Research

Journal Publications

1. Feature-driven Layer Specialization for Label Heterogeneous Federated Learning. In Neurocomputing (2026), 670, 132620.

2. LearnDiff: MRI Image Super-Resolution Using a Diffusion Model with Learnable Noise. In Computerized Medical Imaging and Graphics (2025), 125, 102641.

3. Knowledge Distillation for an Ensemble of Students from a Pyramid of Teachers with Diverse Perspective. In IEEE Transactions on Artificial Intelligence (2025). DOI: 10.1109/TAI.2025.3591588.

4. Class-Incremental Learning Using Push-Pull Autoencoder for Chest X-ray Diagnosis. In Computers in Biology and Medicine (2025), 198 (Part B), 111280.

5. Jayant Mahawar & Angshuman Paul. Generalizable diagnosis of chest radiographs through attention-guided decomposition of images utilizing self-consistency loss. In Computers in Biology and Medicine (2024), 180, 108922.

6. Nirbhay Sharma, Gautam Kumar, & Angshuman Paul. An Extremely Lightweight CNN Model For the Diagnosis of Chest Radiographs in Resource-constrained Environments. In Medical Physics (2023), 50 (12): 7568-78.

7. Manasi Mukherjee, Angshuman Paul, & Mitali Mukerji. Biotic Assessment of Crowdsourced Data Defines Four Ecoregions in Thar: A Novel Approach for Community Engagement in Conservation. In Global Ecology and Conservation (2023), p.e02559.

8. Saikat Sarkar, Spandan Basu, Angshuman Paul, & Dipti Prasad Mukherjee. ViViD: View Prediction of Online Video through Deep Neural Network based Analysis of Subjective Video Attributes. In IEEE Transactions on Broadcasting. 69.1 (2023): 191-200. 

9. Lucian G. Eftimie, Remus R. Glogojeanu, Tejaswee A, Pavel Gheorghita, Stefan G. Stanciu, Augustin Chirila, George A. Stanciu, Angshuman Paul, & Radu Hristu. Differential Diagnosis of Thyroid Nodule Capsules Using Random Forest Guided Selection of Image Features. In Scientific Reports, 12 (1) (2022), 21636.

10. Aratrik Chattopadhyay, Angshuman Paul, & Dipti Prasad Mukherjee. Detail Preserving Conditional Random Field as 2-D RNN for Gland Segmentation in Histology Images. In Pattern Recognition Letters, 159 (2022), 38-45 (DOI: 10.1016/j.patrec.2022.05.001 ). 

11. Angshuman Paul, Thomas C. Shen, Sungwon Lee, Niranjan Balachandar, Yifan Peng, Zhiyong Lu, & Ronald M. Summers (2021). Generalized Zero-shot Chest X-ray Diagnosis through Trait-Guided Multi-view Semantic Embedding with Self-training. In IEEE Transactions on Medical Imaging, 40.10 (2021): 2642-2655. (DOI: 10.1109/TMI.2021.3054817).  

12. Angshuman Paul, Yu-Xing Tang, Thomas C. Shen, & Ronald M. Summers (2021). Discriminative Ensemble Learning for Few-shot Chest X-ray Diagnosis. In Medical Image Analysis, 68 (2021): 101911 (DOI: 10.1016/j.media.2020.101911). 

13. Bikash Santra, Angshuman Paul, & Dipti Prasad Mukherjee (2020). Deterministic Dropout for Deep Neural Networks Using Composite Random Forest. In Pattern Recognition Letters, 131 (2020): 205-212.

14. Angshuman Paul, & Dipti Prasad Mukherjee (2019). Reinforced Quasi-random Forest. In Pattern Recognition, 94 (2019): 13-24.

15. Angshuman Paul, Dipti Prasad Mukherjee, & Scott T. Acton (2018). Speckle Removal Using Diffusion Potential for Optical Coherence Tomography Images. In IEEE Journal of Biomedical and Health Informatics, 23.1 (2018): 264-272.

16. Angshuman Paul, Dipti Prasad Mukherjee, Prasun Das, Abhinandan Gangopadhyay, Appa Rao Chintha, & Saurabh Kundu (2018). Improved Random Forest for Classification. In IEEE Transactions on Image Processing, 27.8 (2018): 4012-4024.

17. Angshuman Paul, Abhinandan Gangopadhyay, Appa Rao Chintha, Dipti Prasad Mukherjee, Prasun Das, & Saurabh Kundu (2018). Calculation of Phase Fraction in Steel Microstructure Images Using Random Forest Classifier. In IET Image Processing, 12.8 (2018): 1370-1377.

