Analysis of intensity normalization for optimal segmentation performance of a fully convolutional neural network.
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| Title: | Analysis of intensity normalization for optimal segmentation performance of a fully convolutional neural network. |
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| Authors: | Jacobsen N; Medical Physics Group, Institute for Diagnostic and Interventional Radiology, University Hospital Jena, Jena, Germany., Deistung A; Medical Physics Group, Institute for Diagnostic and Interventional Radiology, University Hospital Jena, Jena, Germany; Department of Neurology, Essen University Hospital, University of Duisburg-Essen, Essen, Germany., Timmann D; Department of Neurology, Essen University Hospital, University of Duisburg-Essen, Essen, Germany., Goericke SL; Department of Diagnostic and Interventional Radiology and Neuroradiology, University of Duisburg-Essen, Essen, Germany., Reichenbach JR; Medical Physics Group, Institute for Diagnostic and Interventional Radiology, University Hospital Jena, Jena, Germany; Michael Stifel Center for Data-Driven and Simulation Science, Friedrich Schiller University Jena, Jena, Germany., Güllmar D; Medical Physics Group, Institute for Diagnostic and Interventional Radiology, University Hospital Jena, Jena, Germany. Electronic address: daniel.guellmar@med.uni-jena.de. |
| Source: | Zeitschrift fur medizinische Physik [Z Med Phys] 2019 May; Vol. 29 (2), pp. 128-138. Date of Electronic Publication: 2018 Dec 20. |
| Publication Type: | Journal Article |
| Journal Info: | Publisher: Elsevier GmbH Country of Publication: Germany NLM ID: 100886455 Publication Model: Print-Electronic Cited Medium: Internet ISSN: 1876-4436 (Electronic) Linking ISSN: 09393889 NLM ISO Abbreviation: Z Med Phys Subsets: MEDLINE |
| Database: | MEDLINE Ultimate |
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