Motion and Positional Error Correction for Cone Beam 3D Reconstruction with Mobile C Arms 1st Edition by C Bodensteiner, C Darolti, H Schumacher, L Matthaus, Achim Schweikard ISBN 9783540757573

Motion and Positional Error Correction for Cone Beam 3D Reconstruction with Mobile C Arms 1st Edition by C Bodensteiner, C Darolti, H Schumacher, L Matthaus, Achim Schweikard – Ebook PDF Instant Download/Delivery. 9783540757573
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ISBN 10: 
ISBN 13: 9783540757573
Author: C Bodensteiner, C Darolti, H Schumacher, L Matthaus, Achim Schweikard

CT-images acquired by mobile C-arm devices can contain artefacts caused by positioning errors. We propose a data driven method based on iterative 3D-reconstruction and 2D/3D-registration to correct projection data inconsistencies. With a 2D/3D-registration algorithm, transformations are computed to align the acquired projection images to a previously reconstructed volume. In an iterative procedure, the reconstruction algorithm uses the results of the registration step. This algorithm also reduces small motion artefacts within 3D-reconstructions. Experiments with simulated projections from real patient data show the feasibility of the proposed method. In addition, experiments with real projection data acquired with an experimental robotised C-arm device have been performed with promising results.

Motion and Positional Error Correction for Cone Beam 3D Reconstruction with Mobile C Arms 1st Table of contents:

• Introduction
  1.1 Motivation and Background
  1.2 Importance of Cone Beam 3D Reconstruction in Medical Imaging
  1.3 Challenges in Motion and Positional Errors During Reconstruction
  1.4 Mobile C-Arms and Their Role in Modern Imaging
  1.5 Key Contributions and Objectives of the Paper
  1.6 Structure of the Paper

• Preliminaries
  2.1 Overview of Cone Beam Computed Tomography (CBCT)
  2.2 Mobile C-Arms: Functionality and Application in Medical Imaging
  2.3 Motion and Positional Errors in 3D Reconstruction
  2.4 Error Sources: Patient Movement, C-Arm Misalignment, and External Disturbances
  2.5 Previous Work on Error Correction in CBCT and Mobile C-Arms

• Theoretical Framework for Error Correction
  3.1 Types of Motion and Positional Errors in 3D Reconstruction
  3.2 Mathematical Models for Motion Correction in CBCT
  3.3 Positional Error Models and Their Impact on Image Quality
  3.4 Integrating Motion Correction into CBCT Reconstruction Algorithms
  3.5 Approaches to Compensate for Errors in Real-Time Mobile C-Arm Imaging

• Methodology
  4.1 Data Acquisition and Imaging Protocol for Mobile C-Arms
  4.2 Motion Tracking and Positional Error Detection Techniques
  4.3 Algorithm for Real-Time Motion Correction in Cone Beam Reconstruction
  4.4 Model-Based Error Correction for C-Arm Positioning
  4.5 Integration of Motion Correction Algorithms with C-Arm Systems

• Experimental Results
  5.1 Description of the Experimental Setup and Data Collection
  5.2 Evaluation of Error Correction Performance (e.g., Image Quality, Accuracy)
  5.3 Comparison of Corrected and Uncorrected 3D Reconstructions
  5.4 Case Studies: Use of Mobile C-Arms for Patient Imaging
  5.5 Sensitivity Analysis: Effect of Different Types of Motion and Errors

• Applications
  6.1 Clinical Applications of Mobile C-Arms and 3D Reconstruction
  6.2 Use in Orthopedic Surgery, Interventional Radiology, and Trauma Imaging
  6.3 Enhancing Accuracy for Guided Procedures and Minimally Invasive Surgery
  6.4 Role in Real-Time Navigation and Monitoring During Surgery
  6.5 Integration with Robotic and Augmented Reality-Assisted Surgery

• Discussion
  7.1 Insights from Motion and Positional Error Correction Techniques
  7.2 Strengths and Limitations of Current Correction Methods
  7.3 Challenges in Implementing Real-Time Error Correction in Clinical Settings
  7.4 Future Directions for Motion and Positional Error Correction Algorithms
  7.5 Potential for AI and Machine Learning in Further Improving Accuracy

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