A curated, expert-labeled, AI-ready histopathological dataset consisting of 1,714 images obtained from 115 patients, explicitly designed to differentiate between OSCC and completely healthy oral tissue, which provides a robust framework for developing scalable deep learning tools optimized for early oral cancer screening.
Oral squamous cell carcinoma accounts for nearly 90% of all oral malignancies worldwide. While early detection is critical to improve the disappointed 35%–45% advanced-stage survival rate, manual histopathological evaluation remains a laborious process prone to intra-observer variability and physical strain. Artificial...
Salma Bahaa· Machine Learning for Biomedi...· 0 citations
This study presents a two-stage deep learning framework for multi-class tissue classification and pixel-level histopathological region segmentation, accompanied by a systematic comparison of state-of-the-art architectures at each stage.
Hadi Hasan, Safaa Salman, Lama Sleem et al.· 0 citations
The proposed framework demonstrated clinically meaningful performance for automated oral cancer detection and grading, with explainability analysis confirming alignment with established histopathological criteria, suggesting that such a framework have the potential to serve as a viable decision-support tool for ENT pra...
L. Rahul, Swagatika Pradhan· The Egyptian Journal of Otol...· 0 citations
BACKGROUND
Head and neck squamous cell carcinoma (HNSCC) is a common malignancy with increasing incidence. Histopathological assessment remains the diagnostic gold standard, but is labor-intensive and affected by a growing shortage of specialized pathologists. Limited availability of annotated data poses a major challe...
Till Nicke, Fleming Wolf-Eli Michelsen, J. Schäfer et al.· Journal of Oral Pathology &...· 0 citations
Cutaneous melanoma (CM) is a highly aggressive form of skin cancer requiring accurate subtype classification for effective prognosis and treatment. To address the scarcity of high-quality datasets, we curated 82 Hematoxylin & Eosin (H&E)-stained whole slide images (WSIs) from 32 patients in the Clinical Proteomic Tum...
Seongho Yoon, Byungeun Shon, So-yeon Kim et al.· Scientific Data· 0 citations
Oral Squamous Cell Carcinoma (OSCC) is a significant global health challenge where early and accurate detection is critical for improving patient outcomes. Histopathological examination is a method for diagnosing OSCC, but the issue is the labour, time spent and the observer variability. In this research, deep learning...
K. Arun· Natural Resources for Human...· 0 citations
We use cookies to run the site and, with your consent, for analytics and to show ads.
See our Cookie Policy.
