Uncertainty-Guided Cross Attention Ensemble Mean Teacher for Semi-Supervised Medical Image Segmentation Meghana Karri, Amit Soni Arya, Koushik Biswas, Nicolò Gennaro, Vedat Cicek, Gorkem Durak, Yuri S. Velichko, Ulas Bagci Proceedings 2025 IEEE Winter Conference on Applications of Computer Vision Wacv 2025, 2025 This work proposes a novel framework, UncertaintyGuided Cross Attention Ensemble Mean Teacher (UGCEMT), for achieving state-of-the-art performance in semisupervised medical image segmentation. UG-CEMT leverages the strengths of co-training and knowledge distillation by combining a Cross-attention Ensemble Mean Teacher framework (CEMT) inspired by Vision Transformers (ViT) with uncertainty-guided consistency regularization and Sharpness-Aware Minimization emphasizing uncertainty. UG-CEMT improves semi-supervised performance while maintaining a consistent network architecture and task setting by fostering high disparity between sub-networks. Experiments demonstrate significant advantages over existing methods like Mean Teacher and Crosspseudo Supervision in terms of disparity, domain generalization, and medical image segmentation performance. UG-CEMT achieves state-of-the-art results on multi-center prostate MRI and cardiac MRI datasets, where object segmentation is particularly challenging. Our results show that using only 10% labeled data, UG-CEMT approaches the performance of fully supervised methods, demonstrating its effectiveness in exploiting unlabeled data for robust medical image segmentation. The code is publicly available at https://github.com/Meghnak13/UG-CEMT
Adaptive sparse modeling in spectral & spatial domain for compressed image restoration Amit Soni Arya, Susanta Mukhopadhyay Signal Processing, 2023 Block discrete cosine transform (BDCT) is an indispensable component of modern image and video coding standards, specifically for its decorrelation and superior energy compaction aspects. BDCT typically employs block-specific quantization, which results in unpleasant compression-blocking artifacts which predominates at low bit rates. The proposed method aims to minimize these blocking artifacts to generate high-quality images under the framework of the alternating direction method of multipliers (ADMM) optimization. The proposed method exploits the local structures identified and extracted via wavelet-patch-based sparse representation and non-local self-similarity identified and extracted via group-based sparse representation, which are subsequently combined optimally employing ADMM. Moreover, the method uses a Gaussian quantization noise model, which allows a more precise and reliable assessment. An adaptive regularization parameter is used, which integrates spectral and spatial domain sparse representations with multi-resolution dictionaries and PCA-based dictionary. The proposed algorithm improves the overall practicality of the process and outperforms existing methods in terms of objective measures like structural similarity index measure, peak signal-to-noise ratio and visual perception.
Sparse modeling for image inpainting: A multi-scale morphological patch-based k-SVD and group-based PCA AS Arya, S Mukhopadhyay Signal Processing: Image Communication 138, 117341 , 2025 2025 Citations: 3
Uncertainty-guided cross attention ensemble mean teacher for semi-supervised medical image segmentation M Karri, AS Arya, K Biswas, N Gennaro, V Cicek, G Durak, YS Velichko, ... Proceedings of the Winter Conference on Applications of Computer Vision … , 2025 2025 Citations: 4
Sparse Representation with Residual Learning Model for Medical Image AS Arya, S Mukhopadhyay Machine Learning, Image Processing, Network Security and Data Sciences: 5th … , 2024 2024
ADMM optimizer for integrating wavelet-patch and group-based sparse representation for image inpainting AS Arya, A Saha, S Mukhopadhyay The Visual Computer 40 (1), 345-372 , 2024 2024 Citations: 12
Sparse Representation with Residual Learning Model for Medical Image Classification AS Arya, S Mukhopadhyay International Conference on Machine Learning, Image Processing, Network … , 2023 2023
Deep sparse representation learning for multi-class image classification AS Arya, S Thakur, S Mukhopadhyay International Conference on Pattern Recognition and Machine Intelligence … , 2023 2023 Citations: 2
Adaptive sparse modeling in spectral & spatial domain for compressed image restoration AS Arya, S Mukhopadhyay Signal Processing, 109191 , 2023 2023 Citations: 9
Cyber fraud detection using evolving spiking neural network AS Arya, V Ravi, V Tejasviram, N Sengupta, N Kasabov 2016 11th international conference on industrial and information systems … , 2016 2016 Citations: 15
MOST CITED SCHOLAR PUBLICATIONS
Cyber fraud detection using evolving spiking neural network AS Arya, V Ravi, V Tejasviram, N Sengupta, N Kasabov 2016 11th international conference on industrial and information systems … , 2016 2016 Citations: 15
ADMM optimizer for integrating wavelet-patch and group-based sparse representation for image inpainting AS Arya, A Saha, S Mukhopadhyay The Visual Computer 40 (1), 345-372 , 2024 2024 Citations: 12
Adaptive sparse modeling in spectral & spatial domain for compressed image restoration AS Arya, S Mukhopadhyay Signal Processing, 109191 , 2023 2023 Citations: 9
Uncertainty-guided cross attention ensemble mean teacher for semi-supervised medical image segmentation M Karri, AS Arya, K Biswas, N Gennaro, V Cicek, G Durak, YS Velichko, ... Proceedings of the Winter Conference on Applications of Computer Vision … , 2025 2025 Citations: 4
Sparse modeling for image inpainting: A multi-scale morphological patch-based k-SVD and group-based PCA AS Arya, S Mukhopadhyay Signal Processing: Image Communication 138, 117341 , 2025 2025 Citations: 3
Deep sparse representation learning for multi-class image classification AS Arya, S Thakur, S Mukhopadhyay International Conference on Pattern Recognition and Machine Intelligence … , 2023 2023 Citations: 2
Sparse Representation with Residual Learning Model for Medical Image AS Arya, S Mukhopadhyay Machine Learning, Image Processing, Network Security and Data Sciences: 5th … , 2024 2024
Sparse Representation with Residual Learning Model for Medical Image Classification AS Arya, S Mukhopadhyay International Conference on Machine Learning, Image Processing, Network … , 2023 2023
