Journal Title : International Journal of Modern Trends in Engineering and Science

Author’s Name : Lakshmi A S | Nissa Surling S N

Volume 02 Issue 12  Year 2015 

ISSN no: 2348-3121  

Page no: 8-12

Abstract An Echocardiogram is a non-invasive procedure used to assess the heart’s function and structures. This paper proposes  a new hybrid  approach to estimate  the cardiac  cycle phases  in  2-D  echocardiographic  images  as  a  first  step  in cardiac  volume  estimation.  Here  analysis  of the  atrial  systole and  diastole  events  by  using  the  geometrical  position  of the mitral  valve and a set of image features  is done. The proposed algorithm is based on an organization of image processing methods and Support Vector Machine as a classifier to robustly extract   anatomical information.  An original   set of image feature is used and derived to recognize the cardiac phases. The aforestated approach is performed in a denoising scenario. In this scenario,   the images are corrupted with Gaussian noise distribution. This hybrid algorithm does not involve any manual   tracing   of the boundaries for segmentation   process. The algorithm is realized as computer aided diagnosis (CADi) software.  A dataset of 160 images that include both normal and infarct   cardiac   pathologies were used.  An  accuracy   of 93 percentage  and  a  1.2s  in  terms   of  execution  time  of  CADi application was  reported in  a  cardiac  cycle estimation  task. The significant  improvement of this paper  is the introduction of  a  hybrid   method  and  set  of  image  features   that  can  be helpful  for  automatic detection  applications  without  any  user intervention.

Keywords— Support Vector Machine; Cardiac Phase Cycle; CAD; Image features


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