YEARS

2013-2015

AUTHORS

Samuel A Wickline

TITLE

ENTROPY-BASED TISSUE DISCRIMINATORS

ABSTRACT

DESCRIPTION (provided by applicant): The major problem addressed in this proposal is the development and evaluation of an automated noninvasive approach to discriminate different normal and pathological tissue types using machine learning algorithms; previous applications of machine learning have been based on features of the backscattered ultrasound that are essentially energy based. Our approach will be based on extracting features from images whose pixels are determined by the entropy contained in segments of the backscattered ultrasound. The unique attributes of entropy imaging suggest that the automated analysis we propose would be particularly robust for discrimination of deep tissues in a clinical environment.

FUNDED PUBLICATIONS

  • A role for peptides in overcoming endosomal entrapment in siRNA delivery - A focus on melittin.
  • Joint entropy of continuously differentiable ultrasonic waveforms.
  • Additional results for "joint entropy of continuously differentiable ultrasonic waveforms" [J. Acoust. Soc. Am. 133(1), 283-300 (2013)].
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    20 TRIPLES      17 PREDICATES      21 URIs      9 LITERALS

    Subject Predicate Object
    1 grants:86d8d1c04c2c15c5b9a4f629e73f258c sg:abstract DESCRIPTION (provided by applicant): The major problem addressed in this proposal is the development and evaluation of an automated noninvasive approach to discriminate different normal and pathological tissue types using machine learning algorithms; previous applications of machine learning have been based on features of the backscattered ultrasound that are essentially energy based. Our approach will be based on extracting features from images whose pixels are determined by the entropy contained in segments of the backscattered ultrasound. The unique attributes of entropy imaging suggest that the automated analysis we propose would be particularly robust for discrimination of deep tissues in a clinical environment.
    2 sg:endYear 2015
    3 sg:fundingAmount 412300.0
    4 sg:fundingCurrency USD
    5 sg:hasContribution contributions:6d7d55c1a5147272a1b524661885a038
    6 sg:hasFieldOfResearchCode anzsrc-for:08
    7 anzsrc-for:0801
    8 sg:hasFundedPublication articles:496f64da3b996eaa1f3ed50bebcbbd2b
    9 articles:a6bd2f0e0987c81c172c40fb928013da
    10 articles:ca9b8798d7cfb8708c5dced1a492d4e3
    11 sg:hasFundingOrganization grid-institutes:grid.280347.a
    12 sg:hasRecipientOrganization grid-institutes:grid.4367.6
    13 sg:language English
    14 sg:license http://scigraph.springernature.com/explorer/license/
    15 sg:scigraphId 86d8d1c04c2c15c5b9a4f629e73f258c
    16 sg:startYear 2013
    17 sg:title ENTROPY-BASED TISSUE DISCRIMINATORS
    18 sg:webpage http://projectreporter.nih.gov/project_info_description.cfm?aid=8737902
    19 rdf:type sg:Grant
    20 rdfs:label Grant: ENTROPY-BASED TISSUE DISCRIMINATORS
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