Faculty of Engineering, Cairo University Department of Systems and Biomedical Engineering
This repository contains a collection of tasks completed as part of the course "Introduction to Imaging and Image-Based Anatomy". Each task explores a unique aspect of imaging systems and medical image analysis, demonstrating both foundational understanding and innovative applications.
This repository contains five project tasks that explore concepts related to imaging and anatomy. Each task is organized in a dedicated folder for clarity and accessibility.
- Objective: Reconstruct medical images in different planes (axial, sagittal, and coronal).
- Features:
- Interactive slicing through medical image stacks.
- Visual representation of anatomical structures across different planes.
- Subtask 1: Organ Classification in Medical Images
- Developed a machine learning model to classify main organs (heart, brain, liver, limbs).
- Subtask 2: Football Player Tracking & Heatmap Analysis
- Applied pretrained YOLO AI for player tracking in match videos.
- Generated movement heatmaps for individual players.
- Objective: Create an interactive puzzle game using unity engine for assembling 3D anatomical organ models.
- Features:
- Engaging and educational tool for learning anatomy.
- Real-time feedback on correct placements.
- Objective: Propose a revolutionary idea that breaks one of the established laws of physics to transform medical imaging.
- Task:
- Developed the concept of Subconscious Imaging by creatively "breaking" Newton's First Law of Motion to visualize subconscious brain activity.
- Key Features:
- Manipulation of light to bend, pause, and trace neural pathways.
- Application of technologies such as entangled photons, multiphoton microscopy, and gradient-index (GRIN) lenses.
- Proposed transformative applications in mental health diagnostics, memory recovery, and dream visualization.
- Deliverables included:
- A one-page professional proposal.
- A 2-minute demonstration video.
- Objective: Develop a professional-grade viewer for DICOM files.
- Features:
- Supports 2D, M2D, and 3D image visualization.
- User-friendly interface inspired by professional tools like RadiAnt and MicroDicom.
- Objective:Create a professional-grade tool for viewing and manipulating medical images.
- Features:
- Zooming and panning capabilities.
- Contrast Enhancement:
- Implemented CLAHE (Contrast Limited Adaptive Histogram Equalization) for improving image contrast.
- Interpolation Methods for Resizing:
- Nearest-Neighbor, Bilinear, and Cubic interpolation techniques for resizing images.
- Histogram Visualization:
- Display and analyze the intensity distribution of medical images for better insight.
The following diagram outlines the workflow and timeline for completing the tasks in this course:
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Programming Languages:
Python, C#. -
Frameworks and Libraries:
Pydicom, Numpy, TensorFlow, PyTorch, OpenCV, ITK/VTK...etc -
Tools:
YOLO, DICOM libraries, 3D visualization tools...etc
- Course Title: Introduction to Imaging and Image-Based Anatomy
- Institution: Faculty of Engineering, Cairo University
- Department: Systems and Biomedical Engineering
- Supervised By: Prof. [Tamer Basha] & Prof. [Aliaa Rehan]
This course introduces key concepts in imaging and its application to anatomical studies, providing hands-on experience through project-based learning.
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Abdullah Gamil
-
Mohamed Badawy
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Rowaida Mohamed
-
Yomna Sabry
For questions or collaborations, feel free to reach out to any of the team members: