Deep learning models for CT image classification: a comprehensive literature review.

ABSTRACT:

Background and objective

Computed tomography (CT) imaging plays a crucial role in the early detection and diagnosis of life-threatening diseases, particularly in respiratory illnesses and oncology. The rapid advancement of deep learning (DL) has revolutionized CT image analysis, enhancing diagnostic accuracy and efficiency. This review explores the impact of advanced DL methodologies in CT imaging, with a particular focus on their applications in coronavirus disease 2019 (COVID-19) detection and lung nodule classification.

Methods

A comprehensive literature search was conducted, examining the evolution of DL architectures in medical imaging from conventional convolutional neural networks (CNNs) to sophisticated foundational models (FMs). We reviewed publications from major d

SUBMITTER: Ahmad IS 

PROVIDER: S-EPMC11744119 | biostudies-literature | 2025 Jan

REPOSITORIES: biostudies-literature