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Intra-Control: Advancing Tissue Deformation Modeling for Precise Robot Control in MRI-Safe Robot-Assisted Breast Cancer Biopsy

MSc assignment

Introduction:

In breast cancer biopsy procedures, accurate tissue sampling is critical for diagnosis and treatment planning. Robot-assisted biopsy systems offer enhanced precision and control, particularly in minimally invasive approaches. However, performing biopsies under magnetic resonance imaging (MRI) guidance introduces unique challenges due to the MRI environment's constraints and tissue deformation during needle insertion. This master's thesis proposal aims to advance the technology concerning tissue deformation modelling for precise robot control in MRI-safe robot-assisted breast cancer biopsy. By integrating advanced modelling techniques with MRI-compatible robotic systems, this research seeks to improve biopsy accuracy and patient outcomes in breast cancer diagnosis and treatment.

Objectives:

  1. Investigate state-of-the-art modelling techniques for tissue deformation prediction and adaptation in MRI-guided surgical procedures.
  2. Develop tissue deformation mechanisms and investigate their implications for robot-assisted breast cancer biopsy in MRI environments, in terms of sensing and control strategies.
  3. Design and implement novel control algorithms to address real-time tissue deformation modelling and robot control integration in MRI-compatible robotic systems.
  4. Evaluate the performance and feasibility of the proposed approach through simulated biopsy procedures and experimental validation in MRI environments.

Expected Outcomes:

  1. Development of novel algorithms for real-time tissue deformation modelling and integration with control mechanism of  MRI-compatible robotic systems for breast cancer biopsy.
  2. Demonstration of improved accuracy and efficiency in MRI-guided robot-assisted breast biopsy procedures through experimental validation.
  3. Dissemination of research findings through conference presentations/poster and journal publications, fostering collaboration and knowledge exchange with other researchers.

Conclusion:

This master's thesis proposal outlines a research endeavor aimed at advancing the technology concerning tissue deformation modelling for precise robot control in MRI-safe robot-assisted breast cancer biopsy. By integrating advanced modelling techniques with MRI-compatible robotic systems, this research seeks to enhance biopsy accuracy and patient outcomes in breast cancer diagnosis and treatment.