Fahdi Kanavati
Fahdi Kanavati
Research Associate, Imperial College London
Verified email at imperial.ac.uk
TitleCited byYear
Supervoxel classification forests for estimating pairwise image correspondences: applications in registration and segmentation
F Kanavati, T Tong, K Misawa, M Fujiwara, K Mori, D Rueckert, B Glocker
Pattern Recognition 63, 561-569, 2017
232017
Supervoxel Classification Forests for Estimating Pairwise Image Correspondences
F Kanavati, T Tong, K Misawa, M Fujiwara, K Mori, D Rueckert, B Glocker
Machine Learning in Medical Imaging: 6th International Workshop, MLMI 2015 …, 2015
232015
A mathematical-descriptor of tumor-mesoscopic-structure from computed-tomography images annotates prognostic-and molecular-phenotypes of epithelial ovarian cancer
H Lu, M Arshad, A Thornton, G Avesani, P Cunnea, E Curry, F Kanavati, ...
Nature communications 10 (1), 764, 2019
42019
Automatic L3 slice detection in 3D CT images using fully-convolutional networks
F Kanavati, S Islam, EO Aboagye, A Rockall
arXiv preprint arXiv:1811.09244, 2018
22018
Joint supervoxel classification forest for weakly-supervised organ segmentation
F Kanavati, K Misawa, M Fujiwara, K Mori, D Rueckert, B Glocker
International Workshop on Machine Learning in Medical Imaging, 79-87, 2017
22017
A mathematical descriptor of tumour mesoscopic structure from computed tomography images annotates prognostic and molecular phenotypes of epithelial ovarian cancer
H Lu, M Arshad, A Thornton, G Avesani, P Cunnea, E Curry, F Kanavati, ...
BJOG-AN INTERNATIONAL JOURNAL OF OBSTETRICS AND GYNAECOLOGY 126, 89-89, 2019
2019
Efficient extraction of semantic information from medical images in large datasets using random forests
F Kanavati
Imperial College London, 2017
2017
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