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Machine Learning in Medical Imaging

14th International Workshop, MLMI 2023, Held in Conjunction with MICCAI 2023, Vancouver, BC, Canada, October 8, 2023, Proceedings, Part I

  • Conference proceedings
  • © 2024

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Editors:
  1. Xiaohuan Cao

    1. Shanghai United Imaging Intelligence Co., Ltd., Shanghai, China

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  2. Xuanang Xu

    1. Rensselaer Polytechnic Institute, Troy, USA

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  3. Islem Rekik

    1. Imperial College London, London, UK

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  4. Zhiming Cui

    1. ShanghaiTech University, Shanghai, China

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  5. Xi Ouyang

    1. Shanghai United Imaging Intelligence Co., Ltd., Shanghai, China

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Part of the book series: Lecture Notes in Computer Science (LNCS, volume 14348)

Included in the following conference series:

Conference proceedings info: MLMI 2023.

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Table of contents (46 papers)

  1. Front Matter

    Pages i-xxii
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  2. Structural MRI Harmonization via Disentangled Latent Energy-Based Style Translation

    • Mengqi Wu, Lintao Zhang, Pew-Thian Yap, Weili Lin, Hongtu Zhu, Mingxia Liu
    Pages 1-11

  3. Cross-Domain Iterative Network for Simultaneous Denoising, Limited-Angle Reconstruction, and Attenuation Correction of Cardiac SPECT

    • Xiongchao Chen, Bo Zhou, Huidong Xie, Xueqi Guo, Qiong Liu, Albert J. Sinusas et al.
    Pages 12-22

  4. Arbitrary Reduction of MRI Inter-slice Spacing Using Hierarchical Feature Conditional Diffusion

    • Xin Wang, Zhenrong Shen, Zhiyun Song, Sheng Wang, Mengjun Liu, Lichi Zhang et al.
    Pages 23-32

  5. Reconstruction of 3D Fetal Brain MRI from 2D Cross-Sectional Acquisitions Using Unsupervised Learning Network

    • Yimeng Yang, Dongdong Gu, Xukun Zhang, Zhongxiang Ding, Fei Gao, Zhong Xue et al.
    Pages 33-41

  6. Robust Unsupervised Super-Resolution of Infant MRI via Dual-Modal Deep Image Prior

    • Cheng Che Tsai, Xiaoyang Chen, Sahar Ahmad, Pew-Thian Yap
    Pages 42-51

  7. SR4ZCT: Self-supervised Through-Plane Resolution Enhancement for CT Images with Arbitrary Resolution and Overlap

    • Jiayang Shi, Daniël M. Pelt, K. Joost Batenburg
    Pages 52-61

  8. unORANIC: Unsupervised Orthogonalization of Anatomy and Image-Characteristic Features

    • Sebastian Doerrich, Francesco Di Salvo, Christian Ledig
    Pages 62-71

  9. An Investigation of Different Deep Learning Pipelines for GABA-Edited MRS Reconstruction

    • Rodrigo Berto, Hanna Bugler, Roberto Souza, Ashley Harris
    Pages 72-82

  10. Towards Abdominal 3-D Scene Rendering from Laparoscopy Surgical Videos Using NeRFs

    • Khoa Tuan Nguyen, Francesca Tozzi, Nikdokht Rashidian, Wouter Willaert, Joris Vankerschaver, Wesley De Neve
    Pages 83-93

  11. Brain MRI to PET Synthesis and Amyloid Estimation in Alzheimer’s Disease via 3D Multimodal Contrastive GAN

    • Yan Jin, Jonathan DuBois, Chongyue Zhao, Liang Zhan, Audrey Gabelle, Neda Jahanshad et al.
    Pages 94-103

  12. Accelerated MRI Reconstruction via Dynamic Deformable Alignment Based Transformer

    • Wafa Alghallabi, Akshay Dudhane, Waqas Zamir, Salman Khan, Fahad Shahbaz Khan
    Pages 104-114

  13. Deformable Cross-Attention Transformer for Medical Image Registration

    • Junyu Chen, Yihao Liu, Yufan He, Yong Du
    Pages 115-125

  14. Deformable Medical Image Registration Under Distribution Shifts with Neural Instance Optimization

    • Tony C. W. Mok, Zi Li, Yingda Xia, Jiawen Yao, Ling Zhang, Jingren Zhou et al.
    Pages 126-136

  15. Implicitly Solved Regularization for Learning-Based Image Registration

    • Jan Ehrhardt, Heinz Handels
    Pages 137-146

  16. BHSD: A 3D Multi-class Brain Hemorrhage Segmentation Dataset

    • Biao Wu, Yutong Xie, Zeyu Zhang, Jinchao Ge, Kaspar Yaxley, Suzan Bahadir et al.
    Pages 147-156

  17. Contrastive Learning-Based Breast Tumor Segmentation in DCE-MRI

    • Shanshan Guo, Jiadong Zhang, Dongdong Gu, Fei Gao, Yiqiang Zhan, Zhong Xue et al.
    Pages 157-165

  18. FFPN: Fourier Feature Pyramid Network for Ultrasound Image Segmentation

    • Chaoyu Chen, Xin Yang, Rusi Chen, Junxuan Yu, Liwei Du, Jian Wang et al.
    Pages 166-175

  19. Mammo-SAM: Adapting Foundation Segment Anything Model for Automatic Breast Mass Segmentation in Whole Mammograms

    • Xinyu Xiong, Churan Wang, Wenxue Li, Guanbin Li
    Pages 176-185

  20. Consistent and Accurate Segmentation for Serial Infant Brain MR Images with Registration Assistance

    • Yuhang Sun, Jiameng Liu, Feihong Liu, Kaicong Sun, Han Zhang, Feng Shi et al.
    Pages 186-195
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Other volumes

  1. Machine Learning in Medical Imaging

  2. Machine Learning in Medical Imaging

Keywords

About this book

The two-volume set LNCS 14348 and 14139 constitutes the proceedings of the 14th International Workshop on Machine Learning in Medical Imaging, MLMI 2023, held in conjunction with MICCAI 2023, in Vancouver, Canada, in October 2023. 
The 93 full papers presented in the proceedings were carefully reviewed and selected from 139 submissions. They focus on major trends and challenges in artificial intelligence and machine learning in the medical imaging field, translating medical imaging research into clinical practice. Topics of interests included deep learning, generative adversarial learning, ensemble learning, transfer learning, multi-task learning, manifold learning, reinforcement learning, along with their applications to medical image analysis, computer-aided diagnosis, multi-modality fusion, image reconstruction, image retrieval, cellular image analysis, molecular imaging, digital pathology, etc.

Editors and Affiliations

  • Shanghai United Imaging Intelligence Co., Ltd., Shanghai, China

    Xiaohuan Cao, Xi Ouyang

  • Rensselaer Polytechnic Institute, Troy, USA

    Xuanang Xu

  • Imperial College London, London, UK

    Islem Rekik

  • ShanghaiTech University, Shanghai, China

    Zhiming Cui

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