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Computational Mathematics Modeling in Cancer Analysis

Second International Workshop, CMMCA 2023, Held in Conjunction with MICCAI 2023, Vancouver, BC, Canada, October 8, 2023, Proceedings

  • Conference proceedings
  • © 2023

Overview

Editors:
  1. Wenjian Qin

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

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  2. Nazar Zaki

    1. College of Information Technology, United Arab Emirates University, Al Ain, United Arab Emirates

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  3. Fa Zhang

    1. Beijing Institute of Technology, Beijing, China

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  4. Jia Wu

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

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  5. Fan Yang

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

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  6. Chao Li

    1. University of Cambridge, Cambridge, UK

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Part of the book series: Lecture Notes in Computer Science (LNCS, volume 14243)

Included in the following conference series:

Conference proceedings info: CMMCA 2023.

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Table of contents (17 papers)

  1. Front Matter

    Pages i-x
    Download chapter PDF

  2. Virtual Contrast-Enhanced MRI Synthesis with High Model Generalizability Using Trusted Federated Learning (FL-TrustVCE): A Multi-institutional Study

    • Wen Li, Yiming Shi, Saikit Lam, Andy Lai-Yin Cheung, Haonan Xiao, Chenyang Liu et al.
    Pages 1-10

  3. Label-Efficient Cross-Resolution Polyp Segmentation in Colonoscopy

    • Xiaozhou Shi, Youjian Zhang, Li Li, Yunxin Tang, Zezhou Li, Zhicheng Zhang
    Pages 11-20

  4. G-CNN: Adaptive Geometric Convolutional Neural Networks for MRI-Based Skull Stripping

    • Yifan Li, Chao Li, Yiran Wei, Stephen Price, Carola-Bibiane Schönlieb, Xi Chen
    Pages 21-30

  5. The Value of Ensemble Learning Model Based on Conventional Non-Contrast MRI in the Pathological Grading of Cervical Cancer

    • Zhimin He, Fajin Lv, Chengwei Li, Yang Liu, Zhibo Xiao
    Pages 31-41

  6. Federated Multi-organ Dynamic Attention Segmentation Network with Small CT Dataset

    • Li Li, Yunxin Tang, Youjian Zhang, Zezhou Li, Guanqun Zhou, Haotian Zhou et al.
    Pages 42-50

  7. A 3D Inverse Solver for a Multi-species PDE Model of Glioblastoma Growth

    • Ali Ghafouri, George Biros
    Pages 51-60

  8. Domain Knowledge Adapted Semi-supervised Learning with Mean-Teacher Strategy for Circulating Abnormal Cells Identification

    • Huajia Wang, Yinglan Kuang, Xianjun Fan, Yanling Zhou, Xin Ye, Xing Lu
    Pages 61-70

  9. Advancing Delineation of Gross Tumor Volume Based on Magnetic Resonance Imaging by Performing Source-Free Domain Adaptation in Nasopharyngeal Carcinoma

    • Hongqiu Wang, Shichen Zhang, Xiangde Luo, Wenjun Liao, Lei Zhu
    Pages 71-80

  10. BM-SMIL: A Breast Cancer Molecular Subtype Prediction Framework from H&E Slides with Self-supervised Pretraining and Multi-instance Learning

    • Zihao Shang, Hong Liu, Kuansong Wang, Xiangdong Wang
    Pages 81-90

  11. PET-3DFlow: A Normalizing Flow Based Method for 3D PET Anomaly Detection

    • Zhe Xiong, Qiaoqiao Ding, Yuzhong Zhao, Xiaoqun Zhang
    Pages 91-100

  12. Fully Convolutional Transformer-Based GAN for Cross-Modality CT to PET Image Synthesis

    • Yuemei Li, Qiang Zheng, Yi Wang, Yongkang Zhou, Yang Zhang, Yipeng Song et al.
    Pages 101-109

  13. Contrast Learning Based Robust Framework for Weakly Supervised Medical Image Segmentation with Coarse Bounding Box Annotations

    • Ziqi Zhu, Jun Shi, Minfan Zhao, Zhaohui Wang, Liang Qiao, Hong An
    Pages 110-119

  14. MPSurv: End-to-End Multi-model Pseudo-Label Model for Brain Tumor Survival Prediction with Population Information Integration

    • Qingsong Wang, Xin Lin, Ruiquan Ge, Ahmed Elazab, Xiangyang Hu, Jionghao Cheng et al.
    Pages 120-130

  15. Shape-Aware Diffusion Model for Tumor Segmentation on Gd-EOB-DTPA MRI Images of Hepatocellular Carcinoma

    • Ruodai Wu, Yue Peng, Bing Xiong, Wenjian Qin, Songxiong Wu
    Pages 131-139

  16. Style Enhanced Domain Adaptation Neural Network for Cross-Modality Cervical Tumor Segmentation

    • Boyun Zheng, Jiahui He, Jiuhe Zhu, Yaoqin Xie, Nazar Zaki, Wenjian Qin
    Pages 140-149

  17. Automated Segmentation of Nasopharyngeal Carcinoma Based on Dual-Sequence Magnetic Resonance Imaging Using Self-supervised Learning

    • Zongyou Cai, Yufeng Ye, Zhangnan Zhong, Haiwei Lin, Ziyue Xu, Bin Huang et al.
    Pages 150-159

  18. MetaRegNet: Metamorphic Image Registration Using Flow-Driven Residual Networks

    • Ankita Joshi, Yi Hong
    Pages 160-170

  19. Back Matter

    Pages 171-172
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Other volumes

  1. Computational Mathematics Modeling in Cancer Analysis

Keywords

About this book

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.




Editors and Affiliations

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

    Wenjian Qin, Fan Yang

  • College of Information Technology, United Arab Emirates University, Al Ain, United Arab Emirates

    Nazar Zaki

  • Beijing Institute of Technology, Beijing, China

    Fa Zhang

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

    Jia Wu

  • University of Cambridge, Cambridge, UK

    Chao Li

Bibliographic Information

  • Book Title: Computational Mathematics Modeling in Cancer Analysis

  • Book Subtitle: Second International Workshop, CMMCA 2023, Held in Conjunction with MICCAI 2023, Vancouver, BC, Canada, October 8, 2023, Proceedings

  • Editors: Wenjian Qin, Nazar Zaki, Fa Zhang, Jia Wu, Fan Yang, Chao Li

  • Series Title: Lecture Notes in Computer Science

  • DOI: https://doi.org/10.1007/978-3-031-45087-7

  • 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 2023

  • Softcover ISBN: 978-3-031-45086-0Published: 09 October 2023

  • eBook ISBN: 978-3-031-45087-7Published: 07 October 2023

  • Series ISSN: 0302-9743

  • Series E-ISSN: 1611-3349

  • Edition Number: 1

  • Number of Pages: X, 172

  • Number of Illustrations: 3 b/w illustrations, 52 illustrations in colour

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

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