18. Angshuman Paul, & Dipti Prasad Mukherjee (2015). Mitosis Detection for Invasive Breast Cancer Grading in Histopathological Images. In IEEE Transactions on Image Processing, 24.11 (2015): 4041-4054.

Conference Publications

1. FedImp: Federated Learning Using Important Layers of Client Models for the Diagnosis of Breast Cancer Histopathology Images. In IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), 2025.

2. Distribution-Guided Generative Replay with Semantic Prompts for Class-Incremental Chest X-ray Diagnosis. In BMVC, 2025.

3. Differential Diagnosis of Thyroid Tumors Through Information Fusion from Multiphoton Microscopy Images Using Fusion Autoencoder. In International Conference on Pattern Recognition (ICPR), 2024, pp. 80–93.

4. Adabot: An Adaptive Trading Bot Using an Ensemble of Phase-Specific Few-Shot Learners to Adapt to the Changing Market Dynamics. In International Conference on Pattern Recognition (ICPR), 2024, pp. 49–66.

5. PSIVUS: Atherosclerotic Plaque Segmentation in Intravascular Ultrasound Images via Active Learning. In International Conference on Pattern Recognition (ICPR), 2024, pp. 154–167.

6. Dattatreyo Roy & Angshuman Paul. Anomaly-focused Single Image Super-resolution with Artifact Removal for Chest X-rays using Distribution-aware Diffusion Model. Medical Imaging with Deep Learning. 2024.

7. Shilajit Banerjee & Angshuman Paul (2024). An Ensemble of Well-trained Students Can Perform Almost As Good As a Teacher for Chest X-ray Diagnosis. In IEEE International Symposium on Biomedical Imaging, 2024 .

8. Jayant Mahawar, Bhargab Chattopadhyay  & Angshuman Paul (2024). Label-guided Coreset Generation for Computationally Efficient Chest X-ray Diagnosis. In IEEE International Symposium on Biomedical Imaging, 2024 .

9. Nitya A. Shah, Jinal Suthar, Tejaswee A, Adrian Enache, Lucian G. Eftimie, Radu Hristu, & Angshuman Paul (2024). Deep Learning-based Diagnosis of Thyroid Tumors using Histopathology Images from Thyroid Nodule Capsule.  In Medical Imaging 2024: Computer-Aided Diagnosis. Vol. 12927. SPIE, 2024.

10. Krishna Thoriya, Preeti Mutreja, Sumit Kalra, & Angshuman Paul (2023). Multi-Task Learning for Few-Shot Differential Diagnosis of Breast Cancer Histopathology Images. In Workshop on Medical Image Learning with Limited and Noisy Data 2023 @ MICCAI 2023 (pp. 202-210).

11. Vamshi Vardhan Yadagiri, Sekhar Reddy, & Angshuman Paul (2023). Anomaly Guided Generalizable Super-Resolution of Chest X-Ray Images using Multi-Level Information Rendering. In Workshop on Deep Generative Models for Medical Image Computing and Computer Assisted Intervention (DGM4MICCAI) @ MICCAI 2023 (pp. 77-85).

12. M K Laksath Adityan, Himanchal Sharma, & Angshuman Paul (2023). Segmentation and Classification-based Diagnosis of Tumors from Breast Ultrasound Images using Multibranch U-Net. In IEEE International Conference on Image Processing (ICIP), pp. 2505-2509. IEEE, 2023. 

13. Kshitiz, Garvit Garg, & Angshuman Paul (2023). Few-shot Diagnosis of Chest x rays Using an Ensemble of Random Discriminative Subspaces. In ICLR Workshop on Machine Learning & Global Health, 2023.

14. Keshava Chowdari Dabbara, Radhasyam Nunna, Anabik Pal, & Angshuman Paul (2023). Federated learning using multi-institutional data for generalizable chest X-ray diagnosis. In Medical Imaging 2023: Computer-Aided Diagnosis, 2023 (Vol. 12465, pp. 124650H). International Society for Optics and Photonics.

15. Jared Gregory Frazier, Tejas Sudharshan Mathai, Jianfei Liu, Angshuman Paul, & Ronald M. Summers (2023).  3D universal lesion detection and tagging in CT with self-training. In Medical Imaging 2023: Computer-Aided Diagnosis, 2023  (Vol. 12465, pp. 765-772). International Society for Optics and Photonics.

