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Predictive Intelligence in Medicine

4th International Workshop, PRIME 2021, Held in Conjunction with MICCAI 2021, Strasbourg, France, October 1, 2021, Proceedings

  • Conference proceedings
  • © 2021

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Editors:
  1. Islem Rekik

    1. Istanbul Technical University, Istanbul, Turkey

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  2. Ehsan Adeli

    1. Stanford University, Stanford, USA

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  3. Sang Hyun Park

    1. Daegu Gyeongbuk Institute of Science and Technology, Daegu, Korea (Republic of)

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  4. Julia Schnabel

    1. Helmholtz Center Munich, Neuherberg, Germany

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Part of the book series: Lecture Notes in Computer Science (LNCS, volume 12928)

Part of the book sub series: Image Processing, Computer Vision, Pattern Recognition, and Graphics (LNIP)

Included in the following conference series:

Conference proceedings info: PRIME 2021.

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Table of contents (25 papers)

  1. Front Matter

    Pages i-xiii
    Download chapter PDF

  2. Low-Dose CT Denoising Using Pseudo-CT Image Pairs

    • Dongkyu Won, Euijin Jung, Sion An, Philip Chikontwe, Sang Hyun Park
    Pages 1-10

  3. A Few-Shot Learning Graph Multi-trajectory Evolution Network for Forecasting Multimodal Baby Connectivity Development from a Baseline Timepoint

    • Alaa Bessadok, Ahmed Nebli, Mohamed Ali Mahjoub, Gang Li, Weili Lin, Dinggang Shen et al.
    Pages 11-24

  4. One Representative-Shot Learning Using a Population-Driven Template with Application to Brain Connectivity Classification and Evolution Prediction

    • Umut Guvercin, Mohammed Amine Gharsallaoui, Islem Rekik
    Pages 25-36

  5. Mixing-AdaSIN: Constructing a De-biased Dataset Using Adaptive Structural Instance Normalization and Texture Mixing

    • Myeongkyun Kang, Philip Chikontwe, Miguel Luna, Kyung Soo Hong, June Hong Ahn, Sang Hyun Park
    Pages 37-46

  6. Liver Tumor Localization and Characterization from Multi-phase MR Volumes Using Key-Slice Prediction: A Physician-Inspired Approach

    • Bolin Lai, Yuhsuan Wu, Xiaoyu Bai, Xiao-Yun Zhou, Peng Wang, Jinzheng Cai et al.
    Pages 47-58

  7. Improving Tuberculosis Recognition on Bone-Suppressed Chest X-Rays Guided by Task-Specific Features

    • Yunbi Liu, Genggeng Qin, Yun Liu, Mingxia Liu, Wei Yang
    Pages 59-69

  8. Template-Based Inter-modality Super-Resolution of Brain Connectivity

    • Furkan Pala, Islem Mhiri, Islem Rekik
    Pages 70-82

  9. Adversarial Bayesian Optimization for Quantifying Motion Artifact Within MRI

    • Anastasia Butskova, Rain Juhl, Dženan Zukić, Aashish Chaudhary, Kilian M. Pohl, Qingyu Zhao
    Pages 83-92

  10. False Positive Suppression in Cervical Cell Screening via Attention-Guided Semi-supervised Learning

    • Xiaping Du, Jiayu Huo, Yuanfang Qiao, Qian Wang, Lichi Zhang
    Pages 93-103

  11. Investigating and Quantifying the Reproducibility of Graph Neural Networks in Predictive Medicine

    • Mohammed Amine Gharsallaoui, Furkan Tornaci, Islem Rekik
    Pages 104-116

  12. Self Supervised Contrastive Learning on Multiple Breast Modalities Boosts Classification Performance

    • Shaked Perek, Mika Amit, Efrat Hexter
    Pages 117-127

  13. Self-guided Multi-attention Network for Periventricular Leukomalacia Recognition

    • Zhuochen Wang, Tingting Huang, Bin Xiao, Jiayu Huo, Sheng Wang, Haoxiang Jiang et al.
    Pages 128-137

  14. Opportunistic Screening of Osteoporosis Using Plain Film Chest X-Ray

    • Fakai Wang, Kang Zheng, Yirui Wang, Xiaoyun Zhou, Le Lu, Jing Xiao et al.
    Pages 138-146

  15. Multi-task Deep Segmentation and Radiomics for Automatic Prognosis in Head and Neck Cancer

    • Vincent Andrearczyk, Pierre Fontaine, Valentin Oreiller, Joel Castelli, Mario Jreige, John O. Prior et al.
    Pages 147-156

  16. Integrating Multimodal MRIs for Adult ADHD Identification with Heterogeneous Graph Attention Convolutional Network

    • Dongren Yao, Erkun Yang, Li Sun, Jing Sui, Mingxia Liu
    Pages 157-167

  17. Probabilistic Deep Learning with Adversarial Training and Volume Interval Estimation - Better Ways to Perform and Evaluate Predictive Models for White Matter Hyperintensities Evolution

    • Muhammad Febrian Rachmadi, Maria del C. Valdés-Hernández, Rizal Maulana, Joanna Wardlaw, Stephen Makin, Henrik Skibbe
    Pages 168-180

  18. A Multi-scale Capsule Network for Improving Diagnostic Generalizability in Breast Cancer Diagnosis Using Ultrasonography

    • Chanho Kim, Won Hwa Kim, Hye Jung Kim, Jaeil Kim
    Pages 181-191

  19. Prediction of Pathological Complete Response to Neoadjuvant Chemotherapy Using Multi-scale Patch Learning with Mammography

    • Ho Kyung Shin, Won Hwa Kim, Hye Jung Kim, Chanho Kim, Jaeil Kim
    Pages 192-200

  20. The Pitfalls of Sample Selection: A Case Study on Lung Nodule Classification

    • Vasileios Baltatzis, Kyriaki-Margarita Bintsi, Loïc Le Folgoc, Octavio E. Martinez Manzanera, Sam Ellis, Arjun Nair et al.
    Pages 201-211
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  1. Predictive Intelligence in Medicine

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About this book

This book constitutes the proceedings of the 4th International Workshop on Predictive Intelligence in Medicine, PRIME 2021, held in conjunction with MICCAI 2021, in Strasbourg, France, in October 2021.*

The 25 papers presented in this volume were carefully reviewed and selected for inclusion in this book. The contributions describe new cutting-edge predictive models and methods that solve challenging problems in the medical field for a high-precision predictive medicine.

*The workshop was held virtually.

Editors and Affiliations

  • Istanbul Technical University, Istanbul, Turkey

    Islem Rekik

  • Stanford University, Stanford, USA

    Ehsan Adeli

  • Daegu Gyeongbuk Institute of Science and Technology, Daegu, Korea (Republic of)

    Sang Hyun Park

  • Helmholtz Center Munich, Neuherberg, Germany

    Julia Schnabel

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