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09/18/2023
vSHARP: variable Splitting Half-quadratic ADMM algorithm for Reconstruction of inverse-Problems
Medical Imaging (MI) tasks, such as accelerated Parallel Magnetic Resona...
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08/28/2023
Improving Lesion Volume Measurements on Digital Mammograms
Lesion volume is an important predictor for prognosis in breast cancer. ...
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07/03/2023
Synthesis of Contrast-Enhanced Breast MRI Using Multi-b-Value DWI-based Hierarchical Fusion Network with Attention Mechanism
Magnetic resonance imaging (MRI) is the most sensitive technique for bre...
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02/09/2023
Constrained Empirical Risk Minimization: Theory and Practice
Deep Neural Networks (DNNs) are widely used for their ability to effecti...
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02/03/2023
IMPORTANT-Net: Integrated MRI Multi-Parameter Reinforcement Fusion Generator with Attention Network for Synthesizing Absent Data
Magnetic resonance imaging (MRI) is highly sensitive for lesion detectio...
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02/01/2023
Synthesis-based Imaging-Differentiation Representation Learning for Multi-Sequence 3D/4D MRI
Multi-sequence MRIs can be necessary for reliable diagnosis in clinical ...
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01/20/2023
On Retrospective k-space Subsampling schemes For Deep MRI Reconstruction
Purpose: The MRI k-space acquisition is time consuming. Traditional tech...
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05/27/2022
FlowNet-PET: Unsupervised Learning to Perform Respiratory Motion Correction in PET Imaging
To correct for breathing motion in PET imaging, an interpretable and uns...
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11/18/2021
Recurrent Variational Network: A Deep Learning Inverse Problem Solver applied to the task of Accelerated MRI Reconstruction
Magnetic Resonance Imaging can produce detailed images of the anatomy an...
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10/28/2021
Subpixel object segmentation using wavelets and multi resolution analysis
We propose a novel deep learning framework for fast prediction of bounda...
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09/13/2021
WeakSTIL: Weak whole-slide image level stromal tumor infiltrating lymphocyte scores are all you need
We present WeakSTIL, an interpretable two-stage weak label deep learning...
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08/17/2021
Deep MRI Reconstruction with Radial Subsampling
In spite of its extensive adaptation in almost every medical diagnostic ...
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07/20/2021
DeepSMILE: Self-supervised heterogeneity-aware multiple instance learning for DNA damage response defect classification directly from H E whole-slide images
We propose a Deep learning-based weak label learning method for analysin...
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04/21/2021
Sparse-Shot Learning for Extremely Many Localisations
Object localisation is typically considered in the context of regular im...
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02/07/2021
Automatic Breast Lesion Detection in Ultrafast DCE-MRI Using Deep Learning
Purpose: We propose a deep learning-based computer-aided detection (CADe...
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12/09/2020
State-of-the-art Machine Learning MRI Reconstruction in 2020: Results of the Second fastMRI Challenge
Accelerating MRI scans is one of the principal outstanding problems in t...
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11/10/2020
Multi-channel MR Reconstruction (MC-MRRec) Challenge – Comparing Accelerated MR Reconstruction Models and Assessing Their Genereralizability to Datasets Collected with Differ
The 2020 Multi-channel Magnetic Resonance Reconstruction (MC-MRRec) Chal...
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06/11/2020
Deep learning reconstruction of digital breast tomosynthesis images for accurate breast density and patient-specific radiation dose estimation
The two-dimensional nature of mammography makes estimation of the overal...
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01/24/2020
Kernel of CycleGAN as a Principle homogeneous space
Unpaired image-to-image translation has attracted significant interest d...
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10/20/2019
i-RIM applied to the fastMRI challenge
We, team AImsterdam, summarize our submission to the fastMRI challenge (...
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08/17/2018
Improving Breast Cancer Detection using Symmetry Information with Deep Learning
Convolutional Neural Networks (CNN) have had a huge success in many area...
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08/14/2018
Vendor-independent soft tissue lesion detection using weakly supervised and unsupervised adversarial domain adaptation
Computer-aided detection aims to improve breast cancer screening program...
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08/14/2018
Deep Learning Framework for Digital Breast Tomosynthesis Reconstruction
Digital breast tomosynthesis is rapidly replacing digital mammography as...
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02/19/2018
Automated soft tissue lesion detection and segmentation in digital mammography using a u-net deep learning network
Computer-aided detection or decision support systems aim to improve brea...
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01/15/2018
