Literature DB >> 23685464

COMBINING ATLAS AND ACTIVE CONTOUR FOR AUTOMATIC 3D MEDICAL IMAGE SEGMENTATION.

Yi Gao1, Allen Tannenbaum.   

Abstract

Atlas based methods and active contours are two families of techniques widely used for the task of 3D medical image segmentation. In this work we present a coupled framework where the two methods are combined together, in order to exploit each's advantage while avoid their respective drawbacks. Indeed, the atlas based methods lacks the flexibility in locally tuning the segmentation boundary; whereas the active contour has the drawback that the final result heavily depends on the initialization as well as the contour evolution energy functional. Therefore, in the proposed work, the atlas based segmentation provides a probability map, which not only supplies the initial contour position, but also defines the contour evolution energy in an on-line fashion. Afterward, the active contour further converges to the desired object boundary. Finally, the method is tested on various 3D medical images to demonstrate its robustness as well as accuracy.

Entities:  

Keywords:  Active contour segmentation; Atlas based segmentation

Year:  2011        PMID: 23685464      PMCID: PMC3655328          DOI: 10.1109/isbi.2011.5872662

Source DB:  PubMed          Journal:  Proc IEEE Int Symp Biomed Imaging        ISSN: 1945-7928


  4 in total

1.  A shape-based approach to the segmentation of medical imagery using level sets.

Authors:  Andy Tsai; Anthony Yezzi; William Wells; Clare Tempany; Dewey Tucker; Ayres Fan; W Eric Grimson; Alan Willsky
Journal:  IEEE Trans Med Imaging       Date:  2003-02       Impact factor: 10.048

2.  Active contours without edges.

Authors:  T F Chan; L A Vese
Journal:  IEEE Trans Image Process       Date:  2001       Impact factor: 10.856

3.  Using the logarithm of odds to define a vector space on probabilistic atlases.

Authors:  Kilian M Pohl; John Fisher; Sylvain Bouix; Martha Shenton; Robert W McCarley; W Eric L Grimson; Ron Kikinis; William M Wells
Journal:  Med Image Anal       Date:  2007-06-22       Impact factor: 8.545

4.  Automatic segmentation of the prostate in 3D MR images by atlas matching using localized mutual information.

Authors:  Stefan Klein; Uulke A van der Heide; Irene M Lips; Marco van Vulpen; Marius Staring; Josien P W Pluim
Journal:  Med Phys       Date:  2008-04       Impact factor: 4.071

  4 in total
  5 in total

1.  Automatic segmentation of the left atrium from MRI images using salient feature and contour evolution.

Authors:  Liangjia Zhu; Yi Gao; Anthony Yezzi; Rob MacLeod; Joshua Cates; Allen Tannenbaum
Journal:  Conf Proc IEEE Eng Med Biol Soc       Date:  2012

Review 2.  An Assessment of Imaging Informatics for Precision Medicine in Cancer.

Authors:  C Chennubhotla; L P Clarke; A Fedorov; D Foran; G Harris; E Helton; R Nordstrom; F Prior; D Rubin; J H Saltz; E Shalley; A Sharma
Journal:  Yearb Med Inform       Date:  2017-09-11

3.  A Kalman Filtering Perspective for Multiatlas Segmentation.

Authors:  Yi Gao; Liangjia Zhu; Joshua Cates; Rob S MacLeod; Sylvain Bouix; Allen Tannenbaum
Journal:  SIAM J Imaging Sci       Date:  2015-04-30       Impact factor: 2.867

4.  Towards Generation, Management, and Exploration of Combined Radiomics and Pathomics Datasets for Cancer Research.

Authors:  Joel Saltz; Jonas Almeida; Yi Gao; Ashish Sharma; Erich Bremer; Tammy DiPrima; Mary Saltz; Jayashree Kalpathy-Cramer; Tahsin Kurc
Journal:  AMIA Jt Summits Transl Sci Proc       Date:  2017-07-26

5.  Evaluation of localized region-based segmentation algorithms for CT-based delineation of organs at risk in radiotherapy.

Authors:  Mehdi Astaraki; Mara Severgnini; Vittorino Milan; Anna Schiattarella; Francesca Ciriello; Mario de Denaro; Aulo Beorchia; Hossein Aslian
Journal:  Phys Imaging Radiat Oncol       Date:  2018-03-05
  5 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.