Development and Validation of a Deep-Learning-Based Algorithm for Detecting and Classifying Metallic Implants in Abdominal and Spinal CT Topograms

Development and Validation of a Deep-Learning-Based Algorithm for Detecting and Classifying Metallic Implants in Abdominal and Spinal CT Topograms

Purpose: To develop and validate a deep-learning-based algorithm (DLA) that is designed to segment and classify metallic objects in topograms of abdominal and spinal CT. Methods: DLA training for implant segmentation and classification was based on a U-net-like architecture with 263 annotated hip im...

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Bibliographic Details
Main Authors: Moon-Hyung Choi, Joon-Yong Jung, Zhigang Peng, Stefan Grosskopf, Michael Suehling, Christian Hofmann, Seongyong Pak
Format: Article
Language:English
Published: MDPI AG 2024-03-01
Series:Diagnostics
Subjects:
deep learning
computed tomography
metal detection
metallic implants
topogram
Online Access:https://www.mdpi.com/2075-4418/14/7/668

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