William Thong

PhD student at University of Amsterdam

I am a PhD student at the Intelligent Sensory Information Systems lab of the University of Amsterdam, under the supervision of Arnold Smeulders and Cees Snoek.

Previously, I received a B.Eng. and an M.Sc. in Biomedical Engineering from Polytechnique Montréal. I completed my Master's thesis under the supervision of Samuel Kadoury (MedICAL lab) and Chris Pal (Mila) on the classification of biomedical images with deep learning. I also received an M2 in Bioimaging (BME-Paris) from Télécom ParisTech.

My research mainly involves image similarity and image retrieval using deep learning.

[Github]  [Google Scholar]  [LinkedIn]

Publications

Cooperative Embeddings for Instance, Attribute and Category Retrieval
William Thong, Cees G.M. Snoek, Arnold W.M. Smeulders
Preprint, 2019
[arxiv]  [supp

We introduce a cooperative embedding to integrate instance, attribute and category similarity notions for image retrieval.

A Layer-Based Sequential Framework for Scene Generation with GANs
Mehmet O. Turkoglu, William Thong, Luuk Spreeuwers, Berkay Kicanaoglu
AAAI, 2019
[arxiv]  [poster]  [code]

We compose a scene layer-by-layer, with an explicit control over the generation of all the scene elements.

Convolutional Networks for Kidney Segmentation in Contrast-Enhanced CT Scans
William Thong, Samuel Kadoury, Nicolas Piché, Christopher J. Pal
CMBBE: Imaging & Visualization, 2018
[paper]

We segment healthy and abnormal kidneys in CT scans with a patch-based ConvNet.

Three-dimensional Morphology Study of Surgical Adolescent Idiopathic Scoliosis Patient from Encoded Geometric Models
William Thong, Stefan Parent, James Wu, Carl-Éric Aubin, Hubert Labelle, Samuel Kadoury
European Spine Journal, 2016
[paper]

We cluster the predominant modes of variability of scoliotic spine deformations from all Lenke types with a stacked auto-encoder.

Automatic Labeling of Vertebral Levels using a Robust Template-Based Approach
Eugénie Ullmann, Jean François Pelletier Paquette*, William Thong*, Julien Cohen-Adad
Journal of Biomedical Imaging, 2014
[paper]

We build a template to predict vertebral levels in MRI images.

Workshop papers & Abstracts

Stacked Auto-Encoders for Classification of 3D Spine Models in Adolescent Idiopathic Scoliosis
William Thong, Hubert Labelle, Jesse Shen, Stefan Parent, Samuel Kadoury
Recent Advances in Computational Methods and Clinical Applications for Spine Imaging, 2015
[paper]

Spinal Cord Toolbox: an Open-Source Framework for Processing Spinal Cord MRI Data
J Cohen-Adad, B De Leener, M Benhamou, D Cadotte, D Fleet, A Cadotte, MG Fehlings, JF Pelletier Paquette, W Thong, M Taso, DL Collins, V Callot, V Fonov
OHBM, 2014
[poster]


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