831 citations · 1.1k across the 19 of their papers we have counts for
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Liver Segmentation using Turbolift Learning for CT and Cone-beam C-arm Perfusion Imaging
Hana Haseljić, Soumick Chatterjee, Robert Frysch +9
Model-based reconstruction employing the time separation technique (TST) was found to improve dynamic perfusion imaging of the liver using C-arm cone-beam computed tomography (CBCT…
Magnetic Resonance Imaging study of sheared granular matter
Jing Wang, Zohreh Farmani, Joshua Dijksman +3
We introduce a Magnetic Resonance Imaging technique to study the geometry of shear zones of soft, low-frictional and hard, frictional granular materials and their mixtures. Hydroge…
Automated SSIM Regression for Detection and Quantification of Motion Artefacts in Brain MR Images
Alessandro Sciarra, Soumick Chatterjee, Max Dünnwald +4
Motion artefacts in magnetic resonance brain images can have a strong impact on diagnostic confidence. The assessment of MR image quality is fundamental before proceeding with the…
Weakly-supervised segmentation using inherently-explainable classification models and their application to brain tumour classification
Soumick Chatterjee, Hadya Yassin, Florian Dubost +2
Deep learning has demonstrated significant potential in medical imaging; however, the opacity of "black-box" models hinders clinical trust, while segmentation tasks typically neces…
MICDIR: Multi-scale Inverse-consistent Deformable Image Registration using UNetMSS with Self-Constructing Graph Latent
Soumick Chatterjee, Himanshi Bajaj, Istiyak H. Siddiquee +5
Image registration is the process of bringing different images into a common coordinate system - a technique widely used in various applications of computer vision, such as remote…
DDoS-UNet: Incorporating temporal information using Dynamic Dual-channel UNet for enhancing super-resolution of dynamic MRI
Soumick Chatterjee, Chompunuch Sarasaen, Georg Rose +2
Magnetic resonance imaging (MRI) provides high spatial resolution and excellent soft-tissue contrast without using harmful ionising radiation. Dynamic MRI is an essential tool for…
StRegA: Unsupervised Anomaly Detection in Brain MRIs using a Compact Context-encoding Variational Autoencoder
Soumick Chatterjee, Alessandro Sciarra, Max Dünnwald +7
Expert interpretation of anatomical images of the human brain is the central part of neuro-radiology. Several machine learning-based techniques have been proposed to assist in the…