Fahdi Kanavati

According to our database, Fahdi Kanavati authored at least 12 papers between 2017 and 2023.

Collaborative distances:

• Dijkstra number of five.
• Erdős number of four.

2023

σ-PCA: a unified neural model for linear and nonlinear principal component analysis.

Fahdi Kanavati, Lucy Katsnith, Masayuki Tsuneki

CoRR, 2023

2022

Inference of captions from histopathological patches.

Masayuki Tsuneki, Fahdi Kanavati

Proceedings of the International Conference on Medical Imaging with Deep Learning, 2022

2021

Bayesian analysis of the prevalence bias: learning and predicting from imbalanced data.

Loïc Le Folgoc, Vasileios Baltatzis, Amir Alansary, Sujal Desai, Anand Devaraj, Sam Ellis, Octavio E. Martinez Manzanera, Fahdi Kanavati, Arjun Nair, Julia A. Schnabel, Ben Glocker

CoRR, 2021

A deep learning model for gastric diffuse-type adenocarcinoma classification in whole slide images.

Fahdi Kanavati, Masayuki Tsuneki

CoRR, 2021

Partial transfusion: on the expressive influence of trainable batch norm parameters for transfer learning.

Fahdi Kanavati, Masayuki Tsuneki

Proceedings of the Medical Imaging with Deep Learning, 7-9 July 2021, Lübeck, Germany., 2021

2020

Deep learning models for gastric signet ring cell carcinoma classification in whole slide images.

Fahdi Kanavati, Shin Ichihara, Michael Rambeau, Osamu Iizuka, Koji Arihiro, Masayuki Tsuneki

CoRR, 2020

Bayesian Sampling Bias Correction: Training with the Right Loss Function.

Loïc Le Folgoc, Vasileios Baltatzis, Amir Alansary, Sujal Desai, Anand Devaraj, Sam Ellis, Octavio E. Martinez Manzanera, Fahdi Kanavati, Arjun Nair, Julia A. Schnabel, Ben Glocker

CoRR, 2020

Fully-automated deep learning slice-based muscle estimation from CT images for sarcopenia assessment.

Fahdi Kanavati, Shah Islam, Zohaib Arain, Eric O. Aboagye, Andrea G. Rockall

CoRR, 2020

2018

Automatic L3 slice detection in 3D CT images using fully-convolutional networks.

Fahdi Kanavati, Shah Islam, Eric O. Aboagye, Andrea G. Rockall

CoRR, 2018

2017

Efficient extraction of semantic information from medical images in large datasets using random forests.

Fahdi Kanavati

PhD thesis, 2017

Supervoxel classification forests for estimating pairwise image correspondences.

Fahdi Kanavati, Tong Tong, Kazunari Misawa, Michitaka Fujiwara, Kensaku Mori, Daniel Rueckert, Ben Glocker

Pattern Recognit., 2017

Joint Supervoxel Classification Forest for Weakly-Supervised Organ Segmentation.

Fahdi Kanavati, Kazunari Misawa, Michitaka Fujiwara, Kensaku Mori, Daniel Rueckert, Ben Glocker

Proceedings of the Machine Learning in Medical Imaging - 8th International Workshop, 2017