Search results for "ERFNet"

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Deep Learning-Based Methods for Prostate Segmentation in Magnetic Resonance Imaging

2021

Magnetic Resonance Imaging-based prostate segmentation is an essential task for adaptive radiotherapy and for radiomics studies whose purpose is to identify associations between imaging features and patient outcomes. Because manual delineation is a time-consuming task, we present three deep-learning (DL) approaches, namely UNet, efficient neural network (ENet), and efficient residual factorized convNet (ERFNet), whose aim is to tackle the fully-automated, real-time, and 3D delineation process of the prostate gland on T2-weighted MRI. While UNet is used in many biomedical image delineation applications, ENet and ERFNet are mainly applied in self-driving cars to compensate for limited hardwar…

Computer scienceGraphics processing unit02 engineering and technologyResiduallcsh:TechnologyArticle030218 nuclear medicine & medical imaginglcsh:Chemistrydeep learning; segmentation; prostate; MRI; ENet; UNet; ERFNet; radiomicsSet (abstract data type)03 medical and health sciences0302 clinical medicineENetERFNet0202 electrical engineering electronic engineering information engineeringGeneral Materials ScienceSegmentationlcsh:QH301-705.5InstrumentationSettore ING-INF/05 - Sistemi Di Elaborazione Delle InformazioniFluid Flow and Transfer ProcessesprostateArtificial neural networklcsh:Tbusiness.industryProcess Chemistry and TechnologyDeep learningsegmentationGeneral EngineeringProcess (computing)deep learningUNetPattern recognitionlcsh:QC1-999Computer Science Applicationslcsh:Biology (General)lcsh:QD1-999lcsh:TA1-2040radiomics020201 artificial intelligence & image processingArtificial intelligenceCentral processing unitlcsh:Engineering (General). Civil engineering (General)businesslcsh:PhysicsMRIApplied Sciences
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