{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,9,11]],"date-time":"2025-09-11T22:03:58Z","timestamp":1757628238069,"version":"3.44.0"},"publisher-location":"Cham","reference-count":14,"publisher":"Springer Nature Switzerland","isbn-type":[{"type":"print","value":"9783031761621"},{"type":"electronic","value":"9783031761638"}],"license":[{"start":{"date-parts":[[2024,1,1]],"date-time":"2024-01-01T00:00:00Z","timestamp":1704067200000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2024,1,1]],"date-time":"2024-01-01T00:00:00Z","timestamp":1704067200000},"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":[[2024]]},"DOI":"10.1007\/978-3-031-76163-8_7","type":"book-chapter","created":{"date-parts":[[2024,12,26]],"date-time":"2024-12-26T22:56:09Z","timestamp":1735253769000},"page":"69-78","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["Previous Datasets Performance for Brain Tumor Segmentation of\u00a0BraTS 2023 Current Dataset"],"prefix":"10.1007","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-6011-7011","authenticated-orcid":false,"given":"Agus Subhan","family":"Akbar","sequence":"first","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0009-0000-1604-1606","authenticated-orcid":false,"given":"Ahmad Hayam","family":"Brilian","sequence":"additional","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0002-7348-9762","authenticated-orcid":false,"given":"Chastine","family":"Fatichah","sequence":"additional","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0002-1991-0464","authenticated-orcid":false,"given":"Nanik","family":"Suciati","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2024,12,28]]},"reference":[{"key":"7_CR1","unstructured":"GitHub - rachitsaluja\/BraTS-2023-Metrics: Official BraTS 2023 Segmentation Performance Metrics\u2014https:\/\/github.com\/. https:\/\/github.com\/rachitsaluja\/BraTS-2023-Metrics. Accessed 11 Mar 2024"},{"key":"7_CR2","doi-asserted-by":"publisher","unstructured":"Akbar, A.S., Fatichah, C., Suciati, N.: Simple MyUnet3D for BraTS segmentation. In: ICICoS 2020 - Proceeding: 4th International Conference on Informatics and Computational Sciences (2020). https:\/\/doi.org\/10.1109\/ICICoS51170.2020.9299072","DOI":"10.1109\/ICICoS51170.2020.9299072"},{"key":"7_CR3","series-title":"Lecture Notes in Computer Science","doi-asserted-by":"publisher","first-page":"374","DOI":"10.1007\/978-3-030-72087-2_33","volume-title":"Brainlesion: Glioma, Multiple Sclerosis, Stroke and Traumatic Brain Injuries","author":"AS Akbar","year":"2021","unstructured":"Akbar, A.S., Fatichah, C., Suciati, N.: Modified mobilenet for patient survival prediction. In: Crimi, A., Bakas, S. (eds.) BrainLes 2020. LNCS, vol. 12659, pp. 374\u2013387. Springer, Cham (2021). https:\/\/doi.org\/10.1007\/978-3-030-72087-2_33"},{"key":"7_CR4","doi-asserted-by":"publisher","unstructured":"Akbar, A.S., Fatichah, C., Suciati, N.: SDA-UNET2.5D: shallow dilated with attention Unet2.5D for brain tumor segmentation. Int. J. Intell. Eng. Syst. 15(2), 135\u2013149 (2022). https:\/\/doi.org\/10.22266\/ijies2022.0430.14","DOI":"10.22266\/ijies2022.0430.14"},{"key":"7_CR5","doi-asserted-by":"publisher","unstructured":"Akbar, A.S., Fatichah, C., Suciati, N.: Single level UNet3D with multipath residual attention block for brain tumor segmentation. J. King Saud Univ. - Comput. Inf. Sci. 34(6, Part B), 3247\u20133258 (2022). https:\/\/doi.org\/10.1016\/j.jksuci.2022.03.022","DOI":"10.1016\/j.jksuci.2022.03.022"},{"key":"7_CR6","doi-asserted-by":"publisher","unstructured":"Akbar, A.S., Fatichah, C., Suciati, N.: Unet3D with multiple atrous convolutions attention block for brain tumor segmentation. In: Crimi, A., Bakas, S. (eds.) BrainLes 2021. LNCS, vol. 12962, pp. 182\u2013193 (2022). Springer, Cham. https:\/\/doi.org\/10.1007\/978-3-031-08999-2_14","DOI":"10.1007\/978-3-031-08999-2_14"},{"key":"7_CR7","doi-asserted-by":"publisher","unstructured":"Akbar, A.S., Fatichah, C., Suciati, N., Za\u2019in, C.: Yaru3DFPN: a lightweight modified 3D UNet with feature pyramid network and combine thresholding for brain tumor segmentation. Neural Comput. Appl. (2024). https:\/\/doi.org\/10.1007\/s00521-024-09475-7","DOI":"10.1007\/s00521-024-09475-7"},{"key":"7_CR8","unstructured":"Baid, U., et al.: The RSNA-ASNR-MICCAI