{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,3,28]],"date-time":"2025-03-28T07:07:25Z","timestamp":1743145645546,"version":"3.40.3"},"publisher-location":"Cham","reference-count":15,"publisher":"Springer Nature Switzerland","isbn-type":[{"type":"print","value":"9783031777851"},{"type":"electronic","value":"9783031777868"}],"license":[{"start":{"date-parts":[[2025,1,1]],"date-time":"2025-01-01T00:00:00Z","timestamp":1735689600000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2025,1,1]],"date-time":"2025-01-01T00:00:00Z","timestamp":1735689600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2025]]},"DOI":"10.1007\/978-3-031-77786-8_21","type":"book-chapter","created":{"date-parts":[[2025,1,16]],"date-time":"2025-01-16T11:08:26Z","timestamp":1737025706000},"page":"210-217","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["Glomeruli Segmentation in\u00a0Whole-Slide Images: Is Better Local Performance Always Better?"],"prefix":"10.1007","author":[{"given":"Maria","family":"S\u00e1nchez","sequence":"first","affiliation":[]},{"given":"Helena","family":"S\u00e1nchez","sequence":"additional","affiliation":[]},{"given":"Carlos P\u00e9rez de","family":"Arenaza","sequence":"additional","affiliation":[]},{"given":"David","family":"Ribalta","sequence":"additional","affiliation":[]},{"given":"Nerea","family":"Arrarte","sequence":"additional","affiliation":[]},{"given":"Oscar","family":"C\u00e1mara","sequence":"additional","affiliation":[]},{"given":"Adrian","family":"Galdran","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2025,1,17]]},"reference":[{"issue":"1","key":"21_CR1","doi-asserted-by":"publisher","first-page":"52","DOI":"10.1681\/ASN.2020050597","volume":"32","author":"N Bouteldja","year":"2021","unstructured":"Bouteldja, N., et al.: Deep learning-based segmentation and quantification in experimental kidney histopathology. J. Am. Soc. Nephrol. 32(1), 52\u201368 (2021)","journal-title":"J. Am. Soc. Nephrol."},{"key":"21_CR2","unstructured":"Cleveland Clinic: Glomerulonephritis (GN). https:\/\/my.clevelandclinic.org\/health\/diseases\/16167-glomerulonephritis-gn. Accessed 01 Jun 2024"},{"key":"21_CR3","unstructured":"Dozat, T.: Incorporating nesterov momentum into Adam. In: Proceedings of the 4th International Conference on Learning Representations, pp.\u00a01\u20134"},{"issue":"1","key":"21_CR4","doi-asserted-by":"publisher","first-page":"014001","DOI":"10.1117\/1.JMI.8.1.014001","volume":"8","author":"A Jha","year":"2021","unstructured":"Jha, A., Yang, H., Deng, R., Kapp, M.E., Fogo, A.B., Huo, Y.: Instance segmentation for whole slide imaging: end-to-end or detect-then-segment. J. Med. Imag. 8(1), 014001\u2013014001 (2021)","journal-title":"J. Med. Imag."},{"issue":"8","key":"21_CR5","doi-asserted-by":"publisher","first-page":"1431","DOI":"10.1016\/j.ajpath.2021.05.004","volume":"191","author":"L Jiang","year":"2021","unstructured":"Jiang, L., et al.: A deep learning-based approach for glomeruli instance segmentation from multistained renal biopsy pathologic images. Am. J. Pathol. 191(8), 1431\u20131441 (2021). https:\/\/doi.org\/10.1016\/j.ajpath.2021.05.004","journal-title":"Am. J. Pathol."},{"key":"21_CR6","doi-asserted-by":"crossref","unstructured":"Kaur, G., et al.: Automatic identification of glomerular in whole-slide images using a modified UNet model. Diagnostics 13(19), 3152 (2023)","DOI":"10.3390\/diagnostics13193152"},{"key":"21_CR7","unstructured":"KPIs2024 - Task: Kpis2024 - task (2024). https:\/\/sites.google.com\/view\/kpis2024\/task?authuser=0. Accessed 01 Jun 2024"},{"key":"21_CR8","doi-asserted-by":"publisher","unstructured":"Leng, H., et al.: An accelerated pipeline for multi-label renal pathology image segmentation at the whole slide image level. In: Medical Imaging 2023: Digital and Computational Pathology. vol. 12471, pp. 174\u2013179. SPIE (2023). https:\/\/doi.org\/10.1117\/12.2653651","DOI":"10.1117\/12.2653651"},{"key":"21_CR9","doi-asserted-by":"crossref","unstructured":"Lin, T.Y., Doll\u00e1r, P., Girshick, R., He, K., Hariharan, B., Belongie, S.: Feature pyramid networks for object detection. In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, pp. 2117\u20132125 (2017)","DOI":"10.1109\/CVPR.2017.106"},{"key":"21_CR10","doi-asserted-by":"publisher","unstructured":"Lutnick, B., et al.: A user-friendly tool for cloud-based whole slide image segmentation with examples from renal histopathology. Commun. Med. 