Xiaoguang Lu


Ontology type: schema:Person     


Person Info

NAME

Xiaoguang

SURNAME

Lu

Publications in SciGraph latest 50 shown

  • 2016-09-27 Robust 3D Organ Localization with Dual Learning Architectures and Fusion in DEEP LEARNING AND DATA LABELING FOR MEDICAL APPLICATIONS
  • 2014-01-16 Time-resolved 3D-CMR using free-breathing 2D-acquisitions in JOURNAL OF CARDIOVASCULAR MAGNETIC RESONANCE
  • 2013-01-30 Fully automatic planning of the long-axis views of the heart in JOURNAL OF CARDIOVASCULAR MAGNETIC RESONANCE
  • 2013 Discriminative Context Modeling Using Auxiliary Markers for LV Landmark Detection from a Single MR Image in STATISTICAL ATLASES AND COMPUTATIONAL MODELS OF THE HEART. IMAGING AND MODELLING CHALLENGES
  • 2012-10-30 Learning-Based Detection and Tracking in Medical Imaging: A Probabilistic Approach in DEFORMATION MODELS
  • 2012-02-01 Mitral valve annular velocity measurements derived from cine MRI: validation against Doppler echocardiography in JOURNAL OF CARDIOVASCULAR MAGNETIC RESONANCE
  • 2012 Automatic Segmentation of the Myocardium in Cine MR Images Using Deformable Registration in STATISTICAL ATLASES AND COMPUTATIONAL MODELS OF THE HEART. IMAGING AND MODELLING CHALLENGES
  • 2011-02-02 Automatic LV localization and view planning for cardiac MRI acquisition in JOURNAL OF CARDIOVASCULAR MAGNETIC RESONANCE
  • 2011-02-02 Automatic per-segment analysis of myocardial perfusion MRI in JOURNAL OF CARDIOVASCULAR MAGNETIC RESONANCE
  • 2011-02-02 A novel, automated method for measuring mitral valve annular velocity from standard cine TrueFISP data - a feasibility study in JOURNAL OF CARDIOVASCULAR MAGNETIC RESONANCE
  • 2011 Automatic Delineation of Left and Right Ventricles in Cardiac MRI Sequences Using a Joint Ventricular Model in FUNCTIONAL IMAGING AND MODELING OF THE HEART
  • 2011 Accurate Regression-Based 4D Mitral Valve Surface Reconstruction from 2D+t MRI Slices in MACHINE LEARNING IN MEDICAL IMAGING
  • 2011 Automatic View Planning for Cardiac MRI Acquisition in MEDICAL IMAGE COMPUTING AND COMPUTER-ASSISTED INTERVENTION – MICCAI 2011
  • 2010 Cardiac Anchoring in MRI through Context Modeling in MEDICAL IMAGE COMPUTING AND COMPUTER-ASSISTED INTERVENTION – MICCAI 2010
  • 2009 Discriminative Joint Context for Automatic Landmark Set Detection from a Single Cardiac MR Long Axis Slice in FUNCTIONAL IMAGING AND MODELING OF THE HEART
  • 2005 Multimodal Facial Gender and Ethnicity Identification in ADVANCES IN BIOMETRICS
  • 2004 Integrating Faces, Fingerprints, and Soft Biometric Traits for User Recognition in BIOMETRIC AUTHENTICATION
  • 2004 Skilled Forgery Detection in On-Line Signatures: A Multimodal Approach in BIOMETRIC AUTHENTICATION
  • 2004 Matching 2.5D Scans for Face Recognition in BIOMETRIC AUTHENTICATION
  • 2004 Face Recognition with 3D Model-Based Synthesis in BIOMETRIC AUTHENTICATION
  • 2003-06-24 Resampling for Face Recognition in AUDIO- AND VIDEO-BASED BIOMETRIC PERSON AUTHENTICATION
  • JSON-LD is the canonical representation for SciGraph data.

    TIP: You can open this SciGraph record using an external JSON-LD service: JSON-LD Playground Google SDTT

    [
      {
        "@context": "https://springernature.github.io/scigraph/jsonld/sgcontext.json", 
        "familyName": "Lu", 
        "givenName": "Xiaoguang", 
        "id": "sg:person.0656702353.18", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.0656702353.18"
        ], 
        "sdDataset": "persons", 
        "sdDatePublished": "2022-05-10T11:28", 
        "sdLicense": "https://scigraph.springernature.com/explorer/license/", 
        "sdPublisher": {
          "name": "Springer Nature - SN SciGraph project", 
          "type": "Organization"
        }, 
        "sdSource": "s3://com-springernature-scigraph/baseset/20220509/entities/gbq_results/person/person_635.jsonl", 
        "type": "Person"
      }
    ]
     

    Download the RDF metadata as:  json-ld nt turtle xml License info

    HOW TO GET THIS DATA PROGRAMMATICALLY:

    JSON-LD is a popular format for linked data which is fully compatible with JSON.

    curl -H 'Accept: application/ld+json' 'https://scigraph.springernature.com/person.0656702353.18'

    N-Triples is a line-based linked data format ideal for batch operations.

    curl -H 'Accept: application/n-triples' 'https://scigraph.springernature.com/person.0656702353.18'

    Turtle is a human-readable linked data format.

    curl -H 'Accept: text/turtle' 'https://scigraph.springernature.com/person.0656702353.18'

    RDF/XML is a standard XML format for linked data.

    curl -H 'Accept: application/rdf+xml' 'https://scigraph.springernature.com/person.0656702353.18'


     

    This table displays all metadata directly associated to this object as RDF triples.

    11 TRIPLES      9 PREDICATES      10 URIs      6 LITERALS      1 BLANK NODES

    Subject Predicate Object
    1 sg:person.0656702353.18 schema:familyName Lu
    2 schema:givenName Xiaoguang
    3 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.0656702353.18
    4 schema:sdDatePublished 2022-05-10T11:28
    5 schema:sdLicense https://scigraph.springernature.com/explorer/license/
    6 schema:sdPublisher N89f97625b91e402096dfa02341a95ad4
    7 sgo:license sg:explorer/license/
    8 sgo:sdDataset persons
    9 rdf:type schema:Person
    10 N89f97625b91e402096dfa02341a95ad4 schema:name Springer Nature - SN SciGraph project
    11 rdf:type schema:Organization
     




    Preview window. Press ESC to close (or click here)


    ...