Histopathology image classification: highlighting the gap between manual analysis and AI automation.

ABSTRACT: The field of histopathological image analysis has evolved significantly with the advent of digital pathology, leading to the development of automated models capable of classifying tissues and structures within diverse pathological images. Artificial intelligence algorithms, such as convolutional neural networks, have shown remarkable capabilities in pathology image analysis tasks, including tumor identification, metastasis detection, and patient prognosis assessment. However, traditional manual analysis methods have generally shown low accuracy in diagnosing colorectal cancer using histopathological images. This study investigates the use of AI in image classification and image analytics using histopathological images using the histogram of oriented gradients method. The study develops an

SUBMITTER: Dogan RS 

PROVIDER: S-EPMC10827850 | biostudies-literature | 2023

REPOSITORIES: biostudies-literature