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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...

0 Soumick Chatterjee, et al. ∙

∙ 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...

0 Soumick Chatterjee, et al. ∙

∙ 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)...

0 Hana Haseljić, et al. ∙

∙ 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....

0 Alessandro Sciarra, et al. ∙

∙ 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...

0 Soumick Chatterjee, et al. ∙

∙ 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...

0 Soumick Chatterjee, et al. ∙

∙ 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...

18 Soumick Chatterjee, et al. ∙

∙ 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...

31 Philipp Ernst, et al. ∙

∙ 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...

0 Soumick Chatterjee, et al. ∙

∙ 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...

16 Soumick Chatterjee, et al. ∙

∙ 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...

0 Soumick Chatterjee, et al. ∙

∙ 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...

0 Soumick Chatterjee, et al. ∙

∙ 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...

0 Chompunuch Sarasaen, et al. ∙

∙ 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...

0 Soumick Chatterjee, et al. ∙

∙ 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...

0 Dhanunjaya Mitta, et al. ∙

∙ 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...

22 Soumick Chatterjee, et al. ∙

∙ 01/17/2020

CHAOS Challenge – Combined (CT-MR) Healthy Abdominal Organ Segmentation

Segmentation of abdominal organs has been a comprehensive, yet unresolve...

0 A. Emre Kavur, et al. ∙

∙ 10/10/2019

Breathing deformation model – application to multi-resolution abdominal MRI

Dynamic MRI is a technique of acquiring a series of images continuously ...

0 Chompunuch Sarasaen, et al. ∙

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