Microwave Imaging in Breast Tissue

Project Overview

Microwave imaging is an emerging modality for breast cancer detection that leverages the dielectric contrast between normal and malignant tissues. This project aimed to develop a comprehensive computational framework for electromagnetic modeling of a microwave imaging system, creating realistic 3D computational phantoms from medical images, and designing a user-friendly graphical interface to streamline the imaging process.

Key Objectives

1. Electromagnetic Modeling : Develop accurate models of the microwave imaging system to simulate electromagnetic wave propagation through breast tissue.

2. 3D Computational Phantom Development : Convert real-world 3D medical images (e.g., MRI or CT scans) into realistic computational phantoms for simulation purposes.

3. GUI Development : Design an intuitive graphical user interface (GUI) to control and monitor all aspects of the imaging process, from data acquisition to visualization.

 

Technical Contributions

 

1. Electromagnetic Modeling

► Designed and implemented numerical models to simulate the interaction of microwave signals with breast tissue using finite-difference time-domain (FDTD) and finite-element methods (FEM).

► Integrated frequency-dependent dielectric properties of biological tissues to enhance the accuracy of simulations.

► Validated the model against experimental data and benchmarked it against existing literature.

 

2. 3D Computational Phantom Development

► Developed algorithms to segment and process 3D medical images (e.g., DICOM format) to extract anatomical structures such as breast tissue, tumors, and surrounding regions.

► Converted segmented images into voxel-based or mesh-based computational phantoms compatible with electromagnetic simulation software.

► Ensured the phantoms accurately represented heterogeneous tissue properties, enabling realistic simulations of microwave propagation.

 

3. Graphical User Interface (GUI)

► Designed and implemented a GUI using Python (Tkinter/PyQt) or MATLAB App Designer to provide a seamless user experience.

► Features included:

♦ Control over imaging parameters (frequency range, power levels, etc.).

♦ Real-time visualization of simulation results.

♦ Integration with hardware components for data acquisition.

► Enabled researchers and clinicians to interact with the imaging system without requiring extensive programming knowledge.

 

Tools and Technologies

► Programming Languages : Python, C++, C#

► Simulation Tools : CST Microwave Studio, COMSOL Multiphysics, and some other open-source tools

► Image Processing Libraries : ITK, VTK, SimpleITK

► GUI Frameworks : PyQt, Qt, C#

► Data Formats : DICOM, NIfTI, STL, Voxel-based formats

 

Skills Demonstrated

► Electromagnetic simulation and modeling

► Medical image processing and segmentation

► Development of computational phantoms

► GUI design and implementation

► Problem-solving and optimization

► Interdisciplinary collaboration (engineering, medicine, and computer science)