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CMMCA (Workshop) (2024 :)

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Computational mathematics modeling in cancer analysis = third International Workshop, CMMCA 2024, Marrakesh, Morocco, October 6, 2024 : proceedings /

紀錄類型:	書目-電子資源 : Monograph/item
正題名/作者:	Computational mathematics modeling in cancer analysis/ edited by Jia Wu ... [et al.].
其他題名:	third International Workshop, CMMCA 2024, Marrakesh, Morocco, October 6, 2024 : proceedings /
其他題名:	CMMCA 2024
其他作者:	Wu, Jia.
團體作者:	CMMCA (Workshop)
出版者:	Cham :Springer Nature Switzerland : : 2025.,
面頁冊數:	x, 122 p. :ill. (chiefly color), digital ;24 cm.
內容註:	Unified Modeling Enhanced Multimodal Learning for Precision Neuro-Oncolo -- A Reference-based Approach for Tumor Size Estimation in Monocular Laparoscopic Videos -- Follicular Lymphoma Grading Based on 3D-DDcGAN and Bayesian CNN using PET-CT Images -- Multi-channel Multi-model Fusion Module (MMFM) based Circulating Abnormal Cells (CACs) Detection for Lung Cancer early Diagnosis with Fluorescence in Situ Hybridization (FISH) Images -- Domain Game: Disentangle Anatomical Feature for Single Domain Generalized Segmentation -- Attention-fusion Model for Multi-Omics (AMMO) Data Integration in Lung Adenocarcinoma -- PD-L1 Expression Prediction using Scalable Multi Instance Transformer -- Improving Single-Source Domain Generalization via Anatomy-Guided Texture Augmentation for Cervical Tumor Segmentation -- PANDA: Pneumonitis ANomaly Detection using Attention U-Net -- Estimating The Average Treatment Effect using Weighting Methods in Lung Cancer Immunotherapy -- Beyond Conventional Parametric Modeling: Data-Driven Framework for Estimation and Prediction of Time Activity Curves in Dynamic PET Imaging -- Assessment of Radiomics Feature Repeatability and Reproducibility and Their Generalizability Across Image Modalities by Perturbation in Nasopharyngeal Carcinoma Patients.
Contained By:	Springer Nature eBook
標題:	Cancer - Congresses. - Imaging -
電子資源:	https://doi.org/10.1007/978-3-031-73360-4
ISBN:	9783031733604

Computational mathematics modeling in cancer analysis = third International Workshop, CMMCA 2024, Marrakesh, Morocco, October 6, 2024 : proceedings /
Computational mathematics modeling in cancer analysisthird International Workshop, CMMCA 2024, Marrakesh, Morocco, October 6, 2024 : proceedings /[electronic resource] :CMMCA 2024edited by Jia Wu ... [et al.]. - Cham :Springer Nature Switzerland :2025. - x, 122 p. :ill. (chiefly color), digital ;24 cm. - Lecture notes in computer science,151811611-3349 ;. - Lecture notes in computer science ;15181..

Unified Modeling Enhanced Multimodal Learning for Precision Neuro-Oncolo -- A Reference-based Approach for Tumor Size Estimation in Monocular Laparoscopic Videos -- Follicular Lymphoma Grading Based on 3D-DDcGAN and Bayesian CNN using PET-CT Images -- Multi-channel Multi-model Fusion Module (MMFM) based Circulating Abnormal Cells (CACs) Detection for Lung Cancer early Diagnosis with Fluorescence in Situ Hybridization (FISH) Images -- Domain Game: Disentangle Anatomical Feature for Single Domain Generalized Segmentation -- Attention-fusion Model for Multi-Omics (AMMO) Data Integration in Lung Adenocarcinoma -- PD-L1 Expression Prediction using Scalable Multi Instance Transformer -- Improving Single-Source Domain Generalization via Anatomy-Guided Texture Augmentation for Cervical Tumor Segmentation -- PANDA: Pneumonitis ANomaly Detection using Attention U-Net -- Estimating The Average Treatment Effect using Weighting Methods in Lung Cancer Immunotherapy -- Beyond Conventional Parametric Modeling: Data-Driven Framework for Estimation and Prediction of Time Activity Curves in Dynamic PET Imaging -- Assessment of Radiomics Feature Repeatability and Reproducibility and Their Generalizability Across Image Modalities by Perturbation in Nasopharyngeal Carcinoma Patients.

This book constitutes the refereed proceedings of Third International Workshop on Computational Mathematics Modeling in Cancer Analysis, CMMCA 2024, held in Marrakesh, Morocco, on October 6, 2024, in conjunction with MICCAI 2024. The 12 full papers presented in this book were carefully reviewed and selected from 14 submissions. CMMCA serves as a platform for collaboration among professionals in mathematics, engineering, computer science, and medicine, focusing on innovative mathematical methods for analyzing complex cancer data.

ISBN: 9783031733604

Standard No.: 10.1007/978-3-031-73360-4doiSubjects--Topical Terms:

3605748
Cancer
--Imaging--Congresses.

LC Class. No.: RC270.3.D53

Dewey Class. No.: 616.9940754

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