Multi-class Classification and Gland Segmentation of Colorectal Cancer Tissues from Histopathology Images

Developed a comprehensive pipeline combining advanced image processing techniques, such as K-means clustering and Watershed algorithm, for precise gland segmentation. Implemented classification of colorectal cancer tissues into multiple categories using both traditional machine learning and deep learning models, achieving high accuracy and robustness in segmentation and classification tasks.

Keywords: Colorectal Cancer, Histopathology Image Classification, Gland Segmentation, Image Processing, Machine Learning, Deep Learning

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