I am a postdoctoral researcher working on biomedical image analysis and segmentation of liver tumours in the biomedical image analysis research group. My research interests include image processing (texture analysis, image classification, and image segmentation), computer vision, and pattern recognition.
The collaborative research project I am working on aims to develop and improve 3D Ultrasound-based drug delivery strategies that are capable of targeting both primary and metastatic liver tumours over a single course of administration (more info). The project is funded by the Wellcome Trust as part of the Centre of Excellence in Personalised Healthcare.
O. S. Al-Kadi, Daniel Y.F. Chung, Robert C. Carlisle, Constantin C. Coussios, J. Alison Noble, “Quantification of ultrasonic texture intra-heterogeneity via volumetric stochastic modeling for tissue characterization” Medical Image Analysis, vol. 21(1), pp. 59-71, 2015. (Open access) (AudioSlides)
O. S. Al-Kadi, “A Multiresolution Clinical Decision Support System Based on Fractal Model Design for Classification of Histological Brain Tumours,” Computerized Medical Imaging and Graphics, vol. 41, pp. 67-79, 2015.
J. V. Raja, M. Khan, V. K. Ramachandra and O. S. Al-Kadi, "Texture analysis of computed tomography images in characterization of oral cancers involving buccal mucosa," Dentomaxillofacial Radiology, vol. 41(6), pp. 475-480, 2012.
O. S. Al-Kadi, "Texture measures combination for improved meningioma classification of histopathological images," Pattern Recognition, vol. 43(6), pp. 2043-2053, 2010.
O. S. Al-Kadi, "Assessment of texture measures susceptibility to noise in conventional and contrast enhanced computed tomography lung tumour images," Computerized Medical Imaging and Graphics, vol. 34(6), pp. 494-503, 2010.
O. S. Al-Kadi and D. Watson, "Texture Analysis of Aggressive and non-Aggressive Lung Tumor CE CT Images," IEEE Transactions on Biomedical Engineering, vol. 55(7), pp. 1822-1830, 2008.
O. S. Al-Kadi, ”Supervised texture segmentation: a comparative study,” in IEEE Jordan Conf. on Applied Electrical Engineering and Computing Technologies, Jordan, 2011.
O. S. Al-Kadi, "A fractal dimension based optimal wavelet packet analysis technique for classification of meningioma brain tumours," in IEEE Int. Conf. on Image Processing, Egypt, 2009.
O. S. Al-Kadi and D. Watson, "Susceptibility of texture measures to noise: an application to lung tumor CT images," in 8th IEEE Int. Conf. on BioInformatics and BioEngineering, Greece, 2008.
O. S. Al-Kadi, "Combined statistical and model based texture features for improved image classification," in 4th Int. Conf. on Advances in Medical, Signal & Information Processing, Italy, 2008.
Omar S. Al-Kadi, Daniel YF Chung, Constantin C Coussios, J Alison Noble,”Predicting tumour responsiveness to chemotherapy treatment in volumetric Xenograft images,” Medical Engineering Centres Annual Meeting and Bioengineering14: Cancer Engineering and Technologies, London, UK, Sep 2014.
O. S. Al-Kadi, D. Chung, A. Cifor, C. Coussios, J. A. Noble,”Predicting tumour responsiveness to chemotherapy in volumetric liver ultrasound images,” Oxford Biomedical Imaging Festival, Oxford, UK, Oct 2013.
O. S. Al-Kadi, E. Panayiotou, B. Young, D. Watson, “Fractal dimensions of non-small cell lung cancer on CT predicts FDG-PET stage and uptake,” in UK Radiological Congress 2008, Birmingham, UK, 2008.
O. S. Al-Kadi, D. Watson, “Fractal analysis of CE CT lung tumours images,” in the ninth Great British R&D Show, Westminster, House of Commons, Westminster, London, UK, 2007.
O. S. Al-Kadi, D. Watson, “Fractal analysis in Digital Medical Images for lung tumours blood vessels,” in BSUH/BSMS 4th Annual Research Symposium in Vascular Medicine, Brighton, UK, 2006.