H
Hossein Arabi
Researcher at Geneva College
Publications - 104
Citations - 1974
Hossein Arabi is an academic researcher from Geneva College. The author has contributed to research in topics: Medicine & Computer science. The author has an hindex of 20, co-authored 80 publications receiving 1120 citations. Previous affiliations of Hossein Arabi include University of Geneva & Tehran University of Medical Sciences.
Papers
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Vision 20/20: Magnetic resonance imaging-guided attenuation correction in PET/MRI: Challenges, solutions, and opportunities
TL;DR: The advantages and drawbacks of each approach for addressing the challenges of MR-based attenuation correction are comprehensively described and the opportunities brought by both MRI and PET imaging modalities for deriving accurate attenuation maps and improving PET quantification will be elaborated.
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Atlas-guided generation of pseudo-CT images for MRI-only and hybrid PET-MRI-guided radiotherapy treatment planning
TL;DR: A two-step (segmentation and fusion) atlas-based algorithm focusing on bone tissue identification to create a pseudo-CT image from conventional MRI sequences with improved bone extraction accuracy is proposed and is promising for potential use in PET AC and MRI-only or hybrid PET/MRI-guided RT treatment planning.
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Comparative study of algorithms for synthetic CT generation from MRI: Consequences for MRI-guided radiation planning in the pelvic region.
Hossein Arabi,Jason Dowling,Ninon Burgos,Xiao Han,Peter B. Greer,Nikolaos Koutsouvelis,Habib Zaidi +6 more
TL;DR: Machine learning and advanced atlas-based methods exhibited promising performance by achieving reliable organ segmentation and synthetic CT generation and the challenge of electron density estimation from MR images can be resolved with a clinically tolerable error.
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The promise of artificial intelligence and deep learning in PET and SPECT imaging.
TL;DR: In this article, the authors discuss the foremost applications of artificial intelligence (AI), particularly deep learning (DL) algorithms, in single-photon emission computed tomography (SPECT) and positron emission tomography(PET) imaging.
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Novel adversarial semantic structure deep learning for MRI-guided attenuation correction in brain PET/MRI
TL;DR: A novel sCT generation algorithm based on deep learning adversarial semantic structure (DL-AdvSS) is proposed for MRI-guided attenuation correction in brain PET/MRI, demonstrating competitive performance with respect to the state-of-the-art atlas-based technique.