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Habib Zaidi

Researcher at University Medical Center Groningen

Publications -  557
Citations -  15951

Habib Zaidi is an academic researcher from University Medical Center Groningen. The author has contributed to research in topics: Imaging phantom & Correction for attenuation. The author has an hindex of 62, co-authored 513 publications receiving 13563 citations. Previous affiliations of Habib Zaidi include Johns Hopkins University & University of Southern Denmark.

Papers
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Whole-body bone segmentation from MRI for PET/MRI attenuation correction using shape- based averaging

Hossein Arabi, +1 more
- 01 Nov 2016 - 
TL;DR: The performance of shape-based averaging technique for whole-body bone segmentation from MRI in the context of MRI-guided attenuation correction (MRAC) in hybrid PET/MRI was evaluated and was enhanced through application of local atlas weighting or regularization schemes (L-STAPLE and L-Shp).
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Is radionuclide transmission scanning obsolete for dual-modality PET/CT systems?

Habib Zaidi
- 16 Jan 2007 - 
TL;DR: It is the role of medical physicists providing physics support to clinical PET facilities and involved in today's biomedical imaging research enterprise to debate important issues related to design aspects of this technology and optimal data acquisition and processing protocols with the aim of improving image quality and obtaining accurate quantitative measures.
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MR-guided joint reconstruction of activity and attenuation in brain PET-MR.

Abolfazl Mehranian, +2 more
- 15 Nov 2017 - 
TL;DR: The proposed P‐MLAA++ algorithm provided simultaneous partial volume and attenuation corrections with only a minor compromise of PET quantification and significantly improves the quantitative accuracy of PET images.
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Experimental assessment of the influence of beam hardening filters on image quality and patient dose in volumetric 64-slice X-ray CT scanners

Mohammad Reza Ay, +6 more
- 01 May 2013 - 
TL;DR: The results seem to indicate that an optimum filter for high kVp acquisitions, routinely used in cardiovascular imaging, should be 0.5mm copper or 4mm aluminium minimum, which is a good compromise between image quality and patient dose.
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Deep learning-based metal artefact reduction in PET/CT imaging

Hossein Arabi, +1 more
- 10 Feb 2021 - 
TL;DR: In this paper, the authors investigated the potential of deep learning-based metal artefact reduction (MAR) in quantitative PET/CT imaging, and proposed a DLI-MAR approach to improve CT-based attenuation and scatter correction.