Publications (13)
Semi-supervised ViT knowledge distillation network with style transfer normalization for colorectal liver metastases survival prediction
Mohamed El Amine Elforaici, Emmanuel Montagnon, Francisco Perdigon Romero +7
Colorectal liver metastases (CLM) significantly impact colon cancer patients, influencing survival based on systemic chemotherapy response. Traditional methods like tumor grading s…
Few-shot Adaptation of Medical Vision-Language Models
Fereshteh Shakeri, Yunshi Huang, Julio Silva-RodrÃguez +4
Integrating image and text data through multi-modal learning has emerged as a new approach in medical imaging research, following its successful deployment in computer vision. Whil…
Metastatic liver tumour segmentation from discriminant Grassmannian manifolds
Samuel Kadoury, Eugene Vorontsov, An Tang
The early detection, diagnosis and monitoring of liver cancer progression can be achieved with the precise delineation of metastatic tumours. However, accurate automated segmentati…
Channel-Selective Normalization for Label-Shift Robust Test-Time Adaptation
Pedro Vianna, Muawiz Chaudhary, Paria Mehrbod +5
Deep neural networks have useful applications in many different tasks, however their performance can be severely affected by changes in the data distribution. For example, in the b…
Multi-Level Batch Normalization In Deep Networks For Invasive Ductal Carcinoma Cell Discrimination In Histopathology Images
Francisco Perdigon Romero, An Tang, Samuel Kadoury
Breast cancer is the most diagnosed cancer and the most predominant cause of death in women worldwide. Imaging techniques such as the breast cancer pathology helps in the diagnosis…
Homodyned K-Distribution Parameter Estimation in Quantitative Ultrasound: Autoencoder and Bayesian Neural Network Approaches
Ali K. Z. Tehrani, Guy Cloutier, An Tang +2
Quantitative ultrasound (QUS) analyzes the ultrasound backscattered data to find the properties of scatterers that correlate with the tissue microstructure. Statistics of the envel…
Liver lesion segmentation informed by joint liver segmentation
Eugene Vorontsov, An Tang, Chris Pal +1
We propose a model for the joint segmentation of the liver and liver lesions in computed tomography (CT) volumes. We build the model from two fully convolutional networks, connecte…
Contactless Remote Induction of Shear Waves in Soft Tissues Using a Transcranial Magnetic Stimulation Device
Pol Grasland-Mongrain, Erika Miller-Jolicoeur, An Tang +2
This study presents the first observation of shear wave induced remotely within soft tissues. It was performed through the combination of a transcranial magnetic stimulation device…
Mitigating Aberration-Induced Noise: A Deep Learning-Based Aberration-to-Aberration Approach
Mostafa Sharifzadeh, Sobhan Goudarzi, An Tang +2
One of the primary sources of suboptimal image quality in ultrasound imaging is phase aberration. It is caused by spatial changes in sound speed over a heterogeneous medium, which…
Predictive Model for Assessment of Pathological Response of Colorectal Liver Metastases to Chemotherapy from CT Images
Francisco Perdigon Romero, Emmanuel Montagnon, Milena Cerny +9
problem with results session, numbers are incorrect, theoretical thinking is no longer valid
The Liver Tumor Segmentation Benchmark (LiTS)
Patrick Bilic, Patrick Christ, Hongwei Bran Li +106
In this work, we report the set-up and results of the Liver Tumor Segmentation Benchmark (LiTS), which was organized in conjunction with the IEEE International Symposium on Biomedi…
Learning Normalized Inputs for Iterative Estimation in Medical Image Segmentation
Michal Drozdzal, Gabriel Chartrand, Eugene Vorontsov +6
In this paper, we introduce a simple, yet powerful pipeline for medical image segmentation that combines Fully Convolutional Networks (FCNs) with Fully Convolutional Residual Netwo…
End-to-End Discriminative Deep Network for Liver Lesion Classification
Francisco Perdigon Romero, Andre Diler, Gabriel Bisson-Gregoire +5
Colorectal liver metastasis is one of most aggressive liver malignancies. While the definition of lesion type based on CT images determines the diagnosis and therapeutic strategy,…