","DOI":"10.1016\/j.ijmedinf.2022.104738","article-title":"Ethical, legal, and social considerations of AI-based medical decision-support tools: a scoping review","volume":"161","author":"\u010cartolovni","year":"2022","journal-title":"Int. J. Med. Inform."}],"container-title":["Computer Methods and Programs in Biomedicine"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/api.elsevier.com\/content\/article\/PII:S0169260725001506?httpAccept=text\/xml","content-type":"text\/xml","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/api.elsevier.com\/content\/article\/PII:S0169260725001506?httpAccept=text\/plain","content-type":"text\/plain","content-version":"vor","intended-application":"text-mining"}],"deposited":{"date-parts":[[2025,5,1]],"date-time":"2025-05-01T04:29:27Z","timestamp":1746073767000},"score":1,"resource":{"primary":{"URL":"https:\/\/linkinghub.elsevier.com\/retrieve\/pii\/S0169260725001506"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025,6]]},"references-count":54,"alternative-id":["S0169260725001506"],"URL":"https:\/\/doi.org\/10.1016\/j.cmpb.2025.108733","relation":{},"ISSN":["0169-2607"],"issn-type":[{"value":"0169-2607","type":"print"}],"subject":[],"published":{"date-parts":[[2025,6]]},"assertion":[{"value":"Elsevier","name":"publisher","label":"This article is maintained by"},{"value":"A first explainable-AI-based workflow integrating forward-forward and backpropagation-trained networks of label-free multiphoton microscopy images to assess human biopsies of rare neuromuscular disease","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.2025.108733","name":"articlelink","label":"CrossRef DOI link to publisher maintained version"},{"value":"article","name":"content_type","label":"Content Type"},{"value":"\u00a9 2025 The Author(s). Published by Elsevier B.V.","name":"copyright","label":"Copyright"}],"article-number":"108733"}}