NS-HGlio: A generalizable and repeatable HGG segmentation and volumetric measurement AI algorithm for the longitudinal MRI assessment to inform RANO in trials and clinics.
Aly H AbayazeedAhmed AbbassyMichael MüellerMichael HillMohamed QayatiShady MohamedMahmoud MekhaimarCatalina RaymondPrachi DubeyKambiz NaelSaurabh RohatgiVaishali KapareAshwini KulkarniTina ShiangAtul KumarNicolaus AndratschkeJonas WillmannAlexander BrawanskiReordan De JesusIbrahim TunaSteve H FungJoseph C LandolfiBenjamin M EllingsonMauricio ReyesPublished in: Neuro-oncology advances (2022)
NS-HGlio is accurate, repeatable, and generalizable. The output can be used for visualization, documentation, treatment response monitoring, radiation planning, intra-operative targeting, and estimation of Residual Tumor Volume among others.
Keyphrases
- deep learning
- dengue virus
- artificial intelligence
- machine learning
- convolutional neural network
- primary care
- magnetic resonance imaging
- contrast enhanced
- electronic health record
- zika virus
- high resolution
- cancer therapy
- cross sectional
- advance care planning
- magnetic resonance
- radiation therapy
- clinical evaluation