research
∙
07/18/2023
Conformal prediction under ambiguous ground truth
In safety-critical classification tasks, conformal prediction allows to ...
share
research
∙
07/05/2023
Evaluating AI systems under uncertain ground truth: a case study in dermatology
For safety, AI systems in health undergo thorough evaluations before dep...
research
∙
05/19/2022
Robust and Efficient Medical Imaging with Self-Supervision
Recent progress in Medical Artificial Intelligence (AI) has delivered sy...
research
∙
06/16/2021
A Simple Fix to Mahalanobis Distance for Improving Near-OOD Detection
Mahalanobis distance (MD) is a simple and popular post-processing method...
research
∙
04/08/2021
Does Your Dermatology Classifier Know What It Doesn't Know? Detecting the Long-Tail of Unseen Conditions
We develop and rigorously evaluate a deep learning based system that can...
research
∙
07/10/2020
Contrastive Training for Improved Out-of-Distribution Detection
Reliable detection of out-of-distribution (OOD) inputs is increasingly u...
research
∙
04/30/2020
Importance Driven Continual Learning for Segmentation Across Domains
The ability of neural networks to continuously learn and adapt to new ta...
research
∙
02/25/2020
Recalibrating 3D ConvNets with Project Excite
Fully Convolutional Neural Networks (F-CNNs) achieve state-of-the-art pe...
research
∙
06/11/2019
`Project & Excite' Modules for Segmentation of Volumetric Medical Scans
Fully Convolutional Neural Networks (F-CNNs) achieve state-of-the-art pe...
research
∙
05/16/2019
BrainTorrent: A Peer-to-Peer Environment for Decentralized Federated Learning
Access to sufficient annotated data is a common challenge in training de...
research
∙
04/05/2019
3DQ: Compact Quantized Neural Networks for Volumetric Whole Brain Segmentation
Model architectures have been dramatically increasing in size, improving...
research
∙
02/04/2019
'Squeeze & Excite' Guided Few-Shot Segmentation of Volumetric Images
Deep neural networks enable highly accurate image segmentation, but requ...
research
∙
01/14/2019
Data Augmentation with Manifold Exploring Geometric Transformations for Increased Performance and Robustness
In this paper we propose a novel augmentation technique that improves no...
research
∙
11/24/2018
Bayesian QuickNAT: Model Uncertainty in Deep Whole-Brain Segmentation for Structure-wise Quality Control
We introduce Bayesian QuickNAT for the automated quality control of whol...
research
∙
10/11/2018
InfiNet: Fully Convolutional Networks for Infant Brain MRI Segmentation
We present a novel, parameter-efficient and practical fully convolutiona...
research
∙
10/11/2018
Learning Optimal Deep Projection of ^18F-FDG PET Imaging for Early Differential Diagnosis of Parkinsonian Syndromes
Several diseases of parkinsonian syndromes present similar symptoms at e...
research
∙
08/23/2018
Recalibrating Fully Convolutional Networks with Spatial and Channel 'Squeeze & Excitation' Blocks
In a wide range of semantic segmentation tasks, fully convolutional neur...
research
∙
06/29/2018
SynNet: Structure-Preserving Fully Convolutional Networks for Medical Image Synthesis
Cross modal image syntheses is gaining significant interests for its abi...
research
∙
04/19/2018
Inherent Brain Segmentation Quality Control from Fully ConvNet Monte Carlo Sampling
We introduce inherent measures for effective quality control of brain se...
research
∙
03/07/2018
Concurrent Spatial and Channel Squeeze & Excitation in Fully Convolutional Networks
Fully convolutional neural networks (F-CNNs) have set the state-of-the-a...
research
∙
01/12/2018
QuickNAT: Segmenting MRI Neuroanatomy in 20 seconds
Whole brain segmentation from structural magnetic resonance imaging is a...
research
∙
05/02/2017
Error Corrective Boosting for Learning Fully Convolutional Networks with Limited Data
Training deep fully convolutional neural networks (F-CNNs) for semantic ...
research
∙
04/07/2017
ReLayNet: Retinal Layer and Fluid Segmentation of Macular Optical Coherence Tomography using Fully Convolutional Network
Optical coherence tomography (OCT) is used for non-invasive diagnosis of...
research
∙
12/16/2016
Deep Residual Hashing
Hashing aims at generating highly compact similarity preserving code wor...
research
∙
09/19/2016
Deep Neural Ensemble for Retinal Vessel Segmentation in Fundus Images towards Achieving Label-free Angiography
Automated segmentation of retinal blood vessels in label-free fundus ima...
research
∙
03/19/2016