29 citations · 123 across the 24 of their papers we have counts for
7 papers · 1 filter
When CNNs Outperform Transformers and Mambas: Revisiting Deep Architectures for Dental Caries Segmentation
Aashish Ghimire, Jun Zeng, Roshan Paudel +6
Accurate identification and segmentation of dental caries in panoramic radiographs are critical for early diagnosis and effective treatment planning. Automated segmentation remains…
SRMA-Mamba: Spatial Reverse Mamba Attention Network for Pathological Liver Segmentation in MRI Volumes
Jun Zeng, Quoc-Huy Trinh, Deepak Ranjan Nayak +3
Liver cirrhosis plays a critical role in the prognosis of chronic liver disease. Early detection and timely intervention are essential for reducing mortality rates. However, the in…
PolypDB: A Curated Multi-Center Dataset for Development of AI Algorithms in Colonoscopy
Debesh Jha, Nikhil Kumar Tomar, Vanshali Sharma +19
Colonoscopy is the primary method for examination, detection, and removal of polyps. However, challenges such as variations among the endoscopists' skills, bowel quality preparatio…
Transformer-Enhanced Iterative Feedback Mechanism for Polyp Segmentation
Nikhil Kumar Tomar, Debesh Jha, Koushik Biswas +4
Colorectal cancer (CRC) is the third most common cause of cancer diagnosed in the United States and the second leading cause of cancer-related death among both genders. Notably, CR…
Prototype Learning for Out-of-Distribution Polyp Segmentation
Nikhil Kumar Tomar, Debesh Jha, Ulas Bagci
Existing polyp segmentation models from colonoscopy images often fail to provide reliable segmentation results on datasets from different centers, limiting their applicability. Our…
Assessing generalisability of deep learning-based polyp detection and segmentation methods through a computer vision challenge
Sharib Ali, Noha Ghatwary, Debesh Jha +29
Polyps are well-known cancer precursors identified by colonoscopy. However, variability in their size, location, and surface largely affect identification, localisation, and charac…
FANet: A Feedback Attention Network for Improved Biomedical Image Segmentation
Nikhil Kumar Tomar, Debesh Jha, Michael A. Riegler +5
The increase of available large clinical and experimental datasets has contributed to a substantial amount of important contributions in the area of biomedical image analysis. Imag…