Nov 29, 2023
Brain image simulation protocol
- 1University of Cambridge
Protocol Citation: Bin Fu 2023. Brain image simulation protocol. protocols.io https://dx.doi.org/10.17504/protocols.io.4r3l22bxql1y/v1
License: This is an open access protocol distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited
Protocol status: Working
We use this protocol and it's working
Created: November 29, 2023
Last Modified: May 31, 2024
Protocol Integer ID: 91567
Keywords: ASAPCRN
Funders Acknowledgement:
Aligning Science Across Parkinson's
Grant ID: ASAP-000509
Abstract
This protocol details the method for simulating a brain image with small and large features
Attachments
Materials
File required: ‘imageSimulation’ folder
Toolbox required: Statistics and Machine Learning Toolbox, image processing toolbox
1. Prepare negative control images where no fluorescent puncta were labelled. These images are considered as background images.
2. Select one or several cropped images containing large aggregates in the library and apply a sigmoid function to the selected cropped image where x in the sigmoid function is determined by the distance to the large aggregate in the cropped image.
Simulate small puncta with 2D gaussian distribution on a blank image (same image size as the negative control image), the number of which should be determined from real images. The sigma of puncta should be determined from real images as well.
Add cropped large aggregates onto the background images at a random location. Then add the simulated puncta onto the background image to form a simulated image with both small and large features.
Record position, intensity and background information per small puncta expect for those overlapping with the large aggregates in the simulated image and save the results.
Repeat step2 to 5 again for other background images