LimeSeg: a coarse-grained lipid membrane simulation for 3D image segmentation

BMC Bioinformatics

  ^{1    1    2} 

[1] 0000 0001 2322 4988, grid.8591.5, Aurélien Roux lab, University of Geneva, Department of Biochemistry, quai Ernest-Ansermet 30, 1211, Geneva, Switzerland;0000 0001 2322 4988, grid.8591.5, Marcos González Gaitán lab, University of Geneva, Department of Biochemistry, quai Ernest-Ansermet 30, 1211, Geneva, Switzerland;

关键词: 3D segmentation;    ImageJ;    Surfel-based;    Point-cloud;    Cell volume;    Cell surface;    Cell membrane segmentation;   

DOI  :  10.1186/s12859-018-2471-0

来源: publisher

【 摘 要 】

Background3D segmentation is often a prerequisite for 3D object display and quantitative measurements. Yet existing voxel-based methods do not directly give information on the object surface or topology. As for spatially continuous approaches such as level-set, active contours and meshes, although providing surfaces and concise shape description, they are generally not suitable for multiple object segmentation and/or for objects with an irregular shape, which can hamper their adoption by bioimage analysts.ResultsWe developed LimeSeg, a computationally efficient and spatially continuous 3D segmentation method. LimeSeg is easy-to-use and can process many and/or highly convoluted objects. Based on the concept of SURFace ELements (“Surfels”), LimeSeg resembles a highly coarse-grained simulation of a lipid membrane in which a set of particles, analogous to lipid molecules, are attracted to local image maxima. The particles are self-generating and self-destructing thus providing the ability for the membrane to evolve towards the contour of the objects of interest.The capabilities of LimeSeg: simultaneous segmentation of numerous non overlapping objects, segmentation of highly convoluted objects and robustness for big datasets are demonstrated on experimental use cases (epithelial cells, brain MRI and FIB-SEM dataset of cellular membrane system respectively).ConclusionIn conclusion, we implemented a new and efficient 3D surface reconstruction plugin adapted for various sources of images, which is deployed in the user-friendly and well-known ImageJ environment.

【 授权许可】

CC BY