MRI-guided attenuation correction in torso PET/MRI: Assessment of segmentation-, atlas-, and deep learning-based approaches in the presence of outliers.

Journal: Magnetic resonance in medicine

Published Date: Sep 4, 2021

Abstract

PURPOSE: We compare the performance of three commonly used MRI-guided attenuation correction approaches in torso PET/MRI, namely segmentation-, atlas-, and deep learning-based algorithms.

Authors

Hossein Arabi

Division of Nuclear Medicine and Molecular Imaging, Geneva University Hospital, CH-1211, Geneva 4, Switzerland.
Habib Zaidi

Division of Nuclear Medicine and Molecular Imaging, Geneva University Hospital, CH-1211, Geneva 4, Switzerland. habib.zaidi@hcuge.ch.

Keywords

Algorithms Deep Learning Humans Image Processing, Computer-Assisted Magnetic Resonance Imaging Positron Emission Tomography Computed Tomography Positron-Emission Tomography Torso

External Resources

View on PubMed Access via DOI PubMed (34480771)

MRI-guided attenuation correction in torso PET/MRI: Assessment of segmentation-, atlas-, and deep learning-based approaches in the presence of outliers.

Abstract

Authors

Keywords

External Resources

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