BraTS 2021 benchmark on brain tumor segmentation and radiogenomic classification (2021)"},{"key":"7_CR9","unstructured":"Bakas, S., et al.: Segmentation labels for the pre-operative scans of the TCGA-GBM collection (2017)"},{"key":"7_CR10","unstructured":"Bakas, S., et al.: Segmentation labels for the pre-operative scans of the TCGA-LGG collection (2017)"},{"issue":"1","key":"7_CR11","doi-asserted-by":"publisher","first-page":"170117","DOI":"10.1038\/sdata.2017.117","volume":"4","author":"S Bakas","year":"2017","unstructured":"Bakas, S., et al.: Advancing the cancer genome atlas glioma MRI collections with expert segmentation labels and radiomic features. Sci. Data 4(1), 170117 (2017)","journal-title":"Sci. Data"},{"key":"7_CR12","series-title":"Lecture Notes in Computer Science","doi-asserted-by":"publisher","first-page":"406","DOI":"10.1007\/978-3-030-11726-9_36","volume-title":"Brainlesion: Glioma, Multiple Sclerosis, Stroke and Traumatic Brain Injuries","author":"E Carver","year":"2019","unstructured":"Carver, E., et al.: Automatic brain tumor segmentation and overall survival prediction using machine learning algorithms. In: Crimi, A., Bakas, S., Kuijf, H., Keyvan, F., Reyes, M., van Walsum, T. (eds.) BrainLes 2018. LNCS, vol. 11384, pp. 406\u2013418. Springer, Cham (2019). https:\/\/doi.org\/10.1007\/978-3-030-11726-9_36"},{"issue":"10","key":"7_CR13","doi-asserted-by":"publisher","first-page":"1993","DOI":"10.1109\/TMI.2014.2377694","volume":"34","author":"BH Menze","year":"2015","unstructured":"Menze, B.H., et al.: The multimodal brain tumor image segmentation benchmark (BRATS). IEEE Trans. Med. Imaging 34(10), 1993\u20132024 (2015)","journal-title":"IEEE Trans. Med. Imaging"},{"key":"7_CR14","series-title":"Lecture Notes in Computer Science","doi-asserted-by":"publisher","first-page":"267","DOI":"10.1007\/978-3-030-11726-9_24","volume-title":"Brainlesion: Glioma, Multiple Sclerosis, Stroke and Traumatic Brain Injuries","author":"H-Y Yang","year":"2019","unstructured":"Yang, H.-Y., Yang, J.: Automatic brain tumor segmentation with contour aware residual network and adversarial training. In: Crimi, A., Bakas, S., Kuijf, H., Keyvan, F., Reyes, M., van Walsum, T. (eds.) BrainLes 2018. LNCS, vol. 11384, pp. 267\u2013278. Springer, Cham (2019). https:\/\/doi.org\/10.1007\/978-3-030-11726-9_24"}],"container-title":["Lecture Notes in Computer Science","Brain Tumor Segmentation, and Cross-Modality Domain Adaptation for Medical Image Segmentation"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/978-3-031-76163-8_7","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,9,10]],"date-time":"2025-09-10T06:39:25Z","timestamp":1757486365000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-3-031-76163-8_7"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2024]]},"ISBN":["9783031761621","9783031761638"],"references-count":14,"URL":"https:\/\/doi.org\/10.1007\/978-3-031-76163-8_7","relation":{},"ISSN":["0302-9743","1611-3349"],"issn-type":[{"type":"print","value":"0302-9743"},{"type":"electronic","value":"1611-3349"}],"subject":[],"published":{"date-parts":[[2024]]},"assertion":[{"value":"28 December 2024","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}},{"value":"BraTS","order":1,"name":"conference_acronym","label":"Conference Acronym","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Challenge on Brain Tumor Segmentation","order":2,"name":"conference_name","label":"Conference Name","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Vancouver, BC","order":3,"name":"conference_city","label":"Conference City","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Canada","order":4,"name":"conference_country","label":"Conference Country","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"2023","order":5,"name":"conference_year","label":"Conference Year","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"12 October 2023","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"12 October 2023","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"brats2023","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"https:\/\/www.synapse.org\/Synapse:syn51156910\/wiki\/627802","order":11,"name":"conference_url","label":"Conference URL","group":{"name":"ConferenceInfo","label":"Conference Information"}}]}}