Segmentation of center brains and optic lobes in 3D confocal images of adult fruit fly brains.
Automatic alignment (registration) of 3D images of adult fruit fly brains is often influenced by the significant displacement of the relative locations of the two optic lobes (OLs) and the center brain (CB). In one of our ongoing efforts to produce a better image alignment pipeline of adult fruit fly brains, we consider separating CB and OLs and align them independently. This paper reports our automatic method to segregate CB and OLs, in particular under conditions where the signal to noise ratio (SNR) is low, the variation of the image intensity is big, and the relative displacement of OLs and CB is substantial. We design an algorithm to find a minimum-cost 3D surface in a 3D image stack to best separate an OL (of one side, either left or right) from CB. This surface is defined as an aggregation of the respective minimum-cost curves detected in each individual 2D image slice. Each curve is defined by a list of control points that best segregate OL and CB. To obtain the locations of these control points, we derive an energy function that includes an image energy term defined by local pixel intensities and two internal energy terms that constrain the curve's smoothness and length. Gradient descent method is used to optimize this energy function. To improve both the speed and robustness of the method, for each stack, the locations of optimized control points in a slice are taken as the initialization prior for the next slice. We have tested this approach on simulated and real 3D fly brain image stacks and demonstrated that this method can reasonably segregate OLs from CBs despite the aforementioned difficulties.
Lam
Shing Chun Benny
SC
Janelia Farm Research Campus, Howard Hughes Medical Institute, 19700 Helix Drive, Ashburn, VA 20147, USA.
Ruan
Zongcai
Z
Zhao
Ting
T
Long
Fuhui
F
Jenett
Arnim
A
Simpson
Julie
J
Myers
Eugene W
EW
Peng
Hanchuan
H
D000465:Algorithms; D000818:Animals; D001331:Automation; D001921:Brain / Q000473:pathology*; D001931:Brain Mapping / Q000379:methods*; D003196:Computer Graphics; D003198:Computer Simulation; D004331:Drosophila melanogaster; D007089:Image Enhancement / Q000379:methods; D007090:Image Interpretation, Computer-Assisted / Q000379:methods; D021621:Imaging, Three-Dimensional / Q000379:methods; D018613:Microscopy, Confocal / Q000379:methods*; D015233:Models, Statistical; D009899:Optic Lobe, Nonmammalian / Q000033:anatomy & histology* / Q000502:physiology; D015203:Reproducibility of Results
Neuron. 1999 Mar;22(3):451-61
10197526
Genetics. 2004 Apr;166(4):1775-82
15126397
BMC Bioinformatics. 2006 Dec 29;7:544
17196102
Comput Methods Programs Biomed. 2008 Mar;89(3):239-47
18178286
Bioinformatics. 2008 Sep 1;24(17):1827-36
18603566
IEEE Trans Image Process. 2001;10(2):266-77
18249617
Bioinformatics. 2008 Jan 15;24(2):234-42
18025002
Annu Rev Biomed Eng. 2000;2:315-37
11701515
Proc Natl Acad Sci U S A. 2008 Jul 15;105(28):9715-20
18621688
Development. 1993 Jun;118(2):401-15
8223268
J Comp Neurol. 2006 Aug 20;497(6):928-58
16802334
J Comp Neurol. 2005 Nov 7;492(1):1-19
16175557
IEEE Trans Image Process. 1998;7(3):359-69
18276256
Cell Tissue Res. 2008 Jul;333(1):125-45
18504618
IEEE Trans Pattern Anal Mach Intell. 2007 Jul;29(7):1274-9
17496384