Segmentation of Vestibular Schwannomas on Postoperative Gadolinium-Enhanced T1-Weighted and Noncontrast T2-Weighted Magnetic Resonance Imaging Using Deep Learning.

Yao, Peter; Shavit, Sagit Stern; Shin, James; Selesnick, Samuel; Phillips, C Douglas; Strauss, Sara B

Yao, Peter; Shavit, Sagit Stern; Shin, James; Selesnick, Samuel; Phillips, C Douglas; Strauss, Sara B.

Affiliation

Yao P; Weill Cornell Medical College, Weill Cornell Medicine.
Shavit SS; Department of Otolaryngology-Head and Neck Surgery, Weill Cornell Medicine.
Shin J; Department of Radiology, Weill Cornell Medicine, New York, New York.
Selesnick S; Department of Otolaryngology-Head and Neck Surgery, Weill Cornell Medicine.
Phillips CD; Department of Radiology, Weill Cornell Medicine, New York, New York.
Strauss SB; Department of Radiology, Weill Cornell Medicine, New York, New York.

Otol Neurotol ; 43(10): 1227-1239, 2022 12 01.

Article in En | MEDLINE | ID: mdl-36240735

Subject(s)

Deep Learning; Neuroma, Acoustic; Adult; Humans; Female; Neuroma, Acoustic/diagnostic imaging; Neuroma, Acoustic/surgery; Gadolinium; Retrospective Studies; Artificial Intelligence; Magnetic Resonance Imaging/methods

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Full text: 1 Collection: 01-internacional Database: MEDLINE Main subject: Neuroma, Acoustic / Deep Learning Type of study: Observational_studies / Prognostic_studies / Risk_factors_studies Limits: Adult / Female / Humans Language: En Journal: Otol Neurotol Journal subject: NEUROLOGIA / OTORRINOLARINGOLOGIA Year: 2022 Type: Article

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