Hierarchical Prediction of Registration Misalignment Using a Convolutional LSTM: Application to Chest CT Scans

Hierarchical Prediction of Registration Misalignment Using a Convolutional LSTM: Application to Chest CT Scans

In this paper we propose a supervised method to predict registration misalignment using convolutional neural networks (CNNs). This task is casted to a classification problem with multiple classes of misalignment: “correct” 0-3 mm, “poor” 3-6 mm and &#x...

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Bibliographic Details
Main Authors: Hessam Sokooti, Sahar Yousefi, Mohamed S. Elmahdy, Boudewijn P. F. Lelieveldt, Marius Staring
Format: Article
Language:English
Published: IEEE 2021-01-01
Series:IEEE Access
Subjects:
Image registration
registration misalignment
convolutional neural networks
hierarchical classification
Online Access:https://ieeexplore.ieee.org/document/9408621/

Internet

https://ieeexplore.ieee.org/document/9408621/

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