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  • Magnetic resonance imaging (MRI) is a visualizing method used in radiology that enables viewing internal structures of the body. Using several mathematical methods with data retrieved from MRI it is possible to quantify the brain compartment volume, which has many applications in cognitive, clinical and comparative neurosciences. This paper introduces a new fully automatic method, which can measure the volume of brain tissue using scans obtained from MRI devices. The method introduced in this paper was trained on data taken from 12 patients and the trained result was validated on other independent data obtained from 10 patients and compared to a human experts accuracy. The result achieves 99.407 % +/- 0.062 voxel error accuracy, which is comparable to results achieved by humans (99.540 % + 0.0775) but in a significantly shorter time and without the need of human involvement.
  • Magnetic resonance imaging (MRI) is a visualizing method used in radiology that enables viewing internal structures of the body. Using several mathematical methods with data retrieved from MRI it is possible to quantify the brain compartment volume, which has many applications in cognitive, clinical and comparative neurosciences. This paper introduces a new fully automatic method, which can measure the volume of brain tissue using scans obtained from MRI devices. The method introduced in this paper was trained on data taken from 12 patients and the trained result was validated on other independent data obtained from 10 patients and compared to a human experts accuracy. The result achieves 99.407 % +/- 0.062 voxel error accuracy, which is comparable to results achieved by humans (99.540 % + 0.0775) but in a significantly shorter time and without the need of human involvement. (en)
Title
  • 3D Brain Tissue Selection and Segmentation from MRI
  • 3D Brain Tissue Selection and Segmentation from MRI (en)
skos:prefLabel
  • 3D Brain Tissue Selection and Segmentation from MRI
  • 3D Brain Tissue Selection and Segmentation from MRI (en)
skos:notation
  • RIV/00216305:26220/13:PU104568!RIV14-MPO-26220___
http://linked.open...avai/predkladatel
http://linked.open...avai/riv/aktivita
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  • P(FR-TI4/151), S
http://linked.open...vai/riv/dodaniDat
http://linked.open...aciTvurceVysledku
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  • 119777
http://linked.open...ai/riv/idVysledku
  • RIV/00216305:26220/13:PU104568
http://linked.open...riv/jazykVysledku
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  • Image processing, skull stripping, machine learning, brain selection, segmentation. (en)
http://linked.open.../riv/klicoveSlovo
http://linked.open...ontrolniKodProRIV
  • [86FD92AA99AF]
http://linked.open...v/mistoKonaniAkce
  • Rome
http://linked.open...i/riv/mistoVydani
  • Neuveden
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  • 36th International Conference on Telecommunications and Signal processing
http://linked.open...in/vavai/riv/obor
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http://linked.open...vavai/riv/projekt
http://linked.open...UplatneniVysledku
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  • Burget, Radim
  • Mašek, Jan
  • Uher, Václav
  • Dutta, Malay Kishore
http://linked.open...vavai/riv/typAkce
http://linked.open.../riv/zahajeniAkce
number of pages
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  • Neuveden
https://schema.org/isbn
  • 978-1-4799-0402-0
http://localhost/t...ganizacniJednotka
  • 26220
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