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05/13/2023
Voxel-wise classification for porosity investigation of additive manufactured parts with 3D unsupervised and (deeply) supervised neural networks
Additive Manufacturing (AM) has emerged as a manufacturing process that ...
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02/09/2023
Liver Segmentation in Time-resolved C-arm CT Volumes Reconstructed from Dynamic Perfusion Scans using Time Separation Technique
Perfusion imaging is a valuable tool for diagnosing and treatment planni...
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02/09/2023
Complex Network for Complex Problems: A comparative study of CNN and Complex-valued CNN
Neural networks, especially convolutional neural networks (CNN), are one...
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07/20/2022
Liver Segmentation using Turbolift Learning for CT and Cone-beam C-arm Perfusion Imaging
Model-based reconstruction employing the time separation technique (TST)...
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06/14/2022
Automated SSIM Regression for Detection and Quantification of Motion Artefacts in Brain MR Images
Motion artefacts in magnetic resonance brain images are a crucial issue....
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05/11/2022
Primal-Dual UNet for Sparse View Cone Beam Computed Tomography Volume Reconstruction
In this paper, the Primal-Dual UNet for sparse view CT reconstruction is...
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03/08/2022
MICDIR: Multi-scale Inverse-consistent Deformable Image Registration using UNetMSS with Self-Constructing Graph Latent
Image registration is the process of bringing different images into a co...
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02/10/2022
DDoS-UNet: Incorporating temporal information using Dynamic Dual-channel UNet for enhancing super-resolution of dynamic MRI
Magnetic resonance imaging (MRI) provides high spatial resolution and ex...
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01/31/2022
StRegA: Unsupervised Anomaly Detection in Brain MRIs using a Compact Context-encoding Variational Autoencoder
Expert interpretation of anatomical images of the human brain is the cen...
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12/26/2021
Sinogram upsampling using Primal-Dual UNet for undersampled CT and radial MRI reconstruction
CT and MRI are two widely used clinical imaging modalities for non-invas...
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10/16/2021
TorchEsegeta: Framework for Interpretability and Explainability of Image-based Deep Learning Models
Clinicians are often very sceptical about applying automatic image proce...
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05/28/2021
Classification of Brain Tumours in MR Images using Deep Spatiospatial Models
A brain tumour is a mass or cluster of abnormal cells in the brain, whic...
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03/16/2021
ReconResNet: Regularised Residual Learning for MR Image Reconstruction of Undersampled Cartesian and Radial Data
MRI is an inherently slow process, which leads to long scan time for hig...
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02/25/2021
ShuffleUNet: Super resolution of diffusion-weighted MRIs using deep learning
Diffusion-weighted magnetic resonance imaging (DW-MRI) can be used to ch...
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02/04/2021
Fine-tuning deep learning model parameters for improved super-resolution of dynamic MRI with prior-knowledge
Dynamic imaging is a beneficial tool for interventions to assess physiol...
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11/28/2020
Retrospective Motion Correction of MR Images using Prior-Assisted Deep Learning
In MRI, motion artefacts are among the most common types of artefacts. T...
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11/20/2020
Upgraded W-Net with Attention Gates and its Application in Unsupervised 3D Liver Segmentation
Segmentation of biomedical images can assist radiologists to make a bett...
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06/03/2020
Exploration of Interpretability Techniques for Deep COVID-19 Classification using Chest X-ray Images
The outbreak of COVID-19 has shocked the entire world with its fairly ra...
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01/17/2020
CHAOS Challenge – Combined (CT-MR) Healthy Abdominal Organ Segmentation
Segmentation of abdominal organs has been a comprehensive, yet unresolve...
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10/10/2019
Breathing deformation model – application to multi-resolution abdominal MRI
Dynamic MRI is a technique of acquiring a series of images continuously ...
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05/15/2019
