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Semi-automatic segmentation of multiple mouse embryos in MR images
- Source :
- BMC Bioinformatics, BMC Bioinformatics, Vol 12, Iss 1, p 237 (2011)
- Publication Year :
- 2011
-
Abstract
- Background The motivation behind this paper is to aid the automatic phenotyping of mouse embryos, wherein multiple embryos embedded within a single tube were scanned using Magnetic Resonance Imaging (MRI). Results Our algorithm, a modified version of the simplex deformable model of Delingette, addresses various issues with deformable models including initialization and inability to adapt to boundary concavities. In addition, it proposes a novel technique for automatic collision detection of multiple objects which are being segmented simultaneously, hence avoiding major leaks into adjacent neighbouring structures. We address the initialization problem by introducing balloon forces which expand the initial spherical models close to the true boundaries of the embryos. This results in models which are less sensitive to initial minimum of two fold after each stage of deformation. To determine collision during segmentation, our unique collision detection algorithm finds the intersection between binary masks created from the deformed models after every few iterations of the deformation and modifies the segmentation parameters accordingly hence avoiding collision. We have segmented six tubes of three dimensional MR images of multiple mouse embryos using our modified deformable model algorithm. We have then validated the results of the our semi-automatic segmentation versus manual segmentation of the same embryos. Our Validation shows that except paws and tails we have been able to segment the mouse embryos with minor error. Conclusions This paper describes our novel multiple object segmentation technique with collision detection using a modified deformable model algorithm. Further, it presents the results of segmenting magnetic resonance images of up to 32 mouse embryos stacked in one gel filled test tube and creating 32 individual masks.
- Subjects :
- Computer science
Boundary (topology)
Initialization
lcsh:Computer applications to medicine. Medical informatics
Biochemistry
Mice
Imaging, Three-Dimensional
Intersection
Structural Biology
Animals
Segmentation
Computer vision
Collision detection
Molecular Biology
lcsh:QH301-705.5
business.industry
Applied Mathematics
Methodology Article
Collision
Embryo, Mammalian
Magnetic Resonance Imaging
Computer Science Applications
lcsh:Biology (General)
lcsh:R858-859.7
Artificial intelligence
business
Algorithms
Software
Subjects
Details
- Language :
- English
- ISSN :
- 14712105
- Volume :
- 12
- Issue :
- 1
- Database :
- OpenAIRE
- Journal :
- BMC Bioinformatics
- Accession number :
- edsair.doi.dedup.....aa2f00de59ac32f79e2f5e9c25d98c11