Title
A survey of shaped-based registration and segmentation techniques for cardiac images
Abstract
Heart disease is the leading cause of death in the modern world. Cardiac imaging is routinely applied for assessment and diagnosis of cardiac diseases. Computerized image analysis methods are now widely applied to cardiac segmentation and registration in order to extract the anatomy and contractile function of the heart. The vast number of recent papers on this topic point to the need for an up to date survey in order to summarize and classify the published literature. This paper presents a survey of shape modeling applications to cardiac image analysis from MRI, CT, echocardiography, PET, and SPECT and aims to (1) introduce new methodologies in this field, (2) classify major contributions in image-based cardiac modeling, (3) provide a tutorial to beginners to initiate their own studies, and (4) introduce the major challenges of registration and segmentation and provide practical examples. The techniques surveyed include statistical models, deformable models/level sets, biophysical models, and non-rigid registration using basis functions. About 130 journal articles are categorized based on methodology, output, imaging system, modality, and validations. The advantages and disadvantages of the registration and validation techniques are discussed as appropriate in each section.
Year
DOI
Venue
2013
10.1016/j.cviu.2012.11.017
Computer Vision and Image Understanding
Keywords
Field
DocType
cardiac segmentation,heart disease,shaped-based registration,imaging system,non-rigid registration,cardiac imaging,cardiac image analysis,segmentation technique,major challenge,computerized image analysis method,image-based cardiac modeling,cardiac disease,edv,gmm,pca,pet,em,mi,sax,fe,n,mri,nurbs,mrf,nmi,review article,epi,sad,rpm,ct,cvd,p,asm,esv
Segmentation,Level set,Cardiac imaging,Basis function,Statistical model,Artificial intelligence,Cardiac motion,Machine learning,Mathematics
Journal
Volume
Issue
ISSN
117
9
1077-3142
Citations 
PageRank 
References 
33
1.19
132
Authors
2
Search Limit
100132
Name
Order
Citations
PageRank
Vahid Tavakoli1331.19
Amir A. Amini244363.30