Improved Consistency of Lung Nodule Categorization in CT Scans with Heterogeneous Slice Thickness by Deep Learning-Based 3D Super-Resolution

Improved Consistency of Lung Nodule Categorization in CT Scans with Heterogeneous Slice Thickness by Deep Learning-Based 3D Super-Resolution

<b>Background/Objectives</b>: Accurate volumetric assessment of lung nodules is an essential element of low-dose lung cancer screening programs. Current guidance recommends applying specific thresholds to measured nodule volume to make the following clinical decisions. In reality, howeve...

Full description

Saved in:
Bibliographic Details
Main Authors: Dongok Kim, Jae Hyung Park, Chang Hyun Lee, Young-Ju Kim, Jong Hyo Kim
Format: Article
Language:English
Published: MDPI AG 2024-12-01
Series:Diagnostics
Subjects:
computed tomography
deep learning
super-resolution
slice thickness
Online Access:https://www.mdpi.com/2075-4418/15/1/50
Tags: Add Tag
No Tags, Be the first to tag this record!

Internet

https://www.mdpi.com/2075-4418/15/1/50

Similar Items