Breathing deformation model - application to multi-resolution abdominal MRI. - Chompunuch Sarasaen; Soumick Chatterjee; Mario Breitkopf; Domenico Iuso; Georg Rose; Oliver Speck (EMBC, 2019)

Machine learning approach for segmenting glands in colon histology images using local intensity and texture features. - Rupali Khatun; Soumick Chatterjee (CoRR, 2019)

Exploration of Interpretability Techniques for Deep COVID-19 Classification using Chest X-ray Images. - Soumick Chatterjee; Fatima Saad; Chompunuch Sarasaen; Suhita Ghosh; Rupali Khatun; Petia Radeva; Georg Rose; Sebastian Stober; Oliver Speck; Andreas Nürnberger (CoRR, 2020)

DS6: Deformation-aware learning for small vessel segmentation with small, imperfectly labeled dataset. - Soumick Chatterjee; Kartik Prabhu; Mahantesh Pattadkal; Gerda Bortsova; Florian Dubost; Hendrik Mattern; Marleen de Bruijne; Oliver Speck; Andreas Nürnberger (CoRR, 2020)

Retrospective Motion Correction of MR Images using Prior-Assisted Deep Learning. - Soumick Chatterjee; Alessandro Sciarra; Max Dünnwald; Steffen Oeltze-Jafra; Andreas Nürnberger; Oliver Speck (CoRR, 2020)

ShuffleUNet: Super resolution of diffusion-weighted MRIs using deep learning. - Soumick Chatterjee; Alessandro Sciarra; Max Dünnwald; Raghava Vinaykanth Mushunuri; Ranadheer Podishetti; Rajatha Nagaraja Rao; Geetha Doddapaneni Gopinath; Steffen Oeltze-Jafra; Oliver Speck; Andreas Nürnberger (EUSIPCO, 2021)

Upgraded W-Net with Attention Gates and Its Application in Unsupervised 3D Liver Segmentation. - Dhanunjaya Mitta; Soumick Chatterjee; Oliver Speck; Andreas Nürnberger (ICPRAM, 2021)

Fine-tuning deep learning model parameters for improved super-resolution of dynamic MRI with prior-knowledge. - Chompunuch Sarasaen; Soumick Chatterjee; Mario Breitkopf; Georg Rose; Andreas Nürnberger; Oliver Speck (Artif. Intell. Medicine, 2021)

Classification of Brain Tumours in MR Images using Deep Spatiospatial Models. - Soumick Chatterjee; Faraz Ahmed Nizamani; Andreas Nürnberger; Oliver Speck (CoRR, 2021)

TorchEsegeta: Framework for Interpretability and Explainability of Image-based Deep Learning Models. - Soumick Chatterjee; Arnab Das; Chirag Mandal; Budhaditya Mukhopadhyay; Manish Vipinraj; Aniruddh Shukla; Rajatha Nagaraja Rao; Chompunuch Sarasaen; Oliver Speck; Andreas Nürnberger (CoRR, 2021)

CHAOS Challenge - combined (CT-MR) healthy abdominal organ segmentation. - A. Emre Kavur; Naciye Sinem Gezer; Mustafa Baris; Sinem Aslan; Pierre-Henri Conze; Vladimir Groza; Duc Duy Pham; Soumick Chatterjee; Philipp Ernst; Savas Özkan; Bora Baydar; Dmitry A. Lachinov; et al. (Medical Image Anal., 2021)

Liver Segmentation in Time-resolved C-arm CT Volumes Reconstructed from Dynamic Perfusion Scans using Time Separation Technique. - Soumick Chatterjee; Hana Haseljic; Robert Frysch; Vojtech Kulvait; Vladimir Semshchikov; Bennet Hensen; Frank K. Wacker; Inga Brüsch; Thomas Werncke; Oliver Speck; Andreas Nürnberger; Georg Rose (IPAS, 2022)

Complex Network for Complex Problems: A comparative study of CNN and Complex-valued CNN. - Soumick Chatterjee; Pavan Tummala; Oliver Speck; Andreas Nürnberger (IPAS, 2022)

ReconResNet: Regularised residual learning for MR image reconstruction of Undersampled Cartesian and Radial data. - Soumick Chatterjee; Mario Breitkopf; Chompunuch Sarasaen; Hadya Yassin; Georg Rose; Andreas Nürnberger; Oliver Speck (Comput. Biol. Medicine, 2022)

StRegA: Unsupervised anomaly detection in brain MRIs using a compact context-encoding variational autoencoder. - Soumick Chatterjee; Alessandro Sciarra; Max Dünnwald; Pavan Tummala; Shubham Kumar Agrawal; Aishwarya Jauhari; Aman Kalra; Steffen Oeltze-Jafra; Oliver Speck; Andreas Nürnberger (Comput. Biol. Medicine, 2022)

Primal-Dual UNet for Sparse View Cone Beam Computed Tomography Volume Reconstruction. - Philipp Ernst; Soumick Chatterjee; Georg Rose; Andreas Nürnberger (CoRR, 2022)

Weakly-supervised segmentation using inherently-explainable classification models and their application to brain tumour classification. - Soumick Chatterjee; Hadya Yassin; Florian Dubost; Andreas Nürnberger; Oliver Speck (CoRR, 2022)

Automated SSIM Regression for Detection and Quantification of Motion Artefacts in Brain MR Images. - Alessandro Sciarra; Soumick Chatterjee; Max Dünnwald; Giuseppe Placidi; Andreas Nürnberger; Oliver Speck; Steffen Oeltze-Jafra (CoRR, 2022)

