Interests
- Machine/deep learning
- Computer vision
- Medical image analysis
Publications
Journal Papers
- Lu, H., Arshad, M., Thornton, A., Avesani, G., Cunnea, P., Curry, E., Kanavati, F., et al., 2019. "A mathematical-descriptor of tumor-mesoscopic-structure from computed-tomography images annotates prognostic-and molecular-phenotypes of epithelial ovarian cancer." Nature communications 10, no. 1 (2019): 764.
- Kanavati, F., Misawa, K., Fujiwara, M., Mori, K., Rueckert, D., & Glocker, B., Supervoxel classification forests for estimating pairwise image correspondences, Pattern Recognition, Available online 22 September 2016, ISSN 0031-3203
Pre-print
- Kanavati, F., Islam, S., Aboagye, E.O. and Rockall, A., 2018. "Automatic L3 slice detection in 3D CT images using fully-convolutional networks." arXiv preprint arXiv:1811.09244(2018).
Workshop Papers
- Kanavati, F., Misawa, K., Fujiwara, M., Mori, K., Rueckert, D., & Glocker, B. (2017, September). Joint Supervoxel Classification Forest for Weakly-Supervised Organ Segmentation. In International Workshop on Machine Learning in Medical Imaging (pp. 79-87).
- Kanavati, F., Tong, T., Misawa, K., Fujiwara, M., Mori, K., Rueckert, D., & Glocker, B. “Supervoxel Classification Forests for Estimating Pairwise Image Correspondences.” In Machine Learning in Medical Imaging: 6th International Workshop, MLMI 2015, Held in Conjunction with MICCAI 2015, Munich, Germany, October 5, 2015, Proceedings, pp. 94-101. Springer International Publishing, 2015.
Previous Projects
- MSc Project: Motion Stabilisation for Dynamic Medical Image Sequences (PDF).