As part of the ongoing graduation project defenses for the AI and Data Science program (2025–2026), IUTT – Faculty of Computer Science and IT presented a distinguished research project titled:
A Hybrid Framework for High Precision Classification of Fetal Brain Anomalies in Ultrasound Imaging
The project aims to develop an advanced intelligent model for classifying fetal brain anomalies based on ultrasound imaging. It involved building a hybrid model named ConvDAB-Net by integrating the ConvNeXt architecture with attention mechanisms (Channel and Spatial Attention), achieving an accuracy rate exceeding 98%.
A key feature of the project is the use of Grad-CAM technology to interpret the model’s decisions and highlight significant regions in the images, enhancing transparency and trust for its potential use as a supportive tool in precise medical diagnosis.
Project Implementation: Johara Abdulsalam.
Supervision: Dr. Amin Shayae, Mr. Mohammed Al-Qumasi.
Internal Defense Committee:
Dr. Hamzah Jamel, Dr. Ayman Al-Sabri, Prof. Dr. Fadhl Ba-Alawi, Dr. Jameel Hamzah.
External Defense Committee:
Prof. Dr. Ahmed Sultan Al-Hajami, Assoc. Prof. Dr. Malik Al-Jabri.
