ArticleMedical physics2012
MR∕PET quantification tools: registration, segmentation, classification, and MR-based attenuation correction.
Article in Medical physics, 2012. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 34 papers.
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Who cites it
34 citing papers in PubMed, 49 citations in OpenAlex.
- A two-stage PET/MRI attenuation-correction workflow for pseudo-CT and AC PET synthesis with GUI-based inference.Medical & biological engineering & computing · 2026Article
- MR Image-Based Attenuation Correction of Brain PET Imaging: Review of Literature on Machine Learning Approaches for Segmentation.Journal of digital imaging · 2020Review
- Machine learning in quantitative PET: A review of attenuation correction and low-count image reconstruction methods.Physica medica : PM : an international journal devoted to the applications of physics to medicine and biology : official journal of the Italian Association of Biomedical Physics (AIFB) · 2020Review
- Deep learning-based attenuation correction in the absence of structural information for whole-body positron emission tomography imaging.Physics in medicine and biology · 2020Article
- Synthetic CT generation from non-attenuation corrected PET images for whole-body PET imaging.Physics in medicine and biology · 2019Article
- MRI-based attenuation correction for brain PET/MRI based on anatomic signature and machine learning.Physics in medicine and biology · 2019Article
- Accurate hybrid template-based and MR-based attenuation correction using UTE images for simultaneous PET/MR brain imaging applications.BMC medical imaging · 2018Article
- Use of black-bone MRI in the diagnosis of the patients with posterior plagiocephaly.Child's nervous system : ChNS : official journal of the International Society for Pediatric Neurosurgery · 2018Article
- A combined learning algorithm for prostate segmentation on 3D CT images.Medical physics · 2017Article
- A random walk-based segmentation framework for 3D ultrasound images of the prostate.Medical physics · 2017Article
- On the accuracy and reproducibility of a novel probabilistic atlas-based generation for calculation of head attenuation maps on integrated PET/MR scanners.European journal of nuclear medicine and molecular imaging · 2017Article
- A multi-centre evaluation of eleven clinically feasible brain PET/MRI attenuation correction techniques using a large cohort of patients.NeuroImage · 2017Article
- Deep Learning based Classification for Head and Neck Cancer Detection with Hyperspectral Imaging in an Animal Model.Proceedings of SPIE--the International Society for Optical Engineering · 2017Article
- A supervoxel-based segmentation method for prostate MR images.Medical physics · 2017Article
- Pseudo CT Estimation from MRI Using Patch-based Random Forest.Proceedings of SPIE--the International Society for Optical Engineering · 2017Article
- Automatic segmentation of the prostate on CT images using deep learning and multi-atlas fusion.Proceedings of SPIE--the International Society for Optical Engineering · 2017Article
- One registration multi-atlas-based pseudo-CT generation for attenuation correction in PET/MRI.European journal of nuclear medicine and molecular imaging · 2016Article
- Computer-aided Detection of Prostate Cancer with MRI: Technology and Applications.Academic radiology · 2016Review
- MR Imaging-Guided Attenuation Correction of PET Data in PET/MR Imaging.PET clinics · 2016Review
- Superpixel-Based Segmentation for 3D Prostate MR Images.IEEE transactions on medical imaging · 2016Article
Corrections and comments
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Authors and funding
9 authors at 2 institutions in 1 country.
Funding
Abstract
purposeCombined MR∕PET is a relatively new, hybrid imaging modality. A human MR∕PET prototype system consisting of a Siemens 3T Trio MR and brain PET insert was installed and tested at our institution. Its present design does not offer measured attenuation correction (AC) using traditional transmission imaging. This study is the development of quantification tools including MR-based AC for quantification in combined MR∕PET for brain imaging.
methodsThe developed quantification tools include image registration, segmentation, classification, and MR-based AC. These components were integrated into a single scheme for processing MR∕PET data. The segmentation method is multiscale and based on the Radon transform of brain MR images. It was developed to segment the skull on T1-weighted MR images. A modified fuzzy C-means classification scheme was developed to classify brain tissue into gray matter, white matter, and cerebrospinal fluid. Classified tissue is assigned an attenuation coefficient so that AC factors can be generated. PET emission data are then reconstructed using a three-dimensional ordered sets expectation maximization method with the MR-based AC map. Ten subjects had separate MR and PET scans. The PET with [(11)C]PIB was acquired using a high-resolution research tomography (HRRT) PET. MR-based AC was compared with transmission (TX)-based AC on the HRRT. Seventeen volumes of interest were drawn manually on each subject image to compare the PET activities between the MR-based and TX-based AC methods.
resultsFor skull segmentation, the overlap ratio between our segmented results and the ground truth is 85.2 ± 2.6%. Attenuation correction results from the ten subjects show that the difference between the MR and TX-based methods was <6.5%.
conclusionsMR-based AC compared favorably with conventional transmission-based AC. Quantitative tools including registration, segmentation, classification, and MR-based AC have been developed for use in combined MR∕PET.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.