Visualizing and analyzing EBSS data

This tutorial walks through how you can use livecellx to analyze and visualize EBSS data of single cells. It involves essential processes like loading imaging datasets, cell segmentation, feature extraction, and tracking single-cell trajectories over time.

[1]:
import numpy as np
import matplotlib.pyplot as plt
from cellpose import models
from cellpose.io import imread
import glob
from pathlib import Path
from PIL import Image, ImageSequence
from tqdm import tqdm
import os
import os.path
from livecellx import core
from livecellx.core import datasets
from livecellx.core.datasets import LiveCellImageDataset, SingleImageDataset
from skimage import measure
from livecellx.core import SingleCellTrajectory, SingleCellStatic

# import some common libraries
import numpy as np
import os, json, cv2, random
import cv2

Loading single cell imaging data:

The LiveCellImageDataset and SingleCellImageDataset from livecellx.core.datasets simplify the image loading process, ensuring the user doesn’t load everything directly into memory.

When you provide a path to these datasets, ensure the image files’ names are sorted in chronological order, since the order is determined by string sorting. This means that “T10” (10th time point) comes before “T2” if you don’t use proper left-trailing zeroes.

For those with unique naming patterns, you can provide a dictionary (time2url) mapping the time points to the file locations.

[2]:
# dataset_dir_path = Path(
#     "../datasets/test_data_STAV-A549/DIC_data"
# )

# mask_dataset_path = Path("../datasets/test_data_STAV-A549/mask_data")

dataset_dir_path = Path(
    "../datasets/EBSS_Starvation/tif_STAV-A549_VIM_24hours_NoTreat_NA_YL_Ti2e_2022-12-21/XY16/"
)

