A5079069887- Advanced Neuroimaging Techniques and Applications
- MRI in cancer diagnosis
- Advanced MRI Techniques and Applications
- Fetal and Pediatric Neurological Disorders
- Radiomics and Machine Learning in Medical Imaging
- Functional Brain Connectivity Studies
- Medical Imaging Techniques and Applications
- Wildlife-Road Interactions and Conservation
- Peripheral Nerve Disorders
- Fire effects on ecosystems
- Wildlife Ecology and Conservation
Universidad de Valladolid
2022-2023
Hospital Clínic de Barcelona
2020
Universidad Politécnica de Madrid
2013
The lack of standardization intensity normalization methods and its unknown effect on the quantification output is recognized as a major drawback for harmonization brain FDG-PET protocols. aim this work ground truth-based evaluation different output. Realistic images were generated using Monte Carlo simulation from activity attenuation maps directly derived 25 healthy subjects (adding theoretical relative hypometabolisms 6 regions interest 5 hypometabolism levels). Single-subject statistical...
The objective of this study is to evaluate the efficacy deep learning (DL) techniques in improving quality diffusion MRI (dMRI) data clinical applications. aims determine whether use artificial intelligence (AI) methods medical images may result loss critical information and/or appearance false information. To assess this, focus was on angular resolution dMRI and a trial conducted migraine, specifically between episodic chronic migraine patients. number gradient directions had an impact...
AMURA (Apparent Measures Using Reduced Acquisitions) was originally proposed as a method to infer micro-structural information from single-shell acquisitions in diffusion MRI. It reduces the number of samples needed and computational complexity estimation properties tissues by assuming anisotropy is roughly independent on b-value. This simplification allows computation simplified expressions makes it compatible with standard acquisition protocols commonly used even clinical practice. The...
This work gathers the results of QuadD22 challenge, held in MICCAI 2022. We evaluate whether Deep Learning (DL) Techniques are able to improve quality diffusion MRI data clinical studies. To that end, we focused on a real study migraine, where differences between groups drastically reduced when using 21 gradient directions instead 61. Thus, asked participants augment dMRI acquired with only 61 via DL. The were evaluated TBSS which statistically compared episodic migraine chronic migraine.
The objective of this study is to evaluate the efficacy deep learning (DL) techniques in improving quality diffusion MRI (dMRI) data clinical applications. aims determine whether use artificial intelligence (AI) methods medical images may result loss critical information and/or hallucination false information. To assess this, focus was on angular resolution dMRI and a trial conducted migraine patients. number gradient directions had an impact white matter analysis results, with statistically...
Diffusion Tensor Imaging (DTI) is the most employed method to assess white matter properties using quantitative parameters derived from diffusion MRI, but it presents known limitations that restrict evaluation of complex structures. The objective this study was validate reliability and robustness complementary measures extracted with a novel approach, Apparent Measures Using Reduced Acquisitions (AMURA), typical MRI acquisition clinical context in comparison DTI application studies. Fifty...
Abstract Diffusion Tensor Imaging (DTI) is the most employed method to assess white matter properties using quantitative parameters derived from diffusion MRI, but it presents known limitations that restricts evaluation of complex structures. The objective this study was assessment complementary measures extracted with a novel approach, Apparent Measures Using Reduced Acquisitions (AMURA), in comparison DTI clinical studies. Fifty healthy controls, 51 episodic migraine and 56 chronic...
Validation in Deep Learning for enhancement of diffusion Magnetic Resonance Imaging results usually sticks to conventional image similarity metrics. Despite those results, further research on synthetic data may result discordance with the real one. In this paper we have compared 61 gradient directions against quasi-identical directions, obtained by subsampling ones, assessment differences between chronic and episodic migraine patients. Even high comparison metrics, t-test are not compelling....
We propose a method that can provide information about the anisotropy and orientation of diffusion in brain from only 3 orthogonal gradient directions without imposing additional assumptions. The is based on Diffusion Anisotropy (DiA) measures distance signal to its isotropic equivalent. original formulation Spherical Harmonics basis allows go down order estimate measure. In addition, an alternative simplification color-coding representation are also proposed. Acquisitions publicly available...