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01/18/2023
Active learning for medical image segmentation with stochastic batches
The performance of learning-based algorithms improves with the amount of...
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01/16/2023
TAAL: Test-time Augmentation for Active Learning in Medical Image Segmentation
Deep learning methods typically depend on the availability of labeled da...
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01/11/2023
Real-time simulation of viscoelastic tissue behavior with physics-guided deep learning
Finite element methods (FEM) are popular approaches for simulation of so...
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06/18/2022
Attention-based Dynamic Subspace Learners for Medical Image Analysis
Learning similarity is a key aspect in medical image analysis, particula...
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05/16/2022
Test-Time Adaptation with Shape Moments for Image Segmentation
Supervised learning is well-known to fail at generalization under distri...
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03/10/2022
Leveraging Labeling Representations in Uncertainty-based Semi-supervised Segmentation
Semi-supervised segmentation tackles the scarcity of annotations by leve...
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11/26/2021
Medial Spectral Coordinates for 3D Shape Analysis
In recent years there has been a resurgence of interest in our community...
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08/09/2021
Manifold-aware Synthesis of High-resolution Diffusion from Structural Imaging
The physical and clinical constraints surrounding diffusion-weighted ima...
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08/06/2021
Source-Free Domain Adaptation for Image Segmentation
Domain adaptation (DA) has drawn high interest for its capacity to adapt...
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10/01/2020
Cost-Sensitive Regularization for Diabetic Retinopathy Grading from Eye Fundus Images
Assessing the degree of disease severity in biomedical images is a task ...
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09/29/2020
Realistic Image Normalization for Multi-Domain Segmentation
Image normalization is a building block in medical image analysis. Conve...
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09/03/2020
The Little W-Net That Could: State-of-the-Art Retinal Vessel Segmentation with Minimalistic Models
The segmentation of the retinal vasculature from eye fundus images repre...
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05/07/2020
Source-Relaxed Domain Adaptation for Image Segmentation
Domain adaptation (DA) has drawn high interests for its capacity to adap...
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04/07/2020
Manifold-driven Attention Maps for Weakly Supervised Segmentation
Segmentation using deep learning has shown promising directions in medic...
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04/01/2020
Manifold-Aware CycleGAN for High Resolution Structural-to-DTI Synthesis
Unpaired image-to-image translation has been applied successfully to nat...
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03/31/2020
Graph Domain Adaptation for Alignment-Invariant Brain Surface Segmentation
The varying cortical geometry of the brain creates numerous challenges f...
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12/02/2019
Adversarial normalization for multi domain image segmentation
Image normalization is a critical step in medical imaging. This step is ...
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11/22/2019
Learnable Pooling in Graph Convolution Networks for Brain Surface Analysis
Brain surface analysis is essential to neuroscience, however, the comple...
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11/22/2019
Spectral Graph Transformer Networks for Brain Surface Parcellation
The analysis of the brain surface modeled as a graph mesh is a challengi...
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08/08/2019
Constrained domain adaptation for segmentation
We propose to adapt segmentation networks with a constrained formulation...
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04/09/2018
HyperDense-Net: A hyper-densely connected CNN for multi-modal image segmentation
Recently, dense connections have attracted substantial attention in comp...
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03/27/2018
