research
∙
05/27/2023
Trustworthy Deep Learning for Medical Image Segmentation
Despite the recent success of deep learning methods at achieving new sta...
share
research
∙
05/17/2022
blob loss: instance imbalance aware loss functions for semantic segmentation
Deep convolutional neural networks have proven to be remarkably effectiv...
research
∙
04/05/2022
A Dempster-Shafer approach to trustworthy AI with application to fetal brain MRI segmentation
Deep learning models for medical image segmentation can fail unexpectedl...
research
∙
01/12/2022
ECONet: Efficient Convolutional Online Likelihood Network for Scribble-based Interactive Segmentation
Automatic segmentation of lung lesions associated with COVID-19 in CT im...
research
∙
12/24/2021
Generalized Wasserstein Dice Loss, Test-time Augmentation, and Transformers for the BraTS 2021 challenge
Brain tumor segmentation from multiple Magnetic Resonance Imaging (MRI) ...
research
∙
11/03/2021
Partial supervision for the FeTA challenge 2021
This paper describes our method for our participation in the FeTA challe...
research
∙
08/09/2021
Distributionally Robust Segmentation of Abnormal Fetal Brain 3D MRI
The performance of deep neural networks typically increases with the num...
research
∙
11/23/2020
Explainable-by-design Semi-Supervised Representation Learning for COVID-19 Diagnosis from CT Imaging
Our motivating application is a real-world problem: COVID-19 classificat...
research
∙
07/29/2020
Comparative study of deep learning methods for the automatic segmentation of lung, lesion and lesion type in CT scans of COVID-19 patients
Recent research on COVID-19 suggests that CT imaging provides useful inf...
research
∙
01/08/2020
SGD with Hardness Weighted Sampling for Distributionally Robust Deep Learning
Distributionally Robust Optimization (DRO) has been proposed as an alter...
research
∙
11/05/2018
Identifying the Best Machine Learning Algorithms for Brain Tumor Segmentation, Progression Assessment, and Overall Survival Prediction in the BRATS Challenge
Gliomas are the most common primary brain malignancies, with different d...
research
∙
09/11/2017
NiftyNet: a deep-learning platform for medical imaging
Medical image analysis and computer-assisted intervention problems are i...
research
∙
07/06/2017
On the Compactness, Efficiency, and Representation of 3D Convolutional Networks: Brain Parcellation as a Pretext Task
Deep convolutional neural networks are powerful tools for learning visua...
research
∙
07/03/2017
Generalised Wasserstein Dice Score for Imbalanced Multi-class Segmentation using Holistic Convolutional Networks
The Dice score is widely used for binary segmentation due to its robustn...
research
∙
06/25/2017
ToolNet: Holistically-Nested Real-Time Segmentation of Robotic Surgical Tools
Real-time tool segmentation from endoscopic videos is an essential part ...
research
∙
06/25/2017