Literature DB >> 23708807

Spline-based deforming ellipsoids for interactive 3D bioimage segmentation.

Ricard Delgado-Gonzalo1, Nicolas Chenouard, Michael Unser.   

Abstract

We present a new fast active-contour model (a.k.a. snake) for image segmentation in 3D microscopy. We introduce a parametric design that relies on exponential B-spline bases and allows us to build snakes that are able to reproduce ellipsoids. We design our bases to have the shortest-possible support, subject to some constraints. Thus, computational efficiency is maximized. The proposed 3D snake can approximate blob-like objects with good accuracy and can perfectly reproduce spheres and ellipsoids, irrespective of their position and orientation. The optimization process is remarkably fast due to the use of Gauss' theorem within our energy computation scheme. Our technique yields successful segmentation results, even for challenging data where object contours are not well defined. This is due to our parametric approach that allows one to favor prior shapes. In addition, this paper provides a software that gives full control over the snakes via an intuitive manipulation of few control points.

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Year:  2013        PMID: 23708807     DOI: 10.1109/TIP.2013.2264680

Source DB:  PubMed          Journal:  IEEE Trans Image Process        ISSN: 1057-7149            Impact factor:   10.856


  8 in total

1.  Automatic segmentation and statistical shape modeling of the paranasal sinuses to estimate natural variations.

Authors:  Ayushi Sinha; Simon Leonard; Austin Reiter; Masaru Ishii; Russell H Taylor; Gregory D Hager
Journal:  Proc SPIE Int Soc Opt Eng       Date:  2016-03-21

2.  Automated segmentation of the injured spleen.

Authors:  Ozgür Dandin; Uygar Teomete; Onur Osman; Gökalp Tulum; Tuncer Ergin; Mehmet Zafer Sabuncuoglu
Journal:  Int J Comput Assist Radiol Surg       Date:  2015-09-04       Impact factor: 2.924

3.  Robust and automated three-dimensional segmentation of densely packed cell nuclei in different biological specimens with Lines-of-Sight decomposition.

Authors:  B Mathew; A Schmitz; S Muñoz-Descalzo; N Ansari; F Pampaloni; E H K Stelzer; S C Fischer
Journal:  BMC Bioinformatics       Date:  2015-06-08       Impact factor: 3.169

4.  Survey statistics of automated segmentations applied to optical imaging of mammalian cells.

Authors:  Peter Bajcsy; Antonio Cardone; Joe Chalfoun; Michael Halter; Derek Juba; Marcin Kociolek; Michael Majurski; Adele Peskin; Carl Simon; Mylene Simon; Antoine Vandecreme; Mary Brady
Journal:  BMC Bioinformatics       Date:  2015-10-15       Impact factor: 3.169

5.  FlyLimbTracker: An active contour based approach for leg segment tracking in unmarked, freely behaving Drosophila.

Authors:  Virginie Uhlmann; Pavan Ramdya; Ricard Delgado-Gonzalo; Richard Benton; Michael Unser
Journal:  PLoS One       Date:  2017-04-28       Impact factor: 3.240

6.  Efficient Segmentation of a Breast in B-Mode Ultrasound Tomography Using Three-Dimensional GrabCut (GC3D).

Authors:  Shaode Yu; Shibin Wu; Ling Zhuang; Xinhua Wei; Mark Sak; Duric Neb; Jiani Hu; Yaoqin Xie
Journal:  Sensors (Basel)       Date:  2017-08-08       Impact factor: 3.576

7.  CellECT: cell evolution capturing tool.

Authors:  Diana L Delibaltov; Utkarsh Gaur; Jennifer Kim; Matthew Kourakis; Erin Newman-Smith; William Smith; Samuel A Belteton; Daniel B Szymanski; B S Manjunath
Journal:  BMC Bioinformatics       Date:  2016-02-17       Impact factor: 3.169

8.  Analysis of in vivo single cell behavior by high throughput, human-in-the-loop segmentation of three-dimensional images.

Authors:  Michael Chiang; Sam Hallman; Amanda Cinquin; Nabora Reyes de Mochel; Adrian Paz; Shimako Kawauchi; Anne L Calof; Ken W Cho; Charless C Fowlkes; Olivier Cinquin
Journal:  BMC Bioinformatics       Date:  2015-11-25       Impact factor: 3.169

  8 in total

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