Development and performance evaluation of a deep learning lung nodule detection system.

ABSTRACT:

Background

Lung cancer is the leading cause of cancer-related deaths throughout the world. Chest computed tomography (CT) is now widely used in the screening and diagnosis of lung cancer due to its effectiveness. Radiologists must identify each small nodule shadow from 3D volume images, which is very burdensome and often results in missed nodules. To address these challenges, we developed a computer-aided detection (CAD) system that automatically detects lung nodules in CT images.

Methods

A total of 1997 chest CT scans were collected for algorithm development. The algorithm was designed using deep learning technology. In addition to evaluating detection performance on various public datasets, its robustness to changes in radiation dose was assessed by a phantom study. To inv

SUBMITTER: Katase S 

PROVIDER: S-EPMC9682774 | biostudies-literature | 2022 Nov

REPOSITORIES: biostudies-literature