Deep Learning-Based Slice Thickness Reduction for Computer-Aided Detection of Lung Nodules in Thick-Slice CT

Deep Learning-Based Slice Thickness Reduction for Computer-Aided Detection of Lung Nodules in Thick-Slice CT

Background/Objectives: Computer-aided detection (CAD) systems for lung nodule detection often face challenges with 5 mm computed tomography (CT) scans, leading to missed nodules. This study assessed the efficacy of a deep learning-based slice thickness reduction technique from 5 mm to 1 mm to enhanc...

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Bibliographic Details
Main Authors: Jonghun Jeong, Doohyun Park, Jung-Hyun Kang, Myungsub Kim, Hwa-Young Kim, Woosuk Choi, Soo-Youn Ham
Format: Article
Language:English
Published: MDPI AG 2024-11-01
Series:Diagnostics
Subjects:
deep learning
computer-aided detection
lung nodule
slice thickness reduction
computed tomography
Online Access:https://www.mdpi.com/2075-4418/14/22/2558
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https://www.mdpi.com/2075-4418/14/22/2558

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