Medical image computing and computer assisted intervention -- MICCAI 2023 : 26th International Conference, Vancouver, BC, Canada, October 8-12, 2023, Proceedings. Part X / Hayit Greenspan, Anant Madabhushi, Parvin Mousavi, Septimiu Salcudean, James Duncan, Tanveer Syeda-Mahmood, Russell Taylor, editors.

The ten-volume set LNCS 14220, 14221, 14222, 14223, 14224, 14225, 14226, 14227, 14228, and 14229 constitutes the refereed proceedings of the 26th International Conference on Medical Image Computing and Computer-Assisted Intervention, MICCAI 2023, which was held in Vancouver, Canada, in October 2023....

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Bibliographic Details
Online Access: Full Text (via Springer)
Corporate Author: International Conference on Medical Image Computing and Computer-Assisted Intervention Vancouver, B.C. ; Online
Other Authors: Greenspan, Hayit (Editor), Madabhushi, Anant (Editor), Mousavi, Parvin (Editor), Salcudean, Septimiu Edmund (Editor), Duncan, James, 1951- (Editor), Syeda-Mahmood, Tanveer (Editor), Taylor, Russell (Editor)
Other title:MICCAI 2023
Format: Electronic Conference Proceeding eBook
Language:English
Published: Cham : Springer, 2023.
Series:Lecture notes in computer science ; 14229.
Subjects:
Table of Contents:
  • Intro
  • Preface
  • Organization
  • Contents - Part X
  • Image Reconstruction
  • CDiffMR: Can We Replace the Gaussian Noise with K-Space Undersampling for Fast MRI?
  • 1 Introduction
  • 2 Methodology
  • 2.1 Model Components and Training
  • 2.2 K-Space Conditioning Reverse Process
  • 3 Experimental Results
  • 3.1 Implementation Details and Evaluation Methods
  • 3.2 Comparison and Ablation Studies
  • 4 Discussion and Conclusion
  • References
  • Learning Deep Intensity Field for Extremely Sparse-View CBCT Reconstruction
  • 1 Introduction
  • 2 Method
  • 2.1 Intensity Field
  • 2.2 DIF-Net: Deep Intensity Field Network
  • 2.3 Network Training
  • 2.4 Volume Reconstruction
  • 3 Experiments
  • 3.1 Experimental Settings
  • 3.2 Results
  • 4 Conclusion
  • References
  • Revealing Anatomical Structures in PET to Generate CT for Attenuation Correction
  • 1 Introduction
  • 2 Method
  • 3 Experiments
  • 3.1 Materials
  • 3.2 Comparison with Other Methods
  • 4 Conclusion
  • References
  • LLCaps: Learning to Illuminate Low-Light Capsule Endoscopy with Curved Wavelet Attention and Reverse Diffusion
  • 1 Introduction
  • 2 Methodology
  • 2.1 Preliminaries
  • 2.2 Proposed Methodology
  • 3 Experiments
  • 3.1 Dataset
  • 3.2 Implementation Details
  • 3.3 Results
  • 4 Conclusion
  • References
  • An Explainable Deep Framework: Towards Task-Specific Fusion for Multi-to-One MRI Synthesis
  • 1 Introduction
  • 2 Methods
  • 2.1 Multi-sequence Fusion
  • 2.2 Task-Specific Enhanced Map
  • 3 Experiments
  • 3.1 Dataset and Evaluation Metrics
  • 3.2 Implementation Details
  • 3.3 Quantitative Results
  • 3.4 Ablation Study
  • 3.5 Interpretability Visualization
  • 4 Conclusion
  • References
  • Structure-Preserving Synthesis: MaskGAN for Unpaired MR-CT Translation
  • 1 Introduction
  • 2 Proposed Method
  • 2.1 MaskGAN Architecture
  • 2.2 CycleGAN Supervision
  • 2.3 Mask and Cycle Shape Consistency Supervision
  • 3 Experimental Results
  • 3.1 Experimental Settings
  • 3.2 Results and Discussions
  • 4 Conclusion
  • References
  • Alias-Free Co-modulated Network for Cross-Modality Synthesis and Super-Resolution of MR Images
  • 1 Introduction
  • 2 Methodology
  • 2.1 Co-modulated Network
  • 2.2 Alias-Free Generator
  • 2.3 Optimization
  • 3 Experiments
  • 3.1 Experimental Settings
  • 3.2 Comparative Experiments
  • 4 Conclusion
  • References
  • Multi-perspective Adaptive Iteration Network for Metal Artifact Reduction
  • 1 Introduction
  • 2 Method
  • 3 Experiments
  • 4 Results
  • 5 Discussion and Conclusion
  • References
  • Noise Conditioned Weight Modulation for Robust and Generalizable Low Dose CT Denoising
  • 1 Introduction
  • 2 Method
  • 3 Experimental Setting
  • 4 Result and Discussion
  • 5 Conclusion
  • References
  • Low-Dose CT Image Super-Resolution Network with Dual-Guidance Feature Distillation and Dual-Path Content Communication
  • 1 Introduction
  • 2 Method
  • 2.1 Overall Architecture
  • 2.2 Target Function
  • 3 Experiments