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Computational Mathematics Modeling in Cancer Analysis

Third International Workshop, CMMCA 2024, Marrakesh, Morocco, October 6, 2024, Proceedings

  • Conference proceedings
  • © 2025

Overview

Editors:
  1. Jia Wu

    1. The University of Texas MD Anderson Cancer Center, Houston, USA

  2. Wenjian Qin

    1. Shenzhen Institute of Advanced Technology, Chinese Academy of Sciences, Shenzhen, China

  3. Chao Li

    1. University of Cambridge, Cambridge, UK

  4. Boklye Kim

    1. National Cancer Institute, Bethesda, USA

Part of the book series: Lecture Notes in Computer Science (LNCS, volume 15181)

Included in the following conference series:

Conference proceedings info: CMMCA 2024.

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About this book

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.

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Table of contents (12 papers)

  1. Front Matter

    Pages i-x
    Download chapter PDF

  2. Unified Modeling Enhanced Multimodal Learning for Precision Neuro-Oncology

    • Huahui Yi, Xiaofei Wang, Kang Li, Chao Li
    Pages 1-10

  3. A Reference-Based Approach for Tumor Size Estimation in Monocular Laparoscopic Videos

    • Seyed Amir Mousavi, Francesca Tozzi, Homin Park, Esla Timothy Anzaku, Matthias Van Liefferinge, Nikdokht Rashidian et al.
    Pages 11-20

  4. Follicular Lymphoma Grading Based on 3D-DDcGAN and Bayesian CNN Using PET-CT Images

    • Lulu He, Chunjun Qian, Yue Teng, Chongyang Ding, Chong Jiang
    Pages 21-30

  5. 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

    • Yinglan Kuang, Huajia Wang, Yanling Zhou, Xin Ye, Xing Lu
    Pages 31-40

  6. Domain Game: Disentangle Anatomical Feature for Single Domain Generalized Segmentation

    • Hao Chen, Hongrun Zhang, U. Wang Chan, Rui Yin, Xiaofei Wang, Chao Li
    Pages 41-51

  7. Attention-Fusion Model for Multi-omics (AMMO) Data Integration in Lung Adenocarcinoma

    • Wentao Li, Amgad Muneer, Muhammad Waqas, Xiaobo Zhou, Jia Wu
    Pages 52-60

  8. PD-L1 Expression Prediction Using Scalable Multi Instance Transformer

    • Eman Showkatian, Amgad Muneer, Maliazurina B. Saad, Lingzhi Hong, John V. Heymach, Jianjun Zhang et al.
    Pages 61-69

  9. Improving Single-Source Domain Generalization via Anatomy-Guided Texture Augmentation for Cervical Tumor Segmentation

    • Lixue Qin, Zhibo Xiao, Nazar Zaki, Yaoqin Xie, Wenjian Qin
    Pages 70-79

  10. PANDA: Pneumonitis Anomaly Detection Using Attention U-Net

    • Amgad Muneer, Eman Showkatian, Mehmet Altan, Ajay Sheshadri, Jia Wu
    Pages 80-89

  11. Estimating the Average Treatment Effect Using Weighting Methods in Lung Cancer Immunotherapy

    • Maliazurina B. Saad, Qasem Al-Tashi, Lingzhi Hong, Wentao Li, Shenduo Li, John V. Heymach et al.
    Pages 90-98

  12. Beyond Conventional Parametric Modeling: Data-Driven Framework for Estimation and Prediction of Time Activity Curves in Dynamic PET Imaging

    • Niloufar Zakariaei, Arman Rahmim, Eldad Haber
    Pages 99-109

  13. Assessment of Radiomics Feature Repeatability and Reproducibility and Their Generalizability Across Image Modalities by Perturbation in Nasopharyngeal Carcinoma Patients

    • Zongrui Ma, Jiang Zhang, Xinzhi Teng, Saikit Lam, Yuanpeng Zhang, Yu-Hua Huang et al.
    Pages 110-119

  14. Back Matter

    Pages 121-122
    Download chapter PDF
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Other volumes

  1. Computational Mathematics Modeling in Cancer Analysis

Editors and Affiliations

  • The University of Texas MD Anderson Cancer Center, Houston, USA

    Jia Wu

  • Shenzhen Institute of Advanced Technology, Chinese Academy of Sciences, Shenzhen, China

    Wenjian Qin

  • University of Cambridge, Cambridge, UK

    Chao Li

  • National Cancer Institute, Bethesda, USA

    Boklye Kim

Accessibility Information

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Bibliographic Information

  • Book Title: Computational Mathematics Modeling in Cancer Analysis

  • Book Subtitle: Third International Workshop, CMMCA 2024, Marrakesh, Morocco, October 6, 2024, Proceedings

  • Editors: Jia Wu, Wenjian Qin, Chao Li, Boklye Kim

  • Series Title: Lecture Notes in Computer Science

  • DOI: https://doi.org/10.1007/978-3-031-73360-4

  • Publisher: Springer Cham

  • eBook Packages: Computer Science, Computer Science (R0)

  • Copyright Information: The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerland AG 2025

  • Softcover ISBN: 978-3-031-73359-8Published: 05 October 2024

  • eBook ISBN: 978-3-031-73360-4Published: 04 October 2024

  • Series ISSN: 0302-9743

  • Series E-ISSN: 1611-3349

  • Edition Number: 1

  • Number of Pages: X, 122

  • Number of Illustrations: 1 b/w illustrations, 44 illustrations in colour

  • Topics: Computer Imaging, Vision, Pattern Recognition and Graphics

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