Dr. Haider Ali

Researcher at MIAAI at Danube Private University

Dr. Ali specializes in Mathematical Image Analysis, tumor segmentation, and joint image registration. With over 16 years of academic experience, he has mentored 3 Ph.D. candidates and 18 master’s students, engaging in international collaborations with institutions such as CMIT and Bahçeşehir University. His impactful research is published in leading journals, including IEEE Transactions on Image Processing and Pattern Recognition.

With a Ph.D. in Applied Mathematics (Computer Vision) from the University of Peshawar, Dr. Ali conducted significant research at the Center for Mathematical Imaging Techniques (CMIT), University of Liverpool, England. His doctoral research included a funded invitation to CMIT for collaborative work, further solidifying his expertise in imaging algorithms and computational techniques.

At MIAAI, Dr. Ali develops and optimizes advanced algorithms for medical imaging, contributing to projects that improve diagnostic accuracy and treatment planning.

Research Interests:

• Imaging Algorithms and Computational Techniques

• Deep Learning in Medical Imaging (Segmentation, Registration, and Detection)

Awards and Recognition:

• Best Paper Award, International Symposium on Intelligent Computing Systems, 2018

• Funded invitation to CMIT, University of Liverpool, for collaborative research during Ph.D.

• Funded invitations to Cambridge University and Henri Poincaré Institute

For more on Dr. Ali’s work, visit:

• Publications: [Research Publications of Computational Mathematics Group and CMIT centre of University of Liverpool]

• Software: [liverpool.ac.uk/~cmchenke/softw.htm]

Key publications

1. A New Variational Segmentation Model with Hybrid Image Data Fitting Energies. Pattern Recognition, 2015.

2. Active Contours for Textural and Inhomogeneous Object Extraction. Pattern Recognition, 2016.

3. Image Segmentation for Intensity Inhomogeneity in the Presence of High Noise. IEEE Transactions on Image Processing, 27(8), 87-99.

4. Robust Region-Based Active Contour Model via Local Statistical Similarity and Local Similarity Factor for Intensity and High Noise Image Segmentation. Inverse Problems and Imaging, 2022.

5. Image-Selective Segmentation Model for Multi-Regions within the Object of Interest with Application to Medical Disease. Visual Computer, 2021.

6. A Convex Selective Segmentation Model Based on a Piecewise Constant Metric Guided Edge Detector Function. Soft Computing, 2023.