Literature DB >> 17933492

An electrostatic deformable model for medical image segmentation.

Herng-Hua Chang1, Daniel J Valentino.   

Abstract

A new deformable model, the charged fluid model (CFM), that uses the simulation of charged elements was used to segment medical images. Poisson's equation was used to guide the evolution of the CFM in two steps. In the first step, the elements of the charged fluid were distributed along the propagating interface until electrostatic equilibrium was achieved. In the second step, the propagating front of the charged fluid was deformed in response to the image gradient. The CFM provided sub-pixel precision, required only one parameter setting, and required no prior knowledge of the anatomy of the segmented object. The characteristics of the CFM were compared to existing deformable models using CT and MR images. The results indicate that the CFM is a promising approach for the segmentation of anatomic structures in a wide variety of medical images across different modalities.

Mesh:

Year:  2007        PMID: 17933492      PMCID: PMC2374837          DOI: 10.1016/j.compmedimag.2007.08.012

Source DB:  PubMed          Journal:  Comput Med Imaging Graph        ISSN: 0895-6111            Impact factor:   4.790


  12 in total

1.  Region tracking on level-sets methods.

Authors:  M Bertalmio; G Sapiro; G Randall
Journal:  IEEE Trans Med Imaging       Date:  1999-05       Impact factor: 10.048

2.  Model-based quantitation of 3-D magnetic resonance angiographic images.

Authors:  A F Frangi; W J Niessen; R M Hoogeveen; T van Walsum; M A Viergever
Journal:  IEEE Trans Med Imaging       Date:  1999-10       Impact factor: 10.048

3.  Cortex segmentation: a fast variational geometric approach.

Authors:  Roman Goldenberg; Ron Kimmel; Ehud Rivlin; Michael Rudzsky
Journal:  IEEE Trans Med Imaging       Date:  2002-12       Impact factor: 10.048

4.  Active shape model segmentation with optimal features.

Authors:  Bram van Ginneken; Alejandro F Frangi; Joes J Staal; Bart M ter Haar Romeny; Max A Viergever
Journal:  IEEE Trans Med Imaging       Date:  2002-08       Impact factor: 10.048

5.  Improved watershed transform for medical image segmentation using prior information.

Authors:  V Grau; A U J Mewes; M Alcañiz; R Kikinis; S K Warfield
Journal:  IEEE Trans Med Imaging       Date:  2004-04       Impact factor: 10.048

6.  Area and length minimizing flows for shape segmentation.

Authors:  K Siddiqi; Y B Lauzière; A Tannenbaum; S W Zucker
Journal:  IEEE Trans Image Process       Date:  1998       Impact factor: 10.856

7.  Active contours without edges.

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

Review 8.  Deformable models in medical image analysis: a survey.

Authors:  T McInerney; D Terzopoulos
Journal:  Med Image Anal       Date:  1996-06       Impact factor: 8.545

9.  A geometric snake model for segmentation of medical imagery.

Authors:  A Yezzi; S Kichenassamy; A Kumar; P Olver; A Tannenbaum
Journal:  IEEE Trans Med Imaging       Date:  1997-04       Impact factor: 10.048

10.  Interactive segmentation of cerebral gray matter, white matter, and CSF: photographic and MR images.

Authors:  T Q Bartlett; M W Vannier; D W McKeel; M Gado; C F Hildebolt; R Walkup
Journal:  Comput Med Imaging Graph       Date:  1994 Nov-Dec       Impact factor: 4.790

View more
  3 in total

1.  Computer-aided measurement of liver volumes in CT by means of geodesic active contour segmentation coupled with level-set algorithms.

Authors:  Kenji Suzuki; Ryan Kohlbrenner; Mark L Epstein; Ademola M Obajuluwa; Jianwu Xu; Masatoshi Hori
Journal:  Med Phys       Date:  2010-05       Impact factor: 4.071

2.  A fast region-based active contour model for boundary detection of echocardiographic images.

Authors:  Kalpana Saini; M L Dewal; Manojkumar Rohit
Journal:  J Digit Imaging       Date:  2012-04       Impact factor: 4.056

Review 3.  Manual and Automatic Image Analysis Segmentation Methods for Blood Flow Studies in Microchannels.

Authors:  Violeta Carvalho; Inês M Gonçalves; Andrews Souza; Maria S Souza; David Bento; João E Ribeiro; Rui Lima; Diana Pinho
Journal:  Micromachines (Basel)       Date:  2021-03-18       Impact factor: 2.891

  3 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.