Mahmood Haithami passed his PhD viva with minor changes

The school is proud to announce that Mahmood Haithami has successfully passed his PhD viva subject to minor changes. The viva, held on Tuesday, 23 January 2024, at 10am, was examined by Prof. Nasharuddin Zainal (external examiner) and Dr Tissa Chandesa (internal examiner), and was chaired by Prof. Tomas Maul. Many congratulations to Mahmood Haithami, who successfully defended his thesis entitled “Towards Real-World Clinical Colonoscopy Deep Learning Models for Video-based Bowel Preparation and Generalisable Polyp Segmentation”. Mahmood was supervised by Dr Iman Yi Liao (primary), Dr Amr Ahmed and Dr Hafeez Ullah Amin. As a parallel outcome to this thesis, Mahmood published the following research articles:

• M. Haithami, A. Ahmed, I. Y. Liao, and H. Jalab, “An embedded recurrent neural network-based model for endoscopic semantic segmentation.” In Proceedings of the 3rd International Workshop and Challenge on Computer Vision in Endoscopy (EndoCV 2021) co-located with the 18th IEEE International Symposium on Biomedical Imaging (ISBI 2021), Nice, France, April 13, 2021, vol. 2886, 49–58 (CEUR-WS.org, 2021).
• M. Haithami, A. Ahmed, I. Y. Liao, and H. Jalab, “Employing GRU to combine feature maps in DeeplabV3 for a better segmentation model.” Nordic Machine Intelligence, vol. 1, no. 1, pp. 29–31, Nov. 2021.
• Ali, Sharib, et al., “Assessing generalisability of deep learning-based polyp detection and segmentation methods through a computer vision challenge.” Preprint at arXiv:2202.12031 (2022).
• M. Haithami, A. Ahmed, I. Y. Liao, and H. Jalab, “Automatic bowel preparation assessment using deep learning.” In: Rousseau, JJ., Kapralos, B. (eds) Pattern Recognition, Computer Vision, and Image Processing. ICPR 2022 International Workshops and Challenges. ICPR 2022. Lecture Notes in Computer Science, vol 13643. Springer, Cham. Eisenmann, Matthias, et al. “Biomedical image analysis competitions: The state of current participation practice.” Preprint at arXiv:2212.08568 (2022).
• M. Haithami, A. Ahmed, I. Y. Liao, and H. Jalab. “Enhancing Polyp Segmentation Generalizability by Minimizing Images’ Total Variation.” 2023 IEEE 20th International Symposium on Biomedical Imaging (ISBI). IEEE, 2023.
• M. Haithami, A. Ahmed, I. Y. Liao. “Enhancing generalizability of deep learning polyp segmentation using online spatial interpolation and hue transformation.” Brain Inspired Cognitive Systems: 11th International Conference, BICS 2023, Kuala Lumpur, Malaysia, 2023, Proceedings 11. Lecture Notes in Computer Science, Springer.