H
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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Journal ArticleDOI
Computed tomography-based attenuation correction in neurological positron emission tomography: evaluation of the effect of the X-ray tube voltage on quantitative analysis.
Mohammad Reza Ay,Habib Zaidi +1 more
TL;DR: The use of a single calibration curve acquired under standard imaging conditions does not affect, to a visible or measurable extent, neurological PET images reconstructed using CTAC when CT images are acquired in different conditions.
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Fully Automated Gross Tumor Volume Delineation From PET in Head and Neck Cancer Using Deep Learning Algorithms.
TL;DR: In this paper, three state-of-the-art deep learning algorithms combined with 8 different loss functions for PET image segmentation were evaluated on an external validation set of head and neck cancer (HNC) patients.
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Evaluating the Application of Tissue-Specific Dose Kernels Instead of Water Dose Kernels in Internal Dosimetry: A Monte Carlo Study.
TL;DR: A novel technique is proposed considering tissue-specific dose kernels in the dose calculation algorithm that potentially enables patient-specific dosimetry and improves estimation of the average absorbed dose of 90Y in a tumor located in lung, bone, and soft tissue interface by 6.98% compared with the conventional methods.
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Measurement of scattered radiation in a volumetric 64-slice CT scanner using three experimental techniques
TL;DR: Although the three compared methods present a reasonable accuracy for calculation of the scattered profile in the region corresponding to the object, the collimator shadow method is by far the most accurate empirical technique.
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Assessment of CT dose to the fetus and pregnant female patient using patient-specific computational models
TL;DR: The methodology for construction of personalised computational models can be exploited to estimate the patient-specific radiation dose from CT imaging procedures and the dosimetric data can be used for assessment of the radiation risks to pregnant patients and the foetus from various CT scanning protocols, thus guiding the decision-making process.