Frontiers in Neuroinformatics · 2016 · 619 citations · 50 references
ComputingBiomedical EngineeringNeuroscienceBiomedical ImagingDiagnostic ImagingDiagnostic RadiologyBrain ImagingImage FusionMedical Image AnalysisMedical ImagingVolume RegistrationVolume Segmentation3D Image Segmentation3D Medical Image AnalysisAutomatic SegmentationStructural Brain DevelopmentThree-dimensional Volumetric AnalysisVolumetric AnnotationVolumetric Brain AnalysisWarping
The amount of medical image data produced in clinical and research settings is rapidly growing resulting in vast amount of data to analyze. Automatic and reliable quantitative analysis tools, including segmentation, allow to analyze brain development and to understand specific patterns of many neurological diseases. This field has recently experienced many advances with successful techniques based on non-linear warping and label fusion. In this work we present a novel and fully automatic pipeline for volumetric brain analysis based on multi-atlas label fusion technology that is able to provide accurate volumetric information at different levels of detail in a short time. This method is available through the volBrain online web interface (http://volbrain.upv.es), which is publically and freely accessible to the scientific community. Our new framework has been compared with current state-of-the-art methods showing very competitive results.
50
Proceedings of IEEE International Conference on Computer Vision
1995 · 12.9K citations
Bruce Fischl, David H. Salat, Evelina Busa et al. · Neuron · 2002 · 9K citations · Full text
Bilateral filtering for gray and color images
Carlo Tomasi, Roberto Manduchi · 2002 · 8.1K citations
Arts, Vision Science, Color Vision +16
John Ashburner, Karl Friston · NeuroImage · 2005 · 7.5K citations
A Non-Local Algorithm for Image Denoising
Antoni Buades, B. Coll, Jean‐Michel Morel · 2005 · 7.1K citations