2018
DOI: 10.1007/978-1-4939-8712-2_1
|View full text |Cite
|
Sign up to set email alerts
|

Three-Dimensional Visualization of the Lymphatic Vasculature

Help me understand this report

Search citation statements

Order By: Relevance

Paper Sections

Select...
2
1
1
1

Citation Types

0
10
0

Year Published

2020
2020
2024
2024

Publication Types

Select...
3
3

Relationship

5
1

Authors

Journals

citations
Cited by 8 publications
(10 citation statements)
references
References 13 publications
0
10
0
Order By: Relevance
“…The results reported here were obtained with a basic single objective configuration, illuminated by a dual sided light sheet and we visualized image stacks using our proprietary volume-rendering framework Voreen ( Meyer-Spradow et al, 2009 ; Dierkes et al, 2018 ). We analyzed the same immunostained liver biopsy specimen with LSFM that was later also imaged using OPT.…”
Section: Resultsmentioning
confidence: 99%
“…The results reported here were obtained with a basic single objective configuration, illuminated by a dual sided light sheet and we visualized image stacks using our proprietary volume-rendering framework Voreen ( Meyer-Spradow et al, 2009 ; Dierkes et al, 2018 ). We analyzed the same immunostained liver biopsy specimen with LSFM that was later also imaged using OPT.…”
Section: Resultsmentioning
confidence: 99%
“…Therefore, we used wholemount immunostaining with an RFP antibody to counterstain all tissue specimen derived from a Vegfr3 -tdTomato pup at P5 that were subsequently cleared following the BABB protocol (Fig 6). 3D-volume rendering of image stacks was performed using the open source visualization software package Voreen [37, 38]. In the lung a highly branched lymphatic network was observed lancing both lobes to the level of the terminal bronchioles (Fig 6 A-C).…”
Section: Resultsmentioning
confidence: 99%
“…For image acquisition, Z-steps 3 μm were chosen. 3D reconstruction and analysis of ultramicroscopy stacks were performed by using the volume rendering software Voreen [37, 48].…”
Section: Methodsmentioning
confidence: 99%
“…We applied this hierarchical random walker approach first to a 60 GB data set that covered 52 mm 3 of a BABBcleared, anti-PECAM1-stained mouse kidney. Labeling of seeds was done in a similar fashion as described by Prassni et al (Prassni et al, 2010) using a multi-view interface of the data: The input data set and the intermediate segmentation results were rendered in 3D using the OpenCL raycaster of Voreen (Figure 7 and Video S3) (Dierkes et al, 2018). Vessels of a total length of 160 mm enclosing a volume of 0.35 mm 3 and comprising the renal vasculature to the level of the interlobular vasculature were segmented interactively (Figures 7B, 7E, and 7H).…”
Section: Semi-automatic Segmentation and Analysis Of Vascular Network In Large Light Sheet Microscopy-based Data Setsmentioning
confidence: 99%