Random forest active learning for AAA thrombus segmentation in computed tomography angiography images

Neurocomputing

Volumn 126, Issue , 2014, Pages 71-77

  Maiora, Josu ^a   Ayerdi, Borja ^a   Graña, Manuel ^a  

^a UNIVERSITY OF THE BASQUE COUNTRY UPV EHU   (Spain)

Author keywords

Abdominal aortic aneurysm segmentation; Active learning; CTA image segmentation; Random forests

Indexed keywords

3D COMPUTED TOMOGRAPHIES; ABDOMINAL AORTIC ANEURYSM SEGMENTATION; ABDOMINAL AORTIC ANEURYSMS; ACTIVE LEARNING; COMPUTED TOMOGRAPHY ANGIOGRAPHY; INTERACTIVE IMAGE SEGMENTATION; RANDOM FORESTS; SEGMENTATION PROCEDURE;

BLOOD VESSELS; CLASSIFICATION (OF INFORMATION); COMPUTERIZED TOMOGRAPHY; DECISION TREES;

IMAGE SEGMENTATION;

ABDOMINAL AORTA ANEURYSM; ACCURACY; ANATOMICAL VARIATION; ARTICLE; CLASSIFICATION ALGORITHM; COMPUTED TOMOGRAPHIC ANGIOGRAPHY; CONTROLLED STUDY; IMAGE ANALYSIS; IMAGE DISPLAY; IMAGE PROCESSING; IMAGE QUALITY; IMAGE SEGMENTATION; IMAGING AND DISPLAY; INTERMETHOD COMPARISON; LEARNING ALGORITHM; PRIORITY JOURNAL; RANDOM FOREST ACTIVE LEARNING; THREE DIMENSIONAL IMAGING;

EID: 84887609118     PISSN: 09252312     EISSN: 18728286     Source Type: Journal    
DOI: 10.1016/j.neucom.2013.01.051     Document Type: Article

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