Fahdi Kanavati
Fahdi Kanavati
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Cited by
Cited by
Year
Deep learning models for histopathological classification of gastric and colonic epithelial tumours
O Iizuka, F Kanavati, K Kato, M Rambeau, K Arihiro, M Tsuneki
Scientific Reports 10 (1), 1-11, 2020
1152020
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), 1-11, 2019
752019
Weakly-supervised learning for lung carcinoma classification using deep learning
F Kanavati, G Toyokawa, S Momosaki, M Rambeau, Y Kozuma, F Shoji, ...
Scientific reports 10 (1), 1-11, 2020
452020
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
332017
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
332015
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
92018
Partial transfusion: on the expressive influence of trainable batch norm parameters for transfer learning
F Kanavati, M Tsuneki
arXiv preprint arXiv:2102.05543, 2021
42021
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
42017
Deep learning models for gastric signet ring cell carcinoma classification in whole slide images
F Kanavati, S Ichihara, M Rambeau, O Iizuka, K Arihiro, M Tsuneki
Technology in Cancer Research & Treatment 20, 15330338211027901, 2021
32021
A deep learning model to detect pancreatic ductal adenocarcinoma on endoscopic ultrasound-guided fine-needle biopsy
Y Naito, M Tsuneki, N Fukushima, Y Koga, M Higashi, K Notohara, ...
Scientific reports 11 (1), 1-8, 2021
32021
A deep learning model for the classification of indeterminate lung carcinoma in biopsy whole slide images
F Kanavati, G Toyokawa, S Momosaki, H Takeoka, M Okamoto, ...
Scientific Reports 11 (1), 1-14, 2021
32021
A deep learning model for gastric diffuse-type adenocarcinoma classification in whole slide images
F Kanavati, M Tsuneki
arXiv preprint arXiv:2104.12478, 2021
22021
Fully-automated deep learning slice-based muscle estimation from CT images for sarcopenia assessment
F Kanavati, S Islam, Z Arain, EO Aboagye, A Rockall
arXiv preprint arXiv:2006.06432, 2020
12020
A deep learning model for breast ductal carcinoma in situ classification in whole slide images
F Kanavati, S Ichihara, M Tsuneki
medRxiv, 2022
2022
Inference of captions from histopathological patches
M Tsuneki, F Kanavati
2021
Late Breaking Abstract-Fully automated airway measurement correlates with radiological disease progression in Idiopathic Pulmonary Fibrosis
M Roberts, K Kirov, T Mclellan, E Morgan, F Kanavati, D Gallagher, ...
European Respiratory Journal 58 (suppl 65), 2021
2021
Bayesian analysis of the prevalence bias: learning and predicting from imbalanced data
LL Folgoc, V Baltatzis, A Alansary, S Desai, A Devaraj, S Ellis, ...
arXiv preprint arXiv:2108.00250, 2021
2021
Breast invasive ductal carcinoma classification on whole slide images with weakly-supervised and transfer learning
F Kanavati, M Tsuneki
Cancers 13 (21), 5368, 2021
2021
Deep learning models for poorly differentiated colorectal adenocarcinoma classification in whole slide images using transfer learning
M Tsuneki, F Kanavati
bioRxiv, 2021
2021
Bayesian Sampling Bias Correction: Training with the Right Loss Function
LL Folgoc, V Baltatzis, A Alansary, S Desai, A Devaraj, S Ellis, ...
arXiv preprint arXiv:2006.13798, 2020
2020
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Articles 1–20