Soumick Chatterjee

Orcid: 0000-0001-7594-1188

According to our database1, Soumick Chatterjee authored at least 32 papers between 2019 and 2024.

Collaborative distances:
  • Dijkstra number2 of four.
  • Erdős number3 of four.

Timeline

Legend:

Book 
In proceedings 
Article 
PhD thesis 
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Online presence:

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Bibliography

2024
Voxel-wise segmentation for porosity investigation of additive manufactured parts with 3D unsupervised and (deeply) supervised neural networks.
Appl. Intell., December, 2024

Exploration of Interpretability Techniques for Deep COVID-19 Classification Using Chest X-ray Images.
J. Imaging, February, 2024

Beyond Nyquist: A Comparative Analysis of 3D Deep Learning Models Enhancing MRI Resolution.
J. Imaging, 2024

SPOCKMIP: Segmentation of Vessels in MRAs with Enhanced Continuity using Maximum Intensity Projection as Loss.
CoRR, 2024

DDoS-UNet: Incorporating Temporal Information Using Dynamic Dual-Channel UNet for Enhancing Super-Resolution of Dynamic MRI.
IEEE Access, 2024

2023
Sinogram upsampling using Primal-Dual UNet for undersampled CT and radial MRI reconstruction.
Neural Networks, September, 2023

MICDIR: Multi-scale inverse-consistent deformable image registration using UNetMSS with self-constructing graph latent.
Comput. Medical Imaging Graph., September, 2023

Liver segmentation using Turbolift learning for CT and cone-beam C-arm perfusion imaging.
Comput. Biol. Medicine, March, 2023

PULASki: Learning inter-rater variability using statistical distances to improve probabilistic segmentation.
CoRR, 2023

Voxel-wise classification for porosity investigation of additive manufactured parts with 3D unsupervised and (deeply) supervised neural networks.
CoRR, 2023

Flavours of Convolution for Unsupervised Aspect Extraction and Aspect-based Sentiment Analysis.
Proceedings of the Seventh Workshop on Natural Language for Artificial Intelligence (NL4AI 2023) co-located with 22th International Conference of the Italian Association for Artificial Intelligence (AIxIA 2023), 2023

Unboxing the Black-Box of Deep Learning Based Reconstruction of Undersampled MRIss.
Proceedings of the 4th Italian Workshop on Explainable Artificial Intelligence co-located with 22nd International Conference of the Italian Association for Artificial Intelligence(AIxIA 2023), 2023

2022
Reducing artefacts in MRI using deep learning: enhancing automatic image processing pipelines.
PhD thesis, 2022

DS6, Deformation-Aware Semi-Supervised Learning: Application to Small Vessel Segmentation with Noisy Training Data.
J. Imaging, 2022

Automated SSIM Regression for Detection and Quantification of Motion Artefacts in Brain MR Images.
CoRR, 2022

Weakly-supervised segmentation using inherently-explainable classification models and their application to brain tumour classification.
CoRR, 2022

Primal-Dual UNet for Sparse View Cone Beam Computed Tomography Volume Reconstruction.
CoRR, 2022

StRegA: Unsupervised anomaly detection in brain MRIs using a compact context-encoding variational autoencoder.
Comput. Biol. Medicine, 2022

ReconResNet: Regularised residual learning for MR image reconstruction of Undersampled Cartesian and Radial data.
Comput. Biol. Medicine, 2022

Complex Network for Complex Problems: A comparative study of CNN and Complex-valued CNN.
Proceedings of the 5th IEEE International Conference on Image Processing Applications and Systems, 2022

Liver Segmentation in Time-resolved C-arm CT Volumes Reconstructed from Dynamic Perfusion Scans using Time Separation Technique.
Proceedings of the 5th IEEE International Conference on Image Processing Applications and Systems, 2022

2021
CHAOS Challenge - combined (CT-MR) healthy abdominal organ segmentation.
Medical Image Anal., 2021

TorchEsegeta: Framework for Interpretability and Explainability of Image-based Deep Learning Models.
CoRR, 2021

Classification of Brain Tumours in MR Images using Deep Spatiospatial Models.
CoRR, 2021

Fine-tuning deep learning model parameters for improved super-resolution of dynamic MRI with prior-knowledge.
Artif. Intell. Medicine, 2021

Upgraded W-Net with Attention Gates and Its Application in Unsupervised 3D Liver Segmentation.
Proceedings of the 10th International Conference on Pattern Recognition Applications and Methods, 2021

ShuffleUNet: Super resolution of diffusion-weighted MRIs using deep learning.
Proceedings of the 29th European Signal Processing Conference, 2021

2020
Retrospective Motion Correction of MR Images using Prior-Assisted Deep Learning.
CoRR, 2020

DS6: Deformation-aware learning for small vessel segmentation with small, imperfectly labeled dataset.
CoRR, 2020

Exploration of Interpretability Techniques for Deep COVID-19 Classification using Chest X-ray Images.
CoRR, 2020

2019
Machine learning approach for segmenting glands in colon histology images using local intensity and texture features.
CoRR, 2019

Breathing deformation model - application to multi-resolution abdominal MRI.
Proceedings of the 41st Annual International Conference of the IEEE Engineering in Medicine and Biology Society, 2019


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