16. Alexander Te-Wei Shieh, Tejas Sudharshan Mathai, Jianfei Liu, Angshuman Paul, & Ronald M. Summers. Correcting class imbalances with self-training for improved universal lesion detection and tagging. In Medical Imaging 2023: Computer-Aided Diagnosis, 2023 (Vol. 12465, pp. 224-235). International Society for Optics and Photonics.

17. Varun Naga, Tejas Sudharshan Mathai, Angshuman Paul, & Ronald M. Summers (2022). Universal Lesion Detection and Classification using Limited Data and Weakly-Supervised Self-Training. In Workshop on Medical Image Learning with Limited and Noisy Data 2022 @ MICCAI 2022 (pp. 55-64) @ MICCAI, Springer.

18. Angshuman Paul, Thomas C. Shen, Yifan Peng, Zhiyong Lu, & Ronald M. Summers (2021, April). Learning Few-shot Chest X-ray Diagnosis Using Images from the Published Scientific Literature. In International Symposium on Biomedical Imaging (ISBI), 2021 (pp. 344-348). IEEE. 

19. Angshuman Paul, Thomas C. Shen, Niranjan Balachandar, Yuxing Tang, Yifan Peng, Zhiyong Lu, & Ronald M. Summers (2020). COMe-SEE: Cross-Modality Semantic Embedding Ensemble for Generalized Zero-Shot Diagnosis of Chest Radiographs. In Interpretable and Annotation-Efficient Learning for Medical Image Computing @ MICCAI, 2020 (pp. 103-111), Springer.

20. Angshuman Paul, Yu-Xing Tang, & Ronald M. Summers (2020, February). Fast Few-shot Transfer Learning for Disease Identification from Chest x-ray Images using Autoencoder Ensemble. In Medical Imaging 2020: Computer-Aided Diagnosis, 2020 (vol. 11314, p. 1131407). International Society for Optics and Photonics.

21. Sai A. Sriram, Angshuman Paul, Yingying Zhu, Veit Sandfort, Perry J. Pickhardt, & Ronald M. Summers (2020, February). Multilevel UNet for Pancreas Segmentation from Non-contrast CT Scans through Domain Adaptation. In Medical Imaging 2020: Computer-Aided Diagnosis, 2020 (Vol. 11314, p. 113140K). International Society for Optics and Photonics.

22. Angshuman Paul, Dipti Prasad Mukherjee, & Scott T. Acton (2019). Shape Based Speckle Removal for Ultrasound Image Segmentation. (ICIP), 2019 (pp. 3586-3590). IEEE. 

23. Angshuman Paul, Angshul Majumdar, & Dipti Prasad Mukherjee (2018). Discriminative Autoencoder. In IEEE International Conference on Image Processing (ICIP), 2018 (pp. 3049-3053). IEEE.

24. Angshuman Paul, & Dipti Prasad Mukherjee (2016, December). Reinforced Random Forest. In Indian Conference on Computer Vision, Graphics and Image Processing, (ICVGIP) (pp. 1-8). ACM. (2016, December). (*Best Paper Award) 

25. Angshuman Paul, & Dipti Prasad Mukherjee (2016, September). Gland Segmentation from Histology Images Using Informative Morphological Scale Space. In IEEE International Conference on Image Processing (ICIP), 2016 (pp. 4121-4125). IEEE. 

26. Angshuman Paul, Anisha Dey, Dipti Prasad Mukherjee, Jayanthi Sivaswamy, & Vijaya Tourani (2015, October). Regenerative Random Forest with Automatic Feature Selection to Detect Mitosis in Histopathological Breast Cancer Images. In International Conference on Medical Image Computing and Computer-Assisted Intervention (MICCAI), 2015, pp. 94-102. 

27. Angshuman Paul, & Dipti Prasad Mukherjee (2014, December). Enhanced Random Forest for Mitosis Detection. In Indian Conference on Computer Vision, Graphics and Image Processing, (ICVGIP) (pp. 1-8). ACM, 2014.

28. Ananda S. Chowdhury, Angshuman Paul, Filiz Bunyak, D. D. W. Cornelison, & K. Palaniappan (2012, September). Semi-automated Tracking of Muscle Satellite Cells in Brightfield Microscopy Video. In IEEE International Conference on Image Processing (ICIP), 2012 (pp. 2825-2828). 

29. Angshuman Paul, Nilotpal Bhattacharya, & Ananda S. Chowdhury (2012, December). Digit Recognition from Pressure Sensor Data Using Euler Number and Central Moments. In International Conference on Communications, Devices and Intelligent Systems (CODIS), 2012 (pp. 93-96). IEEE.