mask_dataset_path = Path("../datasets/EBSS_Starvation/tif_STAV-A549_VIM_24hours_NoTreat_NA_YL_Ti2e_2022-12-21/out/XY16/seg")
[3]:
mask_dataset = LiveCellImageDataset(mask_dataset_path, ext="png")
mask_dataset.time2url
291 png img file paths loaded:
[3]:
{0: '../datasets/EBSS_Starvation/tif_STAV-A549_VIM_24hours_NoTreat_NA_YL_Ti2e_2022-12-21/out/XY16/seg/seg_STAV-A549_VIM_24hours_NoTreat_NA_YL_Ti2e_2022-12-21_T001_XY16_DIC.tif.png',
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 2: '../datasets/EBSS_Starvation/tif_STAV-A549_VIM_24hours_NoTreat_NA_YL_Ti2e_2022-12-21/out/XY16/seg/seg_STAV-A549_VIM_24hours_NoTreat_NA_YL_Ti2e_2022-12-21_T003_XY16_DIC.tif.png',
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 239: '../datasets/EBSS_Starvation/tif_STAV-A549_VIM_24hours_NoTreat_NA_YL_Ti2e_2022-12-21/out/XY16/seg/seg_STAV-A549_VIM_24hours_NoTreat_NA_YL_Ti2e_2022-12-21_T240_XY16_DIC.tif.png',
 240: '../datasets/EBSS_Starvation/tif_STAV-A549_VIM_24hours_NoTreat_NA_YL_Ti2e_2022-12-21/out/XY16/seg/seg_STAV-A549_VIM_24hours_NoTreat_NA_YL_Ti2e_2022-12-21_T241_XY16_DIC.tif.png',
 241: '../datasets/EBSS_Starvation/tif_STAV-A549_VIM_24hours_NoTreat_NA_YL_Ti2e_2022-12-21/out/XY16/seg/seg_STAV-A549_VIM_24hours_NoTreat_NA_YL_Ti2e_2022-12-21_T242_XY16_DIC.tif.png',
 242: '../datasets/EBSS_Starvation/tif_STAV-A549_VIM_24hours_NoTreat_NA_YL_Ti2e_2022-12-21/out/XY16/seg/seg_STAV-A549_VIM_24hours_NoTreat_NA_YL_Ti2e_2022-12-21_T243_XY16_DIC.tif.png',
 243: '../datasets/EBSS_Starvation/tif_STAV-A549_VIM_24hours_NoTreat_NA_YL_Ti2e_2022-12-21/out/XY16/seg/seg_STAV-A549_VIM_24hours_NoTreat_NA_YL_Ti2e_2022-12-21_T244_XY16_DIC.tif.png',
 244: '../datasets/EBSS_Starvation/tif_STAV-A549_VIM_24hours_NoTreat_NA_YL_Ti2e_2022-12-21/out/XY16/seg/seg_STAV-A549_VIM_24hours_NoTreat_NA_YL_Ti2e_2022-12-21_T245_XY16_DIC.tif.png',
 245: '../datasets/EBSS_Starvation/tif_STAV-A549_VIM_24hours_NoTreat_NA_YL_Ti2e_2022-12-21/out/XY16/seg/seg_STAV-A549_VIM_24hours_NoTreat_NA_YL_Ti2e_2022-12-21_T246_XY16_DIC.tif.png',
 246: '../datasets/EBSS_Starvation/tif_STAV-A549_VIM_24hours_NoTreat_NA_YL_Ti2e_2022-12-21/out/XY16/seg/seg_STAV-A549_VIM_24hours_NoTreat_NA_YL_Ti2e_2022-12-21_T247_XY16_DIC.tif.png',
 247: '../datasets/EBSS_Starvation/tif_STAV-A549_VIM_24hours_NoTreat_NA_YL_Ti2e_2022-12-21/out/XY16/seg/seg_STAV-A549_VIM_24hours_NoTreat_NA_YL_Ti2e_2022-12-21_T248_XY16_DIC.tif.png',
 248: '../datasets/EBSS_Starvation/tif_STAV-A549_VIM_24hours_NoTreat_NA_YL_Ti2e_2022-12-21/out/XY16/seg/seg_STAV-A549_VIM_24hours_NoTreat_NA_YL_Ti2e_2022-12-21_T249_XY16_DIC.tif.png',
 249: '../datasets/EBSS_Starvation/tif_STAV-A549_VIM_24hours_NoTreat_NA_YL_Ti2e_2022-12-21/out/XY16/seg/seg_STAV-A549_VIM_24hours_NoTreat_NA_YL_Ti2e_2022-12-21_T250_XY16_DIC.tif.png',
 250: '../datasets/EBSS_Starvation/tif_STAV-A549_VIM_24hours_NoTreat_NA_YL_Ti2e_2022-12-21/out/XY16/seg/seg_STAV-A549_VIM_24hours_NoTreat_NA_YL_Ti2e_2022-12-21_T251_XY16_DIC.tif.png',
 251: '../datasets/EBSS_Starvation/tif_STAV-A549_VIM_24hours_NoTreat_NA_YL_Ti2e_2022-12-21/out/XY16/seg/seg_STAV-A549_VIM_24hours_NoTreat_NA_YL_Ti2e_2022-12-21_T252_XY16_DIC.tif.png',
 252: '../datasets/EBSS_Starvation/tif_STAV-A549_VIM_24hours_NoTreat_NA_YL_Ti2e_2022-12-21/out/XY16/seg/seg_STAV-A549_VIM_24hours_NoTreat_NA_YL_Ti2e_2022-12-21_T253_XY16_DIC.tif.png',
 253: '../datasets/EBSS_Starvation/tif_STAV-A549_VIM_24hours_NoTreat_NA_YL_Ti2e_2022-12-21/out/XY16/seg/seg_STAV-A549_VIM_24hours_NoTreat_NA_YL_Ti2e_2022-12-21_T254_XY16_DIC.tif.png',
 254: '../datasets/EBSS_Starvation/tif_STAV-A549_VIM_24hours_NoTreat_NA_YL_Ti2e_2022-12-21/out/XY16/seg/seg_STAV-A549_VIM_24hours_NoTreat_NA_YL_Ti2e_2022-12-21_T255_XY16_DIC.tif.png',
 255: '../datasets/EBSS_Starvation/tif_STAV-A549_VIM_24hours_NoTreat_NA_YL_Ti2e_2022-12-21/out/XY16/seg/seg_STAV-A549_VIM_24hours_NoTreat_NA_YL_Ti2e_2022-12-21_T256_XY16_DIC.tif.png',
 256: '../datasets/EBSS_Starvation/tif_STAV-A549_VIM_24hours_NoTreat_NA_YL_Ti2e_2022-12-21/out/XY16/seg/seg_STAV-A549_VIM_24hours_NoTreat_NA_YL_Ti2e_2022-12-21_T257_XY16_DIC.tif.png',
 257: '../datasets/EBSS_Starvation/tif_STAV-A549_VIM_24hours_NoTreat_NA_YL_Ti2e_2022-12-21/out/XY16/seg/seg_STAV-A549_VIM_24hours_NoTreat_NA_YL_Ti2e_2022-12-21_T258_XY16_DIC.tif.png',
 258: '../datasets/EBSS_Starvation/tif_STAV-A549_VIM_24hours_NoTreat_NA_YL_Ti2e_2022-12-21/out/XY16/seg/seg_STAV-A549_VIM_24hours_NoTreat_NA_YL_Ti2e_2022-12-21_T259_XY16_DIC.tif.png',
 259: '../datasets/EBSS_Starvation/tif_STAV-A549_VIM_24hours_NoTreat_NA_YL_Ti2e_2022-12-21/out/XY16/seg/seg_STAV-A549_VIM_24hours_NoTreat_NA_YL_Ti2e_2022-12-21_T260_XY16_DIC.tif.png',
 260: '../datasets/EBSS_Starvation/tif_STAV-A549_VIM_24hours_NoTreat_NA_YL_Ti2e_2022-12-21/out/XY16/seg/seg_STAV-A549_VIM_24hours_NoTreat_NA_YL_Ti2e_2022-12-21_T261_XY16_DIC.tif.png',
 261: '../datasets/EBSS_Starvation/tif_STAV-A549_VIM_24hours_NoTreat_NA_YL_Ti2e_2022-12-21/out/XY16/seg/seg_STAV-A549_VIM_24hours_NoTreat_NA_YL_Ti2e_2022-12-21_T262_XY16_DIC.tif.png',
 262: '../datasets/EBSS_Starvation/tif_STAV-A549_VIM_24hours_NoTreat_NA_YL_Ti2e_2022-12-21/out/XY16/seg/seg_STAV-A549_VIM_24hours_NoTreat_NA_YL_Ti2e_2022-12-21_T263_XY16_DIC.tif.png',
 263: '../datasets/EBSS_Starvation/tif_STAV-A549_VIM_24hours_NoTreat_NA_YL_Ti2e_2022-12-21/out/XY16/seg/seg_STAV-A549_VIM_24hours_NoTreat_NA_YL_Ti2e_2022-12-21_T264_XY16_DIC.tif.png',
 264: '../datasets/EBSS_Starvation/tif_STAV-A549_VIM_24hours_NoTreat_NA_YL_Ti2e_2022-12-21/out/XY16/seg/seg_STