0000000000267556

AUTHOR

ÁNgel Alberich-bayarri

showing 3 related works from this author

Digital Pathology Enables Automated and Quantitative Assessment of Inflammatory Activity in Patients with Chronic Liver Disease

2021

Traditional histological evaluation for grading liver disease severity is based on subjective and semi-quantitative scores. We examined the relationship between digital pathology analysis and corresponding scoring systems for the assessment of hepatic necroinflammatory activity. A prospective, multicenter study including 156 patients with chronic liver disease (74% nonalcoholic fatty liver disease-NAFLD, 26% chronic hepatitis-CH etiologies) was performed. Inflammation was graded according to the Nonalcoholic Steatohepatitis (NASH) Clinical Research Network system and METAVIR score. Whole-slide digital image analysis based on quantitative (I-score: inflammation ratio) and morphometric (C-sco…

Liver CirrhosisMalenonalcoholic fatty liver diseaseMiddle AgedFibrosisMicrobiologyBiochemistryArticleQR1-502digital pathology; inflammation; nonalcoholic fatty liver disease; chronic hepatitisLiverNon-alcoholic Fatty Liver DiseaseinflammationHumanschronic hepatitisdigital pathologyMolecular BiologyBiomolecules
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CHAIMELEON Project: Creation of a Pan-European Repository of Health Imaging Data for the Development of AI-Powered Cancer Management Tools

2022

[EN] The CHAIMELEON project aims to set up a pan-European repository of health imaging data, tools and methodologies, with the ambition to set a standard and provide resources for future AI experimentation for cancer management. The project is a 4 year long, EU-funded project tackling some of the most ambitious research in the fields of biomedical imaging, artificial intelligence and cancer treatment, addressing the four types of cancer that currently have the highest prevalence worldwide: lung, breast, prostate and colorectal. To allow this, clinical partners and external collaborators will populate the repository with multimodality (MR, CT, PET/CT) imaging and related clinical data. Subse…

Imatges tridimensionals en medicinaCancer ResearchINFORMATIONARTIFICIAL-INTELLIGENCEIntel·ligència artificialArtificial intelligence (AI)radiologyddc:cancer imagingcancer managementComputingMethodologies_PATTERNRECOGNITIONOncologyimage harmonizationartificial intelligence-AI cancer imaging cancer management image harmonization quantitative imaging biomarkers radiologyCIENCIAS DE LA COMPUTACION E INTELIGENCIA ARTIFICIALartificial intelligence-AI; cancer imaging; cancer management; image harmonization; quantitative imaging biomarkers; radiologyartificial intelligence-AI1112 Oncology and CarcinogenesisCàncerquantitative imaging biomarkers
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Disease Biomarkers: Modelling MR Spectroscopy and Clinical Applications

2012

Clinical MRS has become a reference technique for in vivo evaluating the metabolism of different tissues, with special application to brain and prostate lesion characterization and tumour’s follow-up. It allows detecting relevant changes that cannot be appreciated in the conventional MR images. Nowadays, MRS has been widely applied in many different brain pathologies with excellent results as a disease biomarker. Since the different diseases and grades have different manifestations in the spectroscopic profile, a deep understanding of the subjacent biology is needed for the signal interpretation. The development of high-field (≥3 T) scanners has permitted the acquisition of high-quality MRS…

Signal interpretationIn vivo magnetic resonance spectroscopymedicine.medical_specialtymedicine.diagnostic_testbusiness.industryMagnetic resonance imagingmedicine.diseaseProstate cancermedicine.anatomical_structureProstatemedicineDisease biomarkerRadiologyMr imagesbusinessFat fraction
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