CRC-HGD: A Histopathological Image Dataset for Grading Colorectal Cancer
Colorectal cancer (CRC) is the third most common cancer worldwide and the second leading cause of cancer-related deaths globally, with approximately 1,926,425 new cases and 904,019 deaths reported in 2022. Accurate histologic grading plays a critical role in prognosis and treatment planning for colorectal adenocarcinoma. In recent years, artificial intelligence and its subcategories, including machine learning and deep learning, have been increasingly employed for automated cancer detection and classification. An appropriate and well-organized dataset is the essential first step to achieve thi
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- FuzzySimilar title/name (fuzzy) · 59%Tongyi-MAI/Z-Image-Turbo →
“Fuzzy title match (0.73): “CRC-HGD: A Histopathological Image Dataset for Grading Color” ≈ “Tongyi-MAI/Z-Image-Turbo””
- LinkedLinked via arxiv author · 85%Elham Amjadi →
“CRC-HGD: A Histopathological Image Dataset for Grading Colorectal Cancer”
- LinkedLinked via arxiv author · 85%Amin Bahreini →
“CRC-HGD: A Histopathological Image Dataset for Grading Colorectal Cancer”
- LinkedLinked via arxiv author · 85%Sayed Mohammad Hasan Emami →
“CRC-HGD: A Histopathological Image Dataset for Grading Colorectal Cancer”
- LinkedLinked via arxiv author · 85%Sayyed Mohammadreza Hakimian →
“CRC-HGD: A Histopathological Image Dataset for Grading Colorectal Cancer”