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Record Nr. |
UNISA996589546503316 |
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Autore |
Ahmadi Seyed-Ahmad |
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Titolo |
Graphs in Biomedical Image Analysis, and Overlapped Cell on Tissue Dataset for Histopathology [[electronic resource] ] : 5th MICCAI Workshop, GRAIL 2023 and 1st MICCAI Challenge, OCELOT 2023, Held in Conjunction with MICCAI 2023, Vancouver, BC, Canada, September 23, and October 4, 2023, Proceedings / / edited by Seyed-Ahmad Ahmadi, Sérgio Pereira |
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Pubbl/distr/stampa |
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Cham : , : Springer Nature Switzerland : , : Imprint : Springer, , 2024 |
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ISBN |
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Edizione |
[1st ed. 2024.] |
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Descrizione fisica |
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1 online resource (183 pages) |
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Collana |
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Lecture Notes in Computer Science, , 1611-3349 ; ; 14373 |
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Altri autori (Persone) |
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Disciplina |
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Soggetti |
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Computer science |
Artificial intelligence |
Machine learning |
Computer Science |
Artificial Intelligence |
Machine Learning |
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Lingua di pubblicazione |
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Formato |
Materiale a stampa |
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Livello bibliografico |
Monografia |
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Nota di contenuto |
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Artificial intelligence. - Machine learning -- Modeling and simulation -- Life and medical sciences -- Design and analysis of algorithms -- Medical Imaging -- Image Segmentation -- Digital Pathology -- Health Informatics -- Geometric Deep Learning -- Graph Analytics. |
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Sommario/riassunto |
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This LNCS conference volume constitutes the proceedings of the MICCAI Workshop GRAIL 2023 and MICCAI Challenge OCELOT 2023, Held in Conjunction with MICCAI 2023, Vancouver, BC, Canada, September 23, and October 4, 2023. The 9 full papers (GRAIL 2023) and 6 full papers (OCELOT 2023) included in this volume were carefully reviewed and selected from GRAIL 14 (GRAIL 2023) and 6 (OCELOT 2023) submissions. The conference GRAIL 2023 a wide set of methods and application and OCELOT 2023 focuses on the cover a wide range of methods utilizing tissue information for better cell detection, in the sense of training strategy, model architecture, and especially how to |
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model cell-tissue relationships. |
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