Automated segmentation of multiparametric magnetic resonance images for cerebral AVM radiosurgery planning: a deep learning approach.

Simon, Aaron B; Hurt, Brian; Karunamuni, Roshan; Kim, Gwe-Ya; Moiseenko, Vitali; Olson, Scott; Farid, Nikdokht; Hsiao, Albert; Hattangadi-Gluth, Jona A

Simon, Aaron B; Hurt, Brian; Karunamuni, Roshan; Kim, Gwe-Ya; Moiseenko, Vitali; Olson, Scott; Farid, Nikdokht; Hsiao, Albert; Hattangadi-Gluth, Jona A.

Affiliation

Simon AB; Department of Radiation Medicine and Applied Sciences, University of California San Diego, 3960 Health Sciences Dr, Mail Code 0865, La Jolla, CA, USA.
Hurt B; Department of Radiation Oncology, University of California Irvine, Orange, CA, USA.
Karunamuni R; Department of Radiology, University of California San Diego, La Jolla, CA, USA.
Kim GY; Department of Radiation Medicine and Applied Sciences, University of California San Diego, 3960 Health Sciences Dr, Mail Code 0865, La Jolla, CA, USA.
Moiseenko V; Department of Radiation Medicine and Applied Sciences, University of California San Diego, 3960 Health Sciences Dr, Mail Code 0865, La Jolla, CA, USA.
Olson S; Department of Radiation Medicine and Applied Sciences, University of California San Diego, 3960 Health Sciences Dr, Mail Code 0865, La Jolla, CA, USA.
Farid N; Division of Neurosurgery, University of California San Diego, La Jolla, CA, USA.
Hsiao A; Department of Radiology, University of California San Diego, La Jolla, CA, USA.
Hattangadi-Gluth JA; Department of Radiology, University of California San Diego, La Jolla, CA, USA.

Sci Rep ; 12(1): 786, 2022 01 17.

Article de En | MEDLINE | ID: mdl-35039538

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Texte intégral: 1 Collection: 01-internacional Base de données: MEDLINE Sujet principal: Veines de l'encéphale / Angiographie cérébrale / Artères cérébrales / Malformations artérioveineuses intracrâniennes / Radiochirurgie / Angiographie par résonance magnétique / Apprentissage profond / Imagerie par résonance magnétique multiparamétrique Type d'étude: Guideline Limites: Humans Langue: En Journal: Sci Rep Année: 2022 Type de document: Article Pays d'affiliation: États-Unis d'Amérique Pays de publication: Royaume-Uni

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