Project 5 (Medical Image Analysis, Biometrics, Robotics Vision)

Automated Tumor Detection in Medical Images with Biometric Verification for Robotic Surgery

Explanation:

In this project activity, you will develop an automated system for tumor detection in medical images, incorporating biometric verification for robotic surgery applications. The project combines concepts from the lessons “Medical Image Analysis,” “Biometrics,” “Robotics Vision,” and “Computer Vision Applications.” The objective is to build a system that can accurately detect tumors in medical images, verify the identity of the patient using biometric information, and provide visual guidance for robotic surgeons during tumor removal procedures.

Steps:

1. Dataset Selection: Choose a dataset that includes medical images (e.g., MRI, CT scans) with labeled tumor regions. Ensure that the dataset includes a variety of tumor types, sizes, and locations. Additionally, gather biometric information (e.g., fingerprints, iris scans) of the patients for identity verification.

2. Preprocessing: Preprocess the medical images by applying necessary enhancements, such as noise removal, contrast adjustment, and image normalization. Ensure that the images are in a format compatible with the algorithms you will be using.

3. Tumor Detection: Implement a tumor detection algorithm, such as image segmentation techniques (e.g., thresholding, region growing) or deep learning-based approaches using pre-trained models like U-Net or Mask R-CNN. Apply the tumor detection algorithm to the preprocessed medical images to identify and localize the tumor regions.

4. Biometric Verification: Incorporate biometric verification into the system to ensure the identity of the patient before performing any surgical procedure. Use the gathered biometric information to verify the patient’s identity, ensuring the correct patient’s data is associated with the medical images.

5. Robotic Surgery Guidance: Utilize the tumor detection results to provide visual guidance for robotic surgeons during tumor removal procedures. Overlay the detected tumor regions onto the medical images to assist surgeons in accurately locating and removing the tumors using robotic surgical instruments.

6. Performance Evaluation: Evaluate the performance of the automated tumor detection system by comparing the detected tumor regions with the ground truth labels from the dataset. Calculate metrics such as accuracy, precision, recall, and F1-score to assess the system’s performance in accurately detecting tumors.

7. Visualization and Reporting: Visualize the results by displaying the original medical images with the overlaid tumor regions and the associated biometric verification. Document the project activity by explaining the implemented tumor detection algorithm, the biometric verification process, and the robotic surgery guidance system. Provide visual examples of correctly detected tumors and the associated biometric verification process.

8. Real-time Application (Optional): Extend the project to a real-time application by implementing the tumor detection and biometric verification system on a live medical image stream. Simulate the process using pre-recorded medical videos or connect to a medical imaging device to obtain live images. Visualize the real-time tumor detection and biometric verification process.

By completing this project activity, you will have gained practical experience in medical image analysis, biometric verification, and robotics vision. This project demonstrates the potential of computer vision in improving tumor detection accuracy, patient identity verification, and surgical guidance in robotic surgery. It opens avenues for further exploration and innovation in medical imaging analysis and surgical automation using computer vision techniques.