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08/25/2023
GEMTrans: A General, Echocardiography-based, Multi-Level Transformer Framework for Cardiovascular Diagnosis
Echocardiography (echo) is an ultrasound imaging modality that is widely...
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08/13/2023
Manifold DivideMix: A Semi-Supervised Contrastive Learning Framework for Severe Label Noise
Deep neural networks have proven to be highly effective when large amoun...
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07/26/2023
ProtoASNet: Dynamic Prototypes for Inherently Interpretable and Uncertainty-Aware Aortic Stenosis Classification in Echocardiography
Aortic stenosis (AS) is a common heart valve disease that requires accur...
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07/23/2023
EchoGLAD: Hierarchical Graph Neural Networks for Left Ventricle Landmark Detection on Echocardiograms
The functional assessment of the left ventricle chamber of the heart req...
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03/03/2023
TRUSformer: Improving Prostate Cancer Detection from Micro-Ultrasound Using Attention and Self-Supervision
A large body of previous machine learning methods for ultrasound-based p...
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11/01/2022
Self-Supervised Learning with Limited Labeled Data for Prostate Cancer Detection in High Frequency Ultrasound
Deep learning-based analysis of high-frequency, high-resolution micro-ul...
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08/30/2022
EchoGNN: Explainable Ejection Fraction Estimation with Graph Neural Networks
Ejection fraction (EF) is a key indicator of cardiac function, allowing ...
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07/21/2022
Towards Confident Detection of Prostate Cancer using High Resolution Micro-ultrasound
MOTIVATION: Detection of prostate cancer during transrectal ultrasound-g...
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06/26/2022
Class Impression for Data-free Incremental Learning
Standard deep learning-based classification approaches require collectin...
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02/03/2021
Echo-SyncNet: Self-supervised Cardiac View Synchronization in Echocardiography
In echocardiography (echo), an electrocardiogram (ECG) is conventionally...
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02/02/2021
U-LanD: Uncertainty-Driven Video Landmark Detection
This paper presents U-LanD, a framework for joint detection of key frame...
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01/27/2021
Reciprocal Landmark Detection and Tracking with Extremely Few Annotations
Localization of anatomical landmarks to perform two-dimensional measurem...
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10/24/2020
PEP: Parameter Ensembling by Perturbation
Ensembling is now recognized as an effective approach for increasing the...
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12/11/2019
Variational Learning with Disentanglement-PyTorch
Unsupervised learning of disentangled representations is an open problem...
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12/05/2019
A Study into Echocardiography View Conversion
Transthoracic echo is one of the most common means of cardiac studies in...
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11/29/2019
Confidence Calibration and Predictive Uncertainty Estimation for Deep Medical Image Segmentation
Fully convolutional neural networks (FCNs), and in particular U-Nets, ha...
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11/26/2019
A Preliminary Study of Disentanglement With Insights on the Inadequacy of Metrics
Disentangled encoding is an important step towards a better representati...
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11/05/2019
GAN-enhanced Conditional Echocardiogram Generation
Echocardiography (echo) is a common means of evaluating cardiac conditio...
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11/02/2019
On Modelling Label Uncertainty in Deep Neural Networks: Automatic Estimation of Intra-observer Variability in 2D Echocardiography Quality Assessment
Uncertainty of labels in clinical data resulting from intra-observer var...
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06/27/2019
Variational Shape Completion for Virtual Planning of Jaw Reconstructive Surgery
The premorbid geometry of the mandible is of significant relevance in ja...
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06/27/2019
Variational Mandible Shape Completion for Virtual Surgical Planning
The premorbid geometry of the mandible is of significant relevance in ja...
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10/16/2018
Deep Neural Maps
We introduce a new unsupervised representation learning and visualizatio...
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02/25/2017
