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245 1 0 _aTowards the Automatization of Cranial Implant Design in Cranioplasty II
_h[electronic resource] :
_bSecond Challenge, AutoImplant 2021, Held in Conjunction with MICCAI 2021, Strasbourg, France, October 1, 2021, Proceedings /
_cedited by Jianning Li, Jan Egger.
250 _a1st ed. 2021.
264 1 _aCham :
_bSpringer International Publishing :
_bImprint: Springer,
_c2021.
300 _aIX, 129 p. 76 illus., 67 illus. in color.
_bonline resource.
336 _atext
_btxt
_2rdacontent
337 _acomputer
_bc
_2rdamedia
338 _aonline resource
_bcr
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347 _atext file
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490 1 _aImage Processing, Computer Vision, Pattern Recognition, and Graphics,
_x3004-9954 ;
_v13123
505 0 _aPersonalized Calvarial Reconstruction in Neurosurgery -- Qualitative Criteria for Designing Feasible Cranial Implants -- Segmentation of Defective Skulls from CT Data for Tissue Modelling -- Improving the Automatic Cranial Implant Design in Cranioplasty by Linking Different Datasets -- Learning to Rearrange Voxels in Binary Segmentation Masks for Smooth Manifold Triangulation -- A U-Net based System for Cranial Implant Design with Pre-processing and Learned Implant Filtering -- Sparse Convolutional Neural Network for Skull Reconstruction -- Cranial Implant Prediction by Learning an Ensemble of Slice-based Skull Completion networks -- PCA-Skull: 3D Skull Shape Modelling Using Principal Component Analysis -- Cranial Implant Design using V-Net based Region of Interest Reconstruction.
520 _aThis book constitutes the Second Automatization of Cranial Implant Design in Cranioplasty Challenge, AutoImplant 2021, which was held in conjunction with the 24th International Conference on Medical Image Computing and Computer-Assisted Intervention, MICCAI 2021, in Strasbourg, France, in September, 2021. The challenge took place virtually due to the COVID-19 pandemic. The 7 papers are presented together with one invited paper, one qualitative evaluation criteria from neurosurgeons and a dataset descriptor. This challenge aims to provide more affordable, faster, and more patient-friendly solutions to the design and manufacturing of medical implants, including cranial implants, which is needed in order to repair a defective skull from a brain tumor surgery or trauma. The presented solutions can serve as a good benchmark for future publications regarding 3D volumetric shape learning and cranial implant design.
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650 0 _aComputer vision.
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650 0 _aApplication software.
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650 0 _aEducation
_xData processing.
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650 1 4 _aComputer Imaging, Vision, Pattern Recognition and Graphics.
_931569
650 2 4 _aArtificial Intelligence.
_93407
650 2 4 _aComputer and Information Systems Applications.
_9122621
650 2 4 _aComputers and Education.
_941129
700 1 _aLi, Jianning.
_eeditor.
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700 1 _aEgger, Jan.
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773 0 _tSpringer Nature eBook
776 0 8 _iPrinted edition:
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830 0 _aImage Processing, Computer Vision, Pattern Recognition, and Graphics,
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_v13123
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856 4 0 _uhttps://doi.org/10.1007/978-3-030-92652-6
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