Faster and Better: How Anomaly Detection Can Accelerate and Improve Reporting of Head Computed Tomography

Faster and Better: How Anomaly Detection Can Accelerate and Improve Reporting of Head Computed Tomography

Background: Most artificial intelligence (AI) systems are restricted to solving a pre-defined task, thus limiting their generalizability to unselected datasets. Anomaly detection relieves this shortfall by flagging all pathologies as deviations from a learned norm. Here, we investigate whether diagn...

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Bibliographic Details
Main Authors: Tom Finck, Julia Moosbauer, Monika Probst, Sarah Schlaeger, Madeleine Schuberth, David Schinz, Mehmet Yiğitsoy, Sebastian Byas, Claus Zimmer, Franz Pfister, Benedikt Wiestler
Format: Article
Language:English
Published: MDPI AG 2022-02-01
Series:Diagnostics
Subjects:
machine learning
neuroradiology
computed tomography
decision support
anomaly detection
classification
Online Access:https://www.mdpi.com/2075-4418/12/2/452

Internet

https://www.mdpi.com/2075-4418/12/2/452

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