Asad Tariq

Academic

Career

Verbatim text

VtumorDx
VtumorDx is a system that enhances brain tumor classification using image processing techniques, including image segmentation and deep learning techniques. By integrating the approach into a web app and mobile application, the project achieved better results than existing approaches, promising to improve patient outcomes by enabling faster and more accurate. diagnosis of brain tumors. The project's rigorous research has significant implications for doctors and the wider community. It demonstrates the power of combining image processing and Deep learning techniques to solve real-world healthcare problems.
Features include:
- The system includes image segmentation to improve accuracy and speed of diagnosis.
- The project integrates the approach into a web app and mobile application for easy access.
- User and doctors’ interfaces for using the app.
- Improved results in Segmentation of the tumor compared to previous studies.
- Demonstration of the process using animation in the web app.
GROUP MEMBERS
Abdur Rahman 19I-0584
Eman Saleem 19I-0655
Asad Tariq 19I-0659
SUPERVISOR
Dr. Labiba Fahad
Technology Used:
Python, Deep learning, Pytorch, TensorFlow, keras, Angular, Flask Python Framework, Figma
Supervisor Name:
Dr. Labiba Fahad
Group Members:
Mirza Abdur Rahman(i19 - 0584)
Asad Tariq (i19 - 0659)
Eman Saleem (i19 - 0655)

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