A hybrid framework for enhanced segmentation and classification of colorectal cancer histopathology

The proposed hybrid design proves to be a robust tool for the automated analysis of histopathological features in CRC, showing significant promise for improving diagnostic accuracy and efficiency in clinical settings.

Authors

B. Venkataramana
M. D. Aaseegha

Institutions

Vellore Institute of Technology University (IN)

Publication Details

Journal: Frontiers in Artificial Intelligence
Published: 2025-10-14
DOI: https://doi.org/10.3389/frai.2025.1647074
Primary Topic: AI in cancer detection
Type: article
Field-Weighted Citation Impact: 0.00

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article

A hybrid framework for enhanced segmentation and classification of colorectal cancer histopathology

B. Venkataramana, M. D. Aaseegha

Oct 14, 2025

Frontiers in Artificial Intelligence

AI in cancer detection

article

A hybrid framework for enhanced segmentation and classification of colorectal cancer histopathology

B. Venkataramana, M. D. Aaseegha

October 14, 2025article en

Abstract

Frontiers in Artificial IntelligenceVol. 8

Vellore Institute of Technology University (IN)

Openalex Percentile: Top 85%

AI in cancer detection

DOI Open Access PDF OpenAlex

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A hybrid framework for enhanced segmentation and classification of colorectal cancer histopathology — B. Venkataramana, M. D. Aaseegha · Frontiers in Artificial Intelligence (2025) | TGRS Research Map | TGRS