DS6, Deformation-Aware Semi-Supervised Learning: Application to Small Vessel Segmentation with Noisy Training Data. - Soumick Chatterjee; Kartik Prabhu; Mahantesh Pattadkal; Gerda Bortsova; Chompunuch Sarasaen; Florian Dubost; Hendrik Mattern; Marleen de Bruijne; Oliver Speck; Andreas Nürnberger (J. Imaging, 2022)

Reducing artefacts in MRI using deep learning: enhancing automatic image processing pipelines. - Soumick Chatterjee (2022)

Unboxing the Black-Box of Deep Learning Based Reconstruction of Undersampled MRIss. - Soumick Chatterjee; Arnab Das; Rupali Khatun; Andreas Nürnberger (XAI.it@AI*IA, 2023)

Flavours of Convolution for Unsupervised Aspect Extraction and Aspect-based Sentiment Analysis. - Soumick Chatterjee; Sowmya Prakash; Andreas Nürnberger (NL4AI@AI*IA, 2023)

Voxel-wise classification for porosity investigation of additive manufactured parts with 3D unsupervised and (deeply) supervised neural networks. - Domenico Iuso; Soumick Chatterjee; Jan De Beenhouwer; Jan Sijbers (CoRR, 2023)

Liver segmentation using Turbolift learning for CT and cone-beam C-arm perfusion imaging. - Hana Haseljic; Soumick Chatterjee; Robert Frysch; Vojtech Kulvait; Vladimir Semshchikov; Bennet Hensen; Frank K. Wacker; Inga Brüsch; Thomas Werncke; Oliver Speck; Andreas Nürnberger; Georg Rose (Comput. Biol. Medicine, 2023)

MICDIR: Multi-scale inverse-consistent deformable image registration using UNetMSS with self-constructing graph latent. - Soumick Chatterjee; Himanshi Bajaj; Istiyak H. Siddiquee; Nandish Bandi Subbarayappa; Steve Simon; Suraj Bangalore Shashidhar; Oliver Speck; Andreas Nürnberger (Comput. Medical Imaging Graph., 2023)

Sinogram upsampling using Primal-Dual UNet for undersampled CT and radial MRI reconstruction. - Philipp Ernst; Soumick Chatterjee; Georg Rose; Oliver Speck; Andreas Nürnberger (Neural Networks, 2023)

HaWANet: Road Scene Understanding with Multi-modal Sensor Data Using Height-Width-Driven Attention Network. - Soumick Chatterjee; Jiahua Xu; Adarsh Kuzhipathalil; Andreas Nürnberger (AI*IA, 2024)

DDoS-UNet: Incorporating Temporal Information Using Dynamic Dual-Channel UNet for Enhancing Super-Resolution of Dynamic MRI. - Soumick Chatterjee; Chompunuch Sarasaen; Georg Rose; Andreas Nürnberger; Oliver Speck (IEEE Access, 2024)

SPOCKMIP: Segmentation of Vessels in MRAs with Enhanced Continuity using Maximum Intensity Projection as Loss. - Chethan Radhakrishna; Karthikesh Varma Chintalapati; Sri Chandana Hudukula Ram Kumar; Raviteja Sutrave; Hendrik Mattern; Oliver Speck; Andreas Nürnberger; Soumick Chatterjee (CoRR, 2024)

SMILE-UHURA Challenge - Small Vessel Segmentation at Mesoscopic Scale from Ultra-High Resolution 7T Magnetic Resonance Angiograms. - Soumick Chatterjee; Hendrik Mattern; Marc Dörner; Alessandro Sciarra; Florian Dubost; Hannes Schnurre; Rupali Khatun; Chun-Chih Yu; Tsung-Lin Hsieh; Yi-Shan Tsai; Yi-Zeng Fang; Yung-Ching Yang; et al. (CoRR, 2024)

Beyond Nyquist: A Comparative Analysis of 3D Deep Learning Models Enhancing MRI Resolution. - Soumick Chatterjee; Alessandro Sciarra; Max Dünnwald; Anitha Bhat Talagini Ashoka; Mayura Gurjar Cheepinahalli Vasudeva; Shudarsan Saravanan; Venkatesh Thirugnana Sambandham; Pavan Tummala; Steffen Oeltze-Jafra; Oliver Speck; Andreas Nürnberger (J. Imaging, 2024)

Exploration of Interpretability Techniques for Deep COVID-19 Classification Using Chest X-ray Images. - Soumick Chatterjee; Fatima Saad; Chompunuch Sarasaen; Suhita Ghosh; Valerie Krug; Rupali Khatun; Rahul Mishra; Nirja Desai; Petia Radeva; Georg Rose; Sebastian Stober; Oliver Speck; et al. (J. Imaging, 2024)

Voxel-wise segmentation for porosity investigation of additive manufactured parts with 3D unsupervised and (deeply) supervised neural networks. - Domenico Iuso; Soumick Chatterjee; Sven Cornelissen; Dries Verhees; Jan De Beenhouwer; Jan Sijbers (Appl. Intell., 2024)

PULASki: Learning inter-rater variability using statistical distances to improve probabilistic segmentation. - Soumick Chatterjee; Franziska Gaidzik; Alessandro Sciarra; Hendrik Mattern; Gábor Janiga; Oliver Speck; Andreas Nürnberger; Sahani Pathiraja (Medical Image Anal., 2025)

LUMEN-A deep learning pipeline for analysis of the 3D morphology of the cerebral lenticulostriate arteries from time-of-flight 7T MRI. - Rui Li; Soumick Chatterjee; Yeerfan Jiaerken; Xia Zhou; Chethan Radhakrishna; Philip Benjamin; Stefania Nannoni; Daniel J. Tozer; Hugh S. Markus; Christopher T. Rodgers (NeuroImage, 2025)