Estimating the 4D respiratory lung motion by spatiotemporal registration and building super-resolution image

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

Volumn 6891 LNCS, Issue PART 1, 2011, Pages 532-539

  Wu, Guorong ^a   Wang, Qian ^a   Lian, Jun ^a   Shen, Dinggang ^a  

^a UNIVERSITY OF NORTH CAROLINA SCHOOL OF MEDICINE   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

ACCURATE REGISTRATION; ALL PHASE; CORRESPONDENCE DETECTION; CT SCANNERS; DATA SETS; FREE BREATHING; HIGH RESOLUTION; IMAGE INFORMATION; LUNG CANCER; LUNG MOTION; MOTION ARTIFACT; PHASE IMAGE; RESPIRATORY PHASIS; SPATIO-TEMPORAL REGISTRATION; SPATIOTEMPORAL BEHAVIORS; STATE-OF-THE-ART APPROACH; SUPER RESOLUTION; TEMPORAL COHERENCE; TEMPORAL CONSISTENCY; UNIFIED APPROACH;

ALGORITHMS; BIOLOGICAL ORGANS; ESTIMATION; MEDICAL COMPUTING; MEDICAL IMAGING; MOTION ESTIMATION; RADIOTHERAPY;

COMPUTERIZED TOMOGRAPHY;

ALGORITHM; ARTICLE; ARTIFACT; BREATHING; COMPUTER SIMULATION; FOUR DIMENSIONAL COMPUTED TOMOGRAPHY; HISTOLOGY; HUMAN; IMAGE PROCESSING; LUNG; METHODOLOGY; MOTION; PATHOLOGY; RADIOGRAPHY; REPRODUCIBILITY; STATISTICAL MODEL; TIME;

ALGORITHMS; ARTIFACTS; COMPUTER SIMULATION; FOUR-DIMENSIONAL COMPUTED TOMOGRAPHY; HUMANS; IMAGE PROCESSING, COMPUTER-ASSISTED; LUNG; MODELS, STATISTICAL; MOTION; REPRODUCIBILITY OF RESULTS; RESPIRATION; TIME FACTORS;

EID: 82255181780     PISSN: 03029743     EISSN: 16113349     Source Type: Book Series    
DOI: 10.1007/978-3-642-23623-5_67     Document Type: Conference Paper

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