Vision 20/20: Magnetic resonance imaging-guided attenuation correction in PET/MRI: Challenges, solutions, and opportunities.

By Abolfazl Mehranian, Hossein ARABI, Habib Zaidi. 2016

145 citations recorded by the source corpus.

Subfields: Biomedical Engineering, Radiology, Nuclear Medicine and Imaging

Citations in the corpus

• An overview of deep learning in medical imaging focusing on MRI (2018, neutral): “Deep learning is applied in radiotherapy [88], in PET-MRI attenuation correction [89,90], in radiomics [91,92] (see [93] for a review of radiomics related to radiooncology and medical physics), and for theranostics in neurosurgical imaging, combining confocal laser endomicroscopy with deep learning ”
• Advances in multimodal data fusion in neuroimaging: Overview, challenges, and novel orientation (2020, unknown): “In contrast, MRI data is correlated to proton density and magnetic relaxation properties of the tissues [387] .”