OkuwobiIdowuPaul - 桂林电子科技大学

个人简介

Experiences - Ph.D. (Nanjing University of Science and Technology) Research Interests Image processing, medical image segmentation and analysis, machine learning and deep learning. - Develop different algorithm to solve real mechanical problems; image processing and analysis, specifically medical imaging, etc. The Vision and Image Processing Lab (VIP Lab) is headed by Dr. Okuwobi Idowu Paul. VIP Lab is one of the active leading research groups in the School of Artificial Intelligence (SAI, GUET) engaged in research on the processing, visualization, and analysis of medical images and the medical and clinical applications of these computerized methods. VIP Lab collaborates extensively with many national labs across the country as well as with industry. The laboratory has extensive state-of-the-art facilities for doing research, such as high-performance computers, image capture and display devices, software packages, image datasets, and many other peripherals. The faculty and students of VIP Lab actively publish their research results in many high impact journals and conferences. Faculty of the lab offers a wide variety of courses in computer science and vision and other related areas such as in pattern recognition and machine learning. Current Research The current research focus of the VIP Lab is to develop and evaluate new image processing methods, algorithms, and software tools for the analysis of medical images. This includes the image-based extraction of clinically relevant parameters and biomarkers describing the morphology and function of the retinal/body organs. In doing so, we aim to support clinical studies and preclinical research as well as developing and improving computer-aided diagnosis and patient-specific prediction models with a special focus on, but not limited to, the retinal/ body organ. Our current research includes the following: Ø Computer-assisted applications in medicine Ø Biomedical image computing Ø Retinal image processing Ø Optical coherence tomography image analysis Researchers in the VIP Lab are developing novel and exciting ways to address the issues associated with biomedical imaging to assist clinicians, radiologists, pathologists, and clinical research scientists in better visualizing, diagnosing, and understanding various diseases affecting the human eye and body. Dr. Paul’s Profile Dr. Paul holds a PhD degree in Computer science and technology, with a strong focus on pattern recognition and artificial intelligence. From 2012 to early 2015, he researches at the College of Mechanical and Electrical Engineering of the Nanjing University of Aeronautics and Astronautics, where he works with top experts to solve the current problems faced in the mechanical field. From 2015 to 2019, he researches at the School of Computer Science and Engineering of the Nanjing University of Science and Technology, where he works with world-class computer experts and clinicians to solve several problems faced by ophthalmologists in their daily clinical routine. Currently, he’s with the SAI, GUET and oversees the VIP Lab, where his current research objective is to develop new intelligent algorithms for medical image processing. Dr. Paul’s hobby includes reading, traveling, playing football and building AI robots. He’s a fan of numerous famous public figures, musicians, and movies stars.

研究领域

Research Areas As a vibrant growing research group, our goal is to pursue a wide range of applied and theoretical problems across many areas, as such our research areas span a broad range of multidisciplinary topics including but not limited to the following: Ø Computer vision (image segmentation and classification, target tracking, image restoration including denoising, enhancement, and blur removal) Ø Medical image processing and analysis Ø Bio-information processing Ø Super-resolution reconstruction Ø Pattern recognition and artificial intelligence Ø Machine and deep learning applications Ø Statistical image processing and analysis At VIP Lab, we pursue the development and integration of innovative data-processing tools at various stages of the acquisition, analysis, and interpretation pipeline of different data, in particular, using different imaging modality techniques. We aim at obtaining new insights into those aforementioned research areas by devising new approaches that are based on prior simulation and modeling of the data. As such, we investigate into a new methodology that leads to an integrated approach.

近期论文

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[1] I.P. Okuwobi, Z. Ji, W. Fan, S. Yuan, L. Bekalo and Q. Chen. "Automated Quantification of Hyperreflective Foci in SD-OCT with Diabetic Retinopathy", IEEE Journal of Biomedical and Health Informatics, 24(4), 2020, pp.1125-1136. [2] I.P. Okuwobi, Y. Shen, M. Li, W. Fan, S. Yuan and Q. Chen. "Hyperreflective Foci Enhancement in a Combined Spatial-Transform Domains for SD-OCT Images", Translational Vision Science and Technology, 9(3), 2019. [3] I.P. Okuwobi, W. Fan, C. Yu, S. Yuan, Q. Liu, Y. Zhang, B. Loza and Q. Chen. "Automated Segmentation of Hyperreflective Foci in Spectral Domain Optical Coherence Tomography with Diabetic Retinopathy", Journal of Medical Imaging, 5(1), 2018. [4] I.P. Okuwobi, Q. Chen, S. Niu and L. Bekalo. "Three-Dimensional (3D) Facial Recognition and Prediction", Signal, Image and Video Processing (SiVP), Springer, 10(6), 2016, pp.1151-1158. [5] I.P. Okuwobi and Y. Lu. "Analysis and Prediction of Electrochemical Machining (ECM) Workpieces Quality Using Statistical Wavelets Techniques", The International Journal of Advance Manufacturing Technology, Springer, 79(9-12), 2015, pp.1411-1423.