SVseg: Stacked Sparse Autoencoder-Based Patch Classification Modeling for Vertebrae Segmentation
SVseg: Stacked Sparse Autoencoder-Based Patch Classification Modeling for Vertebrae Segmentation
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Publisher
Basel: MDPI AG
Journal title
Language
English
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Publisher
Basel: MDPI AG
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Scope and Contents
Contents
Precise vertebrae segmentation is essential for the image-related analysis of spine pathologies such as vertebral compression fractures and other abnormalities, as well as for clinical diagnostic treatment and surgical planning. An automatic and objective system for vertebra segmentation is required, but its development is likely to run into diffic...
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Full title
SVseg: Stacked Sparse Autoencoder-Based Patch Classification Modeling for Vertebrae Segmentation
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Record Identifier
TN_cdi_doaj_primary_oai_doaj_org_article_05a14e4a714247f989ca486ebb605894
Permalink
https://devfeature-collection.sl.nsw.gov.au/record/TN_cdi_doaj_primary_oai_doaj_org_article_05a14e4a714247f989ca486ebb605894
Other Identifiers
ISSN
2227-7390
E-ISSN
2227-7390
DOI
10.3390/math10050796
