KD_ConvNeXt: knowledge distillation-based image classification of lung tumor surgical specimen sections.

ABSTRACT: Introduction: Lung cancer is currently among the most prevalent and lethal cancers in the world in terms of incidence and fatality rates. In clinical practice, identifying the specific subtypes of lung cancer is essential in diagnosing and treating lung lesions. Methods: This paper aims to collect histopathological section images of lung tumor surgical specimens to construct a clinical dataset for researching and addressing the classification problem of specific subtypes of lung tumors. Our method proposes a teacher-student network architecture based on a knowledge distillation mechanism for the specific subtype classification of lung tumor histopathological section images to assist clinical applications, namely KD_ConvNeXt. The proposed approach enables the student network (

SUBMITTER: Zheng Z 

PROVIDER: S-EPMC10544998 | biostudies-literature | 2023

REPOSITORIES: biostudies-literature