Overuse-related instability of the elbow: the role of CT-arthrography

Autor: Andrea Zagarella, Giulia Signorelli, Giulia Muscogiuri, Roberta Colombo, Gianluca Folco, Paolo Arrigoni, Mattia Radici, Pietro Simone Randelli, Mauro Battista Gallazzi

Publikováno v: Insights into Imaging, Vol 12, Iss 1, Pp 1-14 (2021)

Abstract The elbow is a complex joint whose biomechanical function is granted by the interplay and synergy of various anatomical structures. Articular stability is achieved by both static and dynamic constraints, which consist of osseous as well as s

Externí odkaz: https://doaj.org/article/b8224d9474cb4b8d8cf947f6657bde49

Development and Validation of an AI-driven Mammographic Breast Density Classification Tool Based on Radiologist Consensus

Autor: Veronica Magni, Matteo Interlenghi, Andrea Cozzi, Marco Alì, Christian Salvatore, Alcide A. Azzena, Davide Capra, Serena Carriero, Gianmarco Della Pepa, Deborah Fazzini, Giuseppe Granata, Caterina B. Monti, Giulia Muscogiuri, Giuseppe Pellegrino, Simone Schiaffino, Isabella Castiglioni, Sergio Papa, Francesco Sardanelli

Publikováno v: Radiol Artif Intell
Radiology. Artificial intelligence 4 (2022): e210199. doi:10.1148/ryai.210199
info:cnr-pdr/source/autori:Magni V.; Interlenghi M.; Cozzi A.; Alì M.; Salvatore C.; Azzena A.A.; Capra D.; Carriero S.; Della Pepa G.; Fazzini D.; Granata G.; Monti C.B.; Muscogiuri G.; Pellegrino G.; Schiaffino S.; Castiglioni I.; Papa S.; Sardanelli F./titolo:Development and Validation of an AI-driven Mammographic Breast Density Classification Tool Based on Radiologist Consensu/doi:10.1148%2Fryai.210199/rivista:Radiology. Artificial intelligence/anno:2022/pagina_da:e210199/pagina_a:/intervallo_pagine:e210199/volume:4

Mammographic breast density (BD) is commonly visually assessed using the Breast Imaging Reporting and Data System (BI-RADS) four-category scale. To overcome inter- and intraobserver variability of visual assessment, the authors retrospectively develo

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::614e23baa8a00952f1c258ede5b1c4d2
https://doi.org/10.1148/ryai.210199