2(1), 1\u201315 (2022). https:\/\/doi.org\/10.1038\/s43856-022-00138-z","DOI":"10.1038\/s43856-022-00138-z"},{"key":"21_CR11","doi-asserted-by":"publisher","unstructured":"Mallamaci, F., Tripepi, G.: Risk factors of chronic kidney disease progression: between old and new concepts. J. Clin. Med. 13(3), 678 (2024). https:\/\/doi.org\/10.3390\/jcm13030678. submission received: 20 December 2023 \/ Revised: 17 January 2024 \/ Accepted: 22 January 2024 \/ Published: 24 January 2024","DOI":"10.3390\/jcm13030678"},{"issue":"2","key":"21_CR12","doi-asserted-by":"publisher","first-page":"182","DOI":"10.1038\/s41592-023-02150-0","volume":"21","author":"A Reinke","year":"2024","unstructured":"Reinke, A., et al.: Understanding metric-related pitfalls in image analysis validation. Nat. Methods 21(2), 182\u2013194 (2024). https:\/\/doi.org\/10.1038\/s41592-023-02150-0","journal-title":"Nat. Methods"},{"issue":"11","key":"21_CR13","doi-asserted-by":"publisher","first-page":"1295","DOI":"10.1515\/CCLM.2006.239","volume":"44","author":"L Thomas","year":"2006","unstructured":"Thomas, L., Huber, A.R.: Renal function-estimation of glomerular filtration rate. Clin. Chem. Lab. Med. (CCLM) 44(11), 1295\u20131302 (2006)","journal-title":"Clin. Chem. Lab. Med. (CCLM)"},{"key":"21_CR14","first-page":"12077","volume":"34","author":"E Xie","year":"2021","unstructured":"Xie, E., Wang, W., Yu, Z., Anandkumar, A., Alvarez, J.M., Luo, P.: SegFormer: simple and efficient design for semantic segmentation with transformers. Adv. Neural. Inf. Process. Syst. 34, 12077\u201312090 (2021)","journal-title":"Adv. Neural. Inf. Process. Syst."},{"key":"21_CR15","unstructured":"Yakubovskiy, P.: Segmentation models with PyTorch. https:\/\/github.com\/qubvel-org\/segmentation_models.pytorch (2023)"}],"container-title":["Lecture Notes in Computer Science","Medical Optical Imaging and Virtual Microscopy Image Analysis"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/978-3-031-77786-8_21","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,1,16]],"date-time":"2025-01-16T11:08:32Z","timestamp":1737025712000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-3-031-77786-8_21"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025]]},"ISBN":["9783031777851","9783031777868"],"references-count":15,"URL":"https:\/\/doi.org\/10.1007\/978-3-031-77786-8_21","relation":{},"ISSN":["0302-9743","1611-3349"],"issn-type":[{"type":"print","value":"0302-9743"},{"type":"electronic","value":"1611-3349"}],"subject":[],"published":{"date-parts":[[2025]]},"assertion":[{"value":"17 January 2025","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}},{"value":"The authors have no competing interests to declare that are relevant to the content of this work.","order":1,"name":"Ethics","group":{"name":"EthicsHeading","label":"Disclosure of Interests"}},{"value":"A. Galdran and the P53 team (M. S\u00e1nchez, H. S\u00e1nchez, C. P\u00e9rez de Arenaza, D. Ribalta) developed solutions for the competition, N. Arrarte and O. C\u00e1mara supervised the work of the P53 team, all authors contributed to the writing of this article.","order":2,"name":"Ethics","group":{"name":"EthicsHeading","label":"Contributions"}},{"value":"MOVI","order":1,"name":"conference_acronym","label":"Conference Acronym","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"International Workshop on Medical Optical Imaging and Virtual Microscopy Image Analysis","order":2,"name":"conference_name","label":"Conference Name","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Marrakesh","order":3,"name":"conference_city","label":"Conference City","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Morocco","order":4,"name":"conference_country","label":"Conference Country","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"2024","order":5,"name":"conference_year","label":"Conference Year","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"10 October 2024","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"10 October 2024","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"2","order":9,"name":"conference_number","label":"Conference Number","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"movi2024","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"https:\/\/sites.google.com\/view\/movi2024","order":11,"name":"conference_url","label":"Conference URL","group":{"name":"ConferenceInfo","label":"Conference Information"}}]}}