A5072387429- Radiomics and Machine Learning in Medical Imaging
- Advanced MRI Techniques and Applications
- Medical Imaging Techniques and Applications
- Liver Disease Diagnosis and Treatment
- MRI in cancer diagnosis
- Radiation Dose and Imaging
- Hepatocellular Carcinoma Treatment and Prognosis
- Advanced X-ray and CT Imaging
- Radiology practices and education
- Liver Disease and Transplantation
- Artificial Intelligence in Healthcare and Education
- AI in cancer detection
- Functional Brain Connectivity Studies
- Medical Image Segmentation Techniques
- Glioma Diagnosis and Treatment
- Advanced Neuroimaging Techniques and Applications
- Schizophrenia research and treatment
- Neuroblastoma Research and Treatments
- Atomic and Subatomic Physics Research
- Sarcoma Diagnosis and Treatment
- Cerebrospinal fluid and hydrocephalus
- Spine and Intervertebral Disc Pathology
- Lung Cancer Diagnosis and Treatment
- Medical Imaging and Analysis
- Traumatic Brain Injury and Neurovascular Disturbances
Hospital Universitari i Politècnic La Fe
2016-2025
Instituto de Investigación Sanitaria La Fe
2016-2025
Real Academia Española
2018-2024
University of Cologne
2024
Stanford University
2024
University of California System
2024
University of California, San Francisco
2024
University of Crete
2024
University Hospital of Heraklion
2024
Parc Científic de la Universitat de València
2024
To adapt the so-called nonlocal means filter to deal with magnetic resonance (MR) images spatially varying noise levels (for both Gaussian and Rician distributed noise).Most filtering techniques assume an equal distribution across image. When this assumption is not met, resulting becomes suboptimal. This case of MR levels, such as those obtained by parallel imaging (sensitivity-encoded), intensity inhomogeneity-corrected images, or surface coil-based acquisitions. We propose a new method...
Abstract Purpose To propose a new quality scoring tool, METhodological RadiomICs Score (METRICS), to assess and improve research of radiomics studies. Methods We conducted an online modified Delphi study with group international experts. It was performed in three consecutive stages: Stage#1, item preparation; Stage#2, panel discussion among EuSoMII Auditing Group members identify the items be voted; Stage#3, four rounds exercise by panelists determine eligible for METRICS their weights. The...
Removing the bias and variance of multicentre data has always been a challenge in large scale digital healthcare studies, which requires ability to integrate clinical features extracted from acquired by different scanners protocols improve stability robustness. Previous studies have described various computational approaches fuse single modality datasets. However, these surveys rarely focused on evaluation metrics lacked checklist for harmonisation studies. In this systematic review, we...
Despite major advances in artificial intelligence (AI) research for healthcare, the deployment and adoption of AI technologies remain limited clinical practice. This paper describes FUTURE-AI framework, which provides guidance development trustworthy tools healthcare. The Consortium was founded 2021 comprises 117 interdisciplinary experts from 50 countries representing all continents, including scientists, researchers, biomedical ethicists, social scientists. Over a two year period,...
Ovarian hyperstimulation syndrome (OHSS) results from increased vascular permeability (VP) caused by ovarian hypersecretion of endothelial growth factor (VEGF), which activates its receptor-2. In animals, the dopamine receptor 2 agonist cabergoline (Cb2) inactivates VEGF receptor-2 and prevents VP.Our objective was to test whether Cb2 reduces VP OHSS in humans.We conducted a prospective, randomized, double-blind study on oocyte donors at risk developing (>20 follicles, >12 mm developed, >20...
To develop a consensus and provide updated recommendations on liver MR imaging the clinical use of liver-specific contrast agents. The European Society Gastrointestinal Abdominal Radiology (ESGAR) formed multinational panel experts, selected basis literature review their leadership in field imaging. A modified Delphi process was adopted to draft list statements. Descriptive Cronbach’s statistics were used rate levels agreement internal reliability consensus. Three rounds conducted 76...
Automatic brain tumour segmentation has become a key component for the future of treatment. Currently, most approaches arise from supervised learning standpoint, which requires labelled training dataset to infer models classes. The performance these is directly determined by size and quality corpus, whose retrieval becomes tedious time-consuming task. On other hand, unsupervised avoid limitations but often do not reach comparable results than methods. In this sense, we propose an automated...
Abstract Mobile medical imaging devices are invaluable for clinical diagnostic purposes both in and outside healthcare institutions. Among the various modalities, only a few readily portable. Magnetic resonance (MRI), gold standard numerous conditions, does not traditionally belong to this group. Recently, low-field MRI technology companies have demonstrated first decisive steps towards portability within facilities vehicles. However, these scanners’ weight dimensions incompatible with more...
Structured reporting in radiology continues to hold substantial potential improve the quality of service provided patients and referring physicians. Despite many physicians' preference for structured reports various efforts by radiological societies some vendors, has still not been widely adopted clinical routine.While countries national have launched initiatives further promote reporting, cross-institutional applications report templates incentives usage are lacking. Various legislative...
Abstract This statement has been produced within the European Society of Radiology AI Working Group and identifies key policies EU Act as they pertain to medical imaging. It offers specific recommendations policymakers professional community for effective implementation legislation, addressing potential gaps uncertainties. Key areas include literacy, classification rules high-risk systems, data governance, transparency, human oversight, quality management, deployer obligations, regulatory...
Abstract High‐resolution magic angle spinning (HR‐MAS) one‐ and two‐dimensional 1 H 13 C nuclear magnetic resonance (NMR) spectroscopy has been used to study intact glioblastoma (GBM) brain tumour tissue. The results were compared with in vitro chemical extract vivo spectra. resolution of one‐dimensional, TOCSY HSQC HR‐MAS spectra is comparable that obtained on perchloric extracts. have particularly useful for the identification 37 different metabolites biopsy tumours, excluding water DSS...
Swyer-James syndrome (SJS) is usually diagnosed with plain chest radiographs obtained during inspiration/expiration. The authors studied patients CT to assess its value in the evaluation of this syndrome. In SJS, was useful determination bronchial patency (all nine patients), lung parenchymal changes (subpleural infiltrates six patients, atelectasis two, and cavities two), extent degree bronchiectasis patients). If used for bronchiectasis, knowledge main findings associated SJS (hyperlucent...
Decompression sickness (DCS), as clinically diagnosed by reversal of symptoms with recompression, has never been reported in aquatic breath-hold diving vertebrates despite the occurrence tissue gas tensions sufficient for bubble formation and injury terrestrial animals. Similarly to mammals, sea turtles manage exchange decompression through anatomical, physiological, behavioral adaptations. In former group, DCS-like lesions have observed on necropsies following disturbance such high-powered...
Purpose To determine if preoperative vascular heterogeneity of glioblastoma is predictive overall survival patients undergoing standard-of-care treatment by using an unsupervised multiparametric perfusion-based habitat-discovery algorithm. Materials and Methods Preoperative magnetic resonance (MR) imaging including dynamic susceptibility-weighted contrast material-enhanced perfusion studies in 50 consecutive with were retrieved. Perfusion parameters analyzed used to automatically draw four...
Abstract PRIMAGE is one of the largest and more ambitious research projects dealing with medical imaging, artificial intelligence cancer treatment in children. It a 4-year European Commission-financed project that has 16 partners consortium, including Society for Paediatric Oncology, two imaging biobanks, three prominent paediatric oncology units. The constructed as an observational silico study involving high-quality anonymised datasets (imaging, clinical, molecular, genetics) training...