An Unsupervised Learning with Feature Approach for Brain Tumor Segmentation Using Magnetic Resonance Imaging. - Khurram Ejaz; Mohd Shafry Mohd Rahim; Usama Ijaz Bajwa; Nadim Rana; Amjad Rehman (ICBBB, 2019)

Hybrid Segmentation Method With Confidence Region Detection for Tumor Identification. - Khurram Ejaz; Mohd Shafry Mohd Rahim; Usama Ijaz Bajwa; Huma Chaudhry; Amjad Rehman; Farhan Ejaz (IEEE Access, 2021)

Minimally parametrized segmentation framework with dual metaheuristic optimisation algorithms and FCM for detection of anomalies in MR brain images. - Senthilkumar Natarajan; Vishnuvarthanan Govindaraj; Yudong Zhang 001; Pallikonda Rajasekaran Murugan; Kannapiran Balasubramanian; Karunanithi Kandasamy; Khurram Ejaz (Biomed. Signal Process. Control., 2022)

A novel triple-level combinational framework for brain anomaly segmentation to augment clinical diagnosis. - Senthilkumar Natarajan; Vishnuvarthanan Govindaraj; Ravipudi Venkata Rao Narayana; Yu-Dong Zhang 001; Pallikonda Rajasekaran Murugan; Karunanithi Kandasamy; Khurram Ejaz (Comput. methods Biomech. Biomed. Eng. Imaging Vis., 2022)

Segmentation Method of Deterministic Feature Clustering for Identification of Brain Tumor Using MRI. - Khurram Ejaz; Norhaida Mohd. Suaib; Mohammad Shahid Kamal; Mohd Shafry Mohd Rahim; Nadim Rana (IEEE Access, 2023)

Segmentation Method for Pathological Brain Tumor and Accurate Detection using MRI. - Khurram Ejaz (IEEE DataPort, 2023)