Advances in multimodal data fusion in neuroimaging: overview, challenges, and novel orientation
Multimodal fusion in neuroimaging combines data from multiple imaging modalities to
overcome the fundamental limitations of individual modalities. Neuroimaging fusion can …
overcome the fundamental limitations of individual modalities. Neuroimaging fusion can …
Vision 20/20: magnetic resonance imaging‐guided attenuation correction in PET/MRI: challenges, solutions, and opportunities
Attenuation correction is an essential component of the long chain of data correction
techniques required to achieve the full potential of quantitative positron emission …
techniques required to achieve the full potential of quantitative positron emission …
Deep learning MR imaging–based attenuation correction for PET/MR imaging
Purpose To develop and evaluate the feasibility of deep learning approaches for magnetic
resonance (MR) imaging–based attenuation correction (AC)(termed deep MRAC) in brain …
resonance (MR) imaging–based attenuation correction (AC)(termed deep MRAC) in brain …
Multimodal MR synthesis via modality-invariant latent representation
A Chartsias, T Joyce, MV Giuffrida… - IEEE transactions on …, 2017 - ieeexplore.ieee.org
We propose a multi-input multi-output fully convolutional neural network model for MRI
synthesis. The model is robust to missing data, as it benefits from, but does not require …
synthesis. The model is robust to missing data, as it benefits from, but does not require …
Unsupervised MR-to-CT synthesis using structure-constrained CycleGAN
Synthesizing a CT image from an available MR image has recently emerged as a key goal
in radiotherapy treatment planning for cancer patients. CycleGANs have achieved promising …
in radiotherapy treatment planning for cancer patients. CycleGANs have achieved promising …
Estimating CT image from MRI data using structured random forest and auto-context model
Computed tomography (CT) imaging is an essential tool in various clinical diagnoses and
radiotherapy treatment planning. Since CT image intensities are directly related to positron …
radiotherapy treatment planning. Since CT image intensities are directly related to positron …
[HTML][HTML] A multi-centre evaluation of eleven clinically feasible brain PET/MRI attenuation correction techniques using a large cohort of patients
Aim To accurately quantify the radioactivity concentration measured by PET, emission data
need to be corrected for photon attenuation; however, the MRI signal cannot easily be …
need to be corrected for photon attenuation; however, the MRI signal cannot easily be …
[HTML][HTML] DiCyc: GAN-based deformation invariant cross-domain information fusion for medical image synthesis
Cycle-consistent generative adversarial network (CycleGAN) has been widely used for cross-
domain medical image synthesis tasks particularly due to its ability to deal with unpaired …
domain medical image synthesis tasks particularly due to its ability to deal with unpaired …
Random forest regression for magnetic resonance image synthesis
By choosing different pulse sequences and their parameters, magnetic resonance imaging
(MRI) can generate a large variety of tissue contrasts. This very flexibility, however, can yield …
(MRI) can generate a large variety of tissue contrasts. This very flexibility, however, can yield …
Multimodal MR image synthesis using gradient prior and adversarial learning
In magnetic resonance imaging (MRI), several images can be obtained using different
imaging settings (eg T1, T2, DWI, and Flair). These images have similar anatomical …
imaging settings (eg T1, T2, DWI, and Flair). These images have similar anatomical …