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Author

Anita Gupta

Chitkara School of Health Sciences, Chitkara University, Punjab, India
3 articles in our journals

Articles where this person is an author, newest first. People are matched by their name as printed (no ORCID iD is recorded for them), not by name alone; search the name as text to find namesakes too.

Research ArticleOpen accessRIA-ViT: A Residual Inception Atrous Vision Transformer for Detection of Gallbladder Cancer from CT ImagesAbhishek Sehrawat, Anita Gupta, Vishnupriya, Varun P. GopiGallbladder Cancer (GBC) is a rare but highly aggressive malignancy of the biliary system. In early-stage gallbladder cancer, there are neither overt symptoms nor specific signs. In most patients, it is diagnosed late, resulting in poor outcomes. Even when imaging is available, diagnosing GBC remains difficult because its features overlap with those of non-neoplastic gallbladder pathologies. Furthermore, the overlap between … …Journal of Computer Science, Vol. 22, Issue 10 · 6 Oct 2026 · 413 accessesView PDFCite
Research ArticleOpen accessA Detailed Preserving Medical Image Denoising Using Cluster-Wise PCA Thresholding and Iterative Mean FilteringMohit Sharma, Ayush Dogra, Anita Gupta et al.Image denoising is a vital process in medical imaging that involves removing noise or distortions introduced during image acquisition. Random noise can degrade image quality and reduce contrast, making accurate analysis more challenging. This paper presents a detail-preserving medical image denoising framework based on a hybrid methodology that combines cluster-wise Principal Component Analysis (PCA) thresholding with Iterative Mean Filtering (IMF). … …Journal of Computer Science, Vol. 22, Issue 4 · 18 Apr 2026 · 1,787 accessesView PDFCite
Research ArticleOpen accessA Comprehensive Review of Medical Image Denoising: Techniques, Challenges, Applications and Future DirectionsMohit Sharma, Ayush Dogra, Anita Gupta et al.The concept of noise reduction in medical images plays a vital role in improving image quality and accuracy associated with diagnosis, and facilitating reliable automated analysis. This survey presents a structured overview of medical image denoising, beginning with foundational definitions and noise models for modalities such as MRI and CT. We critically evaluate persistent gaps, including the limited generalizability of … …Journal of Computer Science, Vol. 22, Issue 3 · 28 Mar 2026 · 1,849 accessesView PDFCite