Skip to content
New issue

Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.

Sign up for GitHub

By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.

Already on GitHub? Sign in to your account

HTML to markdown #106

Merged
merged 1 commit into from
Jul 9, 2024
Merged

HTML to markdown #106

Changes from all commits
Commits
Show all changes
1 commit
Select commit
File filter

Filter by extension

Filter by extension
Conversations
Failed to load comments.
Loading
Jump to
Jump to file
Failed to load files.
Loading
Diff view
Diff view
32 changes: 16 additions & 16 deletions examples/demo_dlmbl/solution.py
View file
Open in desktop
Original file line number Diff line number Diff line change
@@ -1,21 +1,21 @@
# %% [markdown]
"""
<div style="text-align: left;">
<h1>Image translation (Virtual Staining)</h1>
<hr>
<h3>Overview</h3>
<p>In this exercise, we will predict fluorescence images of nuclei and membrane markers from quantitative phase images of cells, i.e., we will <i>virtually stain</i> the nuclei and cell membrane visible in the phase image. This is an example of an image translation task. We will apply spatial and intensity augmentations to train robust models and evaluate their performance. Finally, we will explore the opposite process of predicting a phase image from a fluorescence membrane label.</p>

<div style="text-align: center;">
<br><br>
<figure>
<a href="https://github.com/mehta-lab/VisCy/assets/67518483/d53a81eb-eb37-44f3-b522-8bd7bddc7755" target="_blank">
<img src="https://raw.githubusercontent.com/mehta-lab/VisCy/main/docs/figures/svideo_1.png" alt="Virtual Staining" style="width:800px;"/>
</a>
<figcaption>(click image to play)</figcaption>
</figure>
</div>
</div>
# Image translation (Virtual Staining)

## Overview

In this exercise, we will predict fluorescence images of
nuclei and plasma membrane markers from quantitative phase images of cells,
i.e., we will _virtually stain_ the nuclei and plasma membrane
visible in the phase image.
This is an example of an image translation task.
We will apply spatial and intensity augmentations to train robust models
and evaluate their performance.
Finally, we will explore the opposite process of predicting a phase image
from a fluorescence membrane label.

[![HEK293T](https://raw.githubusercontent.com/mehta-lab/VisCy/main/docs/figures/svideo_1.png)](https://github.com/mehta-lab/VisCy/assets/67518483/d53a81eb-eb37-44f3-b522-8bd7bddc7755)
(Click on image to play video)
"""

# %% [markdown]
Expand Down
Loading