Literature DB >> 9873923

Deformable models in medical image analysis: a survey.

T McInerney1, D Terzopoulos.   

Abstract

This article surveys deformable models, a promising and vigorously researched computer-assisted medical image analysis technique. Among model-based techniques, deformable models offer a unique and powerful approach to image analysis that combines geometry, physics and approximation theory. They have proven to be effective in segmenting, matching and tracking anatomic structures by exploiting (bottom-up) constraints derived from the image data together with (top-down) a priori knowledge about the location, size and shape of these structures. Deformable models are capable of accommodating the significant variability of biological structures over time and across different individuals. Furthermore, they support highly intuitive interaction mechanisms that, when necessary, allow medical scientists and practitioners to bring their expertise to bear on the model-based image interpretation task. This article reviews the rapidly expanding body of work on the development and application of deformable models to problems of fundamental importance in medical image analysis, including segmentation, shape representation, matching and motion tracking.

Mesh:

Year:  1996        PMID: 9873923     DOI: 10.1016/s1361-8415(96)80007-7

Source DB:  PubMed          Journal:  Med Image Anal        ISSN: 1361-8415            Impact factor:   8.545


  101 in total

1.  Analytical guide wire motion algorithm for simulation of endovascular interventions.

Authors:  M K Konings; E B van de Kraats; T Alderliesten; W J Niessen
Journal:  Med Biol Eng Comput       Date:  2003-11       Impact factor: 2.602

2.  Deformable organisms for automatic medical image analysis.

Authors:  Tim McInerney; Ghassan Hamarneh; Martha Shenton; Demetri Terzopoulos
Journal:  Med Image Anal       Date:  2002-09       Impact factor: 8.545

3.  A statistically based flow for image segmentation.

Authors:  Eric Pichon; Allen Tannenbaum; Ron Kikinis
Journal:  Med Image Anal       Date:  2004-09       Impact factor: 8.545

4.  Multi-compartment heart segmentation in CT angiography using a spatially varying gaussian classifier.

Authors:  S Murphy; A Akinyemi; J Steel; Y Petillot; I Poole
Journal:  Int J Comput Assist Radiol Surg       Date:  2012-05-27       Impact factor: 2.924

5.  Topological correction of brain surface meshes using spherical harmonics.

Authors:  Rachel Aine Yotter; Robert Dahnke; Paul M Thompson; Christian Gaser
Journal:  Hum Brain Mapp       Date:  2010-07-27       Impact factor: 5.038

6.  A geometric database for gene expression data.

Authors:  Tao Ju; Joe Warren; Gregor Eichele; Christina Thaller; Wah Chiu; James Carson
Journal:  Symp Geom Process       Date:  2003

Review 7.  Shifting from region of interest (ROI) to voxel-based analysis in human brain mapping.

Authors:  Loukas G Astrakas; Maria I Argyropoulou
Journal:  Pediatr Radiol       Date:  2010-05-13

Review 8.  Structural brain atlases: design, rationale, and applications in normal and pathological cohorts.

Authors:  Pravat K Mandal; Rashima Mahajan; Ivo D Dinov
Journal:  J Alzheimers Dis       Date:  2012       Impact factor: 4.472

9.  Depth-map-based scene analysis for active navigation in virtual angioscopy.

Authors:  P Haigron; M E Bellemare; O Acosta; C Göksu; C Kulik; K Rioual; A Lucas
Journal:  IEEE Trans Med Imaging       Date:  2004-11       Impact factor: 10.048

10.  Intraretinal layer segmentation of macular optical coherence tomography images using optimal 3-D graph search.

Authors:  Mona K Garvin; Michael D Abramoff; Randy Kardon; Stephen R Russell; Xiaodong Wu; Milan Sonka
Journal:  IEEE Trans Med Imaging       Date:  2008-10       Impact factor: 10.048

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