Group Work 1: Building your Own Segmentation and Spot Detection Pipeline

Group Work 1: Building your Own Segmentation and Spot Detection Pipeline#

Let’s now consolidate what you have learned! These exercises will walk you through how to create your own Jupyter Notebook containing code that segments images with Cellpose and detects spots with Spotiflow.

The images we will use for this exercise can be downloaded from the Group Work 1 Dataset.

To go through these exercises, you need to create a new folder named bobiac_group_work. In the instruction below, we will assume this folder is on your Desktop but you can choose a different location if you prefer.

Step 1#

Create a new Jupyter Notebook with uv’s juv tool

  1. Open a new Terminal or PowerShell and navigate to the bobiac_group_work folder.

  2. Inside the bobiac_group_work folder, create a new folder named group_work_1 and navigate into it.

  3. Inside the group_work_1, create a new Jupyter Notebook named group_work_1.ipynb using uv’s juv tool.

  4. Run the notebook in your browser using juv.\

  5. Close the notebook tab in your browser and stop the notebook from the terminal (cmd + c or ctrl + c) before proceeding to Step 2.

Solution

  1. Open the Terminal or PowerShell.

  2. cd .../Desktop/bobiac_group_work

  3. mkdir group_work_1

  4. cd .../Desktop/bobiac_group_work/group_work_1

  5. uvx juv init group_work_1.ipynb

  6. uvx juv run group_work_1.ipynb

  7. Close the notebook tab in your browser and stop the notebook from the terminal (cmd + c or ctrl + c)

Step 2#

Add dependencies to the Jupyter Notebook with juv

  1. In your notebook created in Step 1, add your dependencies using juv.

    Note

    It is up to you which dependencies you want to add based on what we covered during the course. If you forget a dependency, you can always close the notebook in both the browser and the terminal, add the dependency, and re-run the notebook.

  2. Run the notebook with juv.

  3. Import the libraries in the first cell.

  4. Run the cell to confirm that they are installed and can be imported without errors.

Note

If you would rather work in Google Colab instead of running the notebook locally, you can copy the .ipynb file you created to your Google Drive and open it from the Colab website.

Keep in mind that Colab does not support the PEP 723 inline script metadata that juv uses to manage dependencies. This means you will need to add a !pip install <package_name> cell for each dependency, and run it before the cell that imports the libraries.

Solution

  1. cd .../Desktop/bobiac_group_work/group_work_1 (the folder created in Step 1)

  2. uvx juv add group_work_1.ipynb cellpose tqdm tifffile spotiflow

  3. uvx juv run group_work_1.ipynb

  4. Add a new code cell in the notebook (+ button)

  5. Within this cell, import the necessary libraries:

    from pathlib import Path

from cellpose import core, io, models, plot
from cellpose.models import MODEL_DIR
from tqdm import tqdm

import csv

import tifffile
from spotiflow.model import Spotiflow
import numpy as np

  6. Run the cell to confirm that the libraries are imported without errors.

Step 3#

Run Cellpose on the full dataset

In this step you need to add the code that segments nuclei and cytoplasm of all the images in the dataset using Cellpose and saves the segmentation as a .tif file.

You need to segment both the nuclei and cytoplasm of the images. The nuclei are in channel 0 and the cytoplasm is in channel 1.

Tip

To get the nuclei segmentation, you can pass only the nuclei channel (channel 0) to the Cellpose eval method. To get the cytoplasm segmentation, you can pass both channels (0 and 1).

  1. For each step, create a new code cell in the notebook (+ button).

  2. Within the cell, add the necessary code.

Solution

See Solution Notebook

Step 4#

Run Spotiflow on the full dataset

In this step you need to add the code that detects spots in the 4th channels of all the images in the dataset using Spotiflow and saves a .csv file of their coordinates.

  1. For each step, create a new code cell in the notebook (+ button).

  2. Within the cell, add the necessary code.

Solution

See Solution Notebook