Stratified Decision Forests for Accurate Anatomical Landmark Localization in Cardiac Images

IEEE Transactions on Medical Imaging

Volumn 36, Issue 1, 2017, Pages 332-342

  Oktay, Ozan ^a   Bai, Wenjia ^a   Guerrero, Ricardo ^a   Rajchl, Martin ^a   De Marvao, Antonio ^b   O'Regan, Declan P ^b   Cook, Stuart A ^b   Heinrich, Mattias P ^c   Glocker, Ben ^a   Rueckert, Daniel ^a  

^a IMPERIAL COLLEGE LONDON   (United Kingdom)

^b MRC CLINICAL SCIENCES CENTRE   (United Kingdom)

^c UNIVERSITY OF LÜBECK   (Germany)

Author keywords

Automatic landmark localization; cardiac image analysis; multi atlas image segmentation; stratified forests

Indexed keywords

DECISION TREES; FORESTRY; IMAGE ACQUISITION; IMAGE SEGMENTATION; LEARNING ALGORITHMS; MAGNETIC RESONANCE IMAGING; MEDICAL IMAGING;

AUTOMATIC IMAGE ANALYSIS; AUTOMATIC SEGMENTATIONS; CARDIAC IMAGE ANALYSIS; HETEROGENEOUS DATASETS; LANDMARK LOCALIZATION; LEARNING-BASED APPROACH; PATIENT SPECIFIC MODEL; STRATIFIED FORESTS;

IMAGE ANALYSIS;

CLASSIFICATION; DECISION TREE; FOREST; HEART; HUMAN; IMAGE ANALYSIS; IMAGE SEGMENTATION; MODEL; ORGAN; PIPELINE; STRATIFICATION; DIAGNOSTIC IMAGING; REPRODUCIBILITY;

DECISION TREES; HEART; HUMANS; REPRODUCIBILITY OF RESULTS;

EID: 85013178225     PISSN: 02780062     EISSN: 1558254X     Source Type: Journal    
DOI: 10.1109/TMI.2016.2597270     Document Type: Article

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