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Titlebook: Computational Mathematics Modeling in Cancer Analysis; Second International Wenjian Qin,Nazar Zaki,Chao Li Conference proceedings 2023 The

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发表于 2025-3-21 18:47:52 | 显示全部楼层 |阅读模式
书目名称Computational Mathematics Modeling in Cancer Analysis
副标题Second International
编辑Wenjian Qin,Nazar Zaki,Chao Li
视频videohttp://file.papertrans.cn/233/232665/232665.mp4
丛书名称Lecture Notes in Computer Science
图书封面Titlebook: Computational Mathematics Modeling in Cancer Analysis; Second International Wenjian Qin,Nazar Zaki,Chao Li Conference proceedings 2023 The
描述.This volume LNCS 14243 constitutes the refereed proceedings of the Second International Workshop, CMMCA 2023, Held in Conjunction with MICCAI 2023, on October 8, 2023, in Vancouver, BC, Canada.  ..The 17 full papers presented were carefully reviewed and selected from 25 submissions. The conference focuses on the discovery of cutting-edge techniques addressing trends and challenges in theoretical, computational, and applied aspects of mathematical cancer data analysis.. . . .
出版日期Conference proceedings 2023
关键词Computer Science; Cancer imaging analysis; Computer-aided tumor detection; Multi-modality; Mathematics m
版次1
doihttps://doi.org/10.1007/978-3-031-45087-7
isbn_softcover978-3-031-45086-0
isbn_ebook978-3-031-45087-7Series ISSN 0302-9743 Series E-ISSN 1611-3349
issn_series 0302-9743
copyrightThe Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerl
The information of publication is updating

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Peter M. Winter,Leonard L. Firestone lowering the burden of HR image annotation is a practical and cost-effective topic to save more human and material resources in the dataset preparation. In this work, we proposed a label-efficient cross-resolution polyp segmentation framework via unsupervised domain adaption with unlabeled HR image
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Peter M. Winter,Leonard L. Firestoneve been successful in automating this process, the reliance on local textures can negatively impact model performance in the presence of pathological conditions such as brain tumors. This study presents a novel yet practical approach to offer supplementary texture-invariant spatial information of th
headlong
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Peter M. Winter,Leonard L. Firestonecal cancer. . We retrospectively included 98 patients with cervical cancer (54 well/moderately differentiated and 44 poorly differentiated). Radiomics features were extracted from T2WI Axi and T2WI Sag. Feature selection was performed by intra-class correlation coefficients (ICC), t-test, least abso
SYN
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echnic
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https://doi.org/10.1007/978-1-4899-2657-9ric, single-snapshot magnetic resonance imaging (mpMRI) scan. We model the dynamics of proliferative, infiltrative, and necrotic tumor cells and their coupling to oxygen concentration. Fitting the PDE to the data is a formidable inverse problem as we need an estimate of the healthy subject anatomy,
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