Colorectal Cancer Segmentation with Adaptive Augmentation and Multi-Resolution Ensemble Models
Colorectal cancer (CRC) is the second most deadly and third most common cancer, and the leading cause of death among gastrointestinal cancers. Early diagnosis is crucial for the treatment of this cancer and increasing the survival rates. Although CRC is more common in developed regions, its occurrence is also increasing in developing regions as well. CRC diagnosis relies on histopathology assessment post-biopsy. Automated deep learning algorithms can significantly reduce diagnosis time, enhancing efficiency and supporting timely clinical decisions. We present an automated segmentation pipeline for whole-slide histopathology images that labels tumor grades 1-3 and normal mucosa. It utilize...
| Authors | Ümit Mert Çağlar, Alptekin Temizel |
|---|---|
| Primary category | eess.IV |
| Published | 29 September 2026 |
| Last updated at source | 29 September 2026 |
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