Angshuman Paul

Orcid: 0000-0002-0935-0256

According to our database1, Angshuman Paul authored at least 32 papers between 2012 and 2024.

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Bibliography

2024
Generalizable diagnosis of chest radiographs through attention-guided decomposition of images utilizing self-consistency loss.
Comput. Biol. Medicine, 2024

Label-Guided Coreset Generation for Computationally Efficient Chest X-Ray Diagnosis.
Proceedings of the IEEE International Symposium on Biomedical Imaging, 2024

An Ensemble of Well-Trained Students Can Perform Almost as Good as a Teacher for Chest X-Ray Diagnosis.
Proceedings of the IEEE International Symposium on Biomedical Imaging, 2024

2023
ViViD: View Prediction of Online Video Through Deep Neural Network-Based Analysis of Subjective Video Attributes.
IEEE Trans. Broadcast., March, 2023

Few-shot Diagnosis of Chest x-rays Using an Ensemble of Random Discriminative Subspaces.
CoRR, 2023

Anomaly Guided Generalizable Super-Resolution of Chest X-Ray Images Using Multi-level Information Rendering.
Proceedings of the Deep Generative Models - Third MICCAI Workshop, 2023

Multi-task Learning for Few-Shot Differential Diagnosis of Breast Cancer Histopathology Images.
Proceedings of the Medical Image Learning with Limited and Noisy Data, 2023

Correcting class imbalances with self-training for improved universal lesion detection and tagging.
Proceedings of the Medical Imaging 2023: Computer-Aided Diagnosis, 2023

3D universal lesion detection and tagging in CT with self-training.
Proceedings of the Medical Imaging 2023: Computer-Aided Diagnosis, 2023

Federated learning using multi-institutional data for generalizable chest x-ray diagnosis.
Proceedings of the Medical Imaging 2023: Computer-Aided Diagnosis, 2023

Segmentation and Classification-Based Diagnosis of Tumors From Breast Ultrasound Images Using Multibranch Unet.
Proceedings of the IEEE International Conference on Image Processing, 2023

2022
Detail preserving conditional random field as 2-D RNN for gland segmentation in histology images.
Pattern Recognit. Lett., 2022

Universal Lesion Detection and Classification Using Limited Data and Weakly-Supervised Self-training.
Proceedings of the Medical Image Learning with Limited and Noisy Data, 2022

2021
Generalized Zero-Shot Chest X-Ray Diagnosis Through Trait-Guided Multi-View Semantic Embedding With Self-Training.
IEEE Trans. Medical Imaging, 2021

Discriminative ensemble learning for few-shot chest x-ray diagnosis.
Medical Image Anal., 2021

Learning Few-Shot Chest X-Ray Diagnosis Using Images From The Published Scientific Literature.
Proceedings of the 18th IEEE International Symposium on Biomedical Imaging, 2021

2020
Deterministic dropout for deep neural networks using composite random forest.
Pattern Recognit. Lett., 2020

COMe-SEE: Cross-modality Semantic Embedding Ensemble for Generalized Zero-Shot Diagnosis of Chest Radiographs.
Proceedings of the Interpretable and Annotation-Efficient Learning for Medical Image Computing, 2020

Multilevel UNet for pancreas segmentation from non-contrast CT scans through domain adaptation.
Proceedings of the Medical Imaging 2020: Computer-Aided Diagnosis, 2020

Fast few-shot transfer learning for disease identification from chest x-ray images using autoencoder ensemble.
Proceedings of the Medical Imaging 2020: Computer-Aided Diagnosis, 2020

2019
Speckle Removal Using Diffusion Potential for Optical Coherence Tomography Images.
IEEE J. Biomed. Health Informatics, 2019

Reinforced quasi-random forest.
Pattern Recognit., 2019

Shape Based Speckle Removal for Ultrasound Image Segmentation.
Proceedings of the 2019 IEEE International Conference on Image Processing, 2019

2018
Improved Random Forest for Classification.
IEEE Trans. Image Process., 2018

Calculation of phase fraction in steel microstructure images using random forest classifier.
IET Image Process., 2018

Discriminative Autoencoder.
Proceedings of the 2018 IEEE International Conference on Image Processing, 2018

2016
Reinforced random forest.
Proceedings of the Tenth Indian Conference on Computer Vision, 2016

Gland segmentation from histology images using informative morphological scale space.
Proceedings of the 2016 IEEE International Conference on Image Processing, 2016

2015
Mitosis Detection for Invasive Breast Cancer Grading in Histopathological Images.
IEEE Trans. Image Process., 2015

Regenerative Random Forest with Automatic Feature Selection to Detect Mitosis in Histopathological Breast Cancer Images.
Proceedings of the Medical Image Computing and Computer-Assisted Intervention - MICCAI 2015, 2015

2014
Enhanced Random Forest for Mitosis Detection.
Proceedings of the 2014 Indian Conference on Computer Vision, 2014

2012
Semi-automated tracking of muscle satellite cells in brightfield microscopy video.
Proceedings of the 19th IEEE International Conference on Image Processing, 2012


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