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08/22/2023
Characterizing normal perinatal development of the human brain structural connectivity
Early brain development is characterized by the formation of a highly or...
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07/07/2023
TBSS++: A novel computational method for Tract-Based Spatial Statistics
Diffusion-weighted magnetic resonance imaging (dMRI) is widely used to a...
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07/05/2023
Direct segmentation of brain white matter tracts in diffusion MRI
The brain white matter consists of a set of tracts that connect distinct...
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05/05/2022
Atlas-powered deep learning (ADL) – application to diffusion weighted MRI
Deep learning has a great potential for estimating biomarkers in diffusi...
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05/02/2022
Deep Learning Framework for Real-time Fetal Brain Segmentation in MRI
Fetal brain segmentation is an important first step for slice-level moti...
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03/25/2022
Learning to segment fetal brain tissue from noisy annotations
Automatic fetal brain tissue segmentation can enhance the quantitative a...
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01/14/2022
Diffusion Tensor Estimation with Transformer Neural Networks
Diffusion tensor imaging (DTI) is the most widely used tool for studying...
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11/21/2021
Calibrated Diffusion Tensor Estimation
It is highly desirable to know how uncertain a model's predictions are, ...
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06/17/2021
Automatic Segmentation of the Prostate on 3D Trans-rectal Ultrasound Images using Statistical Shape Models and Convolutional Neural Networks
In this work we propose to segment the prostate on a challenging dataset...
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03/05/2021
Interpolation of CT Projections by Exploiting Their Self-Similarity and Smoothness
As the medical usage of computed tomography (CT) continues to grow, the ...
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02/26/2021
Convolution-Free Medical Image Segmentation using Transformers
Like other applications in computer vision, medical image segmentation h...
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06/19/2020
A machine learning-based method for estimating the number and orientations of major fascicles in diffusion-weighted magnetic resonance imaging
Multi-compartment modeling of diffusion-weighted magnetic resonance imag...
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05/30/2020
Critical Assessment of Transfer Learning for Medical Image Segmentation with Fully Convolutional Neural Networks
Transfer learning is widely used for training machine learning models. H...
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04/27/2020
A Deep Attentive Convolutional Neural Network for Automatic Cortical Plate Segmentation in Fetal MRI
Fetal cortical plate segmentation is essential in quantitative analysis ...
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04/12/2020
Improving Calibration and Out-of-Distribution Detection in Medical Image Segmentation with Convolutional Neural Networks
Convolutional Neural Networks (CNNs) are powerful medical image segmenta...
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12/06/2019
Sparse and redundant signal representations for x-ray computed tomography
Image models are central to all image processing tasks. The great advanc...
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12/05/2019
Deep learning with noisy labels: exploring techniques and remedies in medical image analysis
Supervised training of deep learning models requires large labeled datas...
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04/22/2019
Reducing the Hausdorff Distance in Medical Image Segmentation with Convolutional Neural Networks
The Hausdorff Distance (HD) is widely used in evaluating medical image s...
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01/27/2019