Detail of Fig6_Edensa_auto
Project
SSBD:Repository
Title
Bright-field and chloroplast autofluorescence images of Egeria densa
Description
This dataset was acquired to establish the deep-learning model for the virtual staining of plant cell structures. It comprises autofluorescence images of chloroplasts in Egeria densa, highlighting the intrinsic fluorescence of chloroplasts (red) against bright-field images. There are 119 frames in total, with 109 frames allocated for training and 10 frames for testing. The combination of bright-field and autofluorescence images in this stack supports virtual staining of chloroplasts to study their distribution and movement. ch1; intrinsic fluorescence of chloroplasts, ch2; bright field. This dataset is the same as the one registered on Figshare. https://doi.org/10.6084/m9.figshare.27247620.v1
Release, Updated
2026-09-30
License
CC BY 4.0
Kind
Image data
File Formats
.tif
Data size
1.9 GB
Datatype
-
Molecular Function (MF)
Biological Process (BP)
Cellular Component (CC)
chloroplast
Biological Imaging Method
spinning disk confocal microscopy
(
Fbbi:00000253
)
X scale
0.28 micrometer
Y scale
0.28 micrometer
Z scale
-
T scale
-
Image Acquisition
Experiment type
-
Microscope type
-
Acquisition mode
-
Contrast method
-
Microscope model
-
Detector model
-
Objective model
-
Filter set
-
Summary of Methods
Ichita M, Yamamichi H, Higaki T. Virtual staining from bright-field microscopy for label-free quantitative analysis of plant cell structures. Plant Molecular Biology. 2025;115(1):29.
Related paper(s)
Contact
Takumi Higaki
, Kumamoto University
, Graduate School of Science and Technology
, Graduate School of Science and Technology
Contributors
OMERO Project