3DFM_AC and 3DFM_BCPop Datasets
Description
Two fluorescent microscopy image datasets of retinal neurons and neural populations. 3DFM_AC: A dataset of 22 3D fluorescent microscopy stacks acquired of individual EYFP-expressing Starburst Amacrine Cells (SACs) from the mouse retina and their corresponding ground truths. Each SAC was acquired 8 times with 5 differing laser powers (0.81uW, 1.85uW, 3.84uW, 7.71uW, 15.70uW). The xy-resolution and z-resolution of the acquired stacks were 0.621um and 0.100um respectively. 3DFM_BCPop: A dataset of 2 fluorescent microscopy stacks acquired of GFP-expressing Bipolar Type 2 Cell populations from the mouse retina and their corresponding ground truths. Each Bipolar Cell population was acquired by averaging 8 frames with a laser power of 15.70uW. The xy-resolution and z-resolution of the acquired stacks were 0.155um and 0.100um respectively.
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Steps to reproduce
Animal procedures were conducted according to institutional guidelines and approved by the NINDS Animal Care and Use Committee (ASP-1344). For our 3DFM_AC dataset, ChAT-Cre mice (Ivanova et al. (2010)) were intravitreally injected with 2uL of AAV-7m8-EF1a-BbTagBY virus with a ∽0.8×10e12 vg/mL titration (Cai et al. (2013)). Retinas were then dissected 3-4 weeks after injection, fixed with 4% paraformaldehyde for 45 minutes, and washed three times. A confocal microscope (Zeiss LSM 510) with a Plan-Neofluar 40x/1.3 Oil objective, a 488 laser line, and a BP505-530 filter was then used to acquire stacks of the fixed retinas. To acquire the 3DFM_BCPop dataset, the retina of a Syt2 mouse was dissected, fixed, and imaged using the same protocol with only a laser power of 15.70uW and a magnification of 0.25. Ground truths were created for both datasets by inputting the highest quality available image into a Frangi filter and then binarizing the output of that filter. References: [1] Ivanova, E., Hwang, G.S., Pan, Z.H., 2010. Characterization of transgenic mouse lines expressing cre recombinase in the retina. Neuroscience 165, 233–243. [2] Cai, D., Cohen, K.B., Luo, T., Lichtman, J.W., Sanes, J.R., 2013. Improved tools for the brainbow toolbox. Nature methods 10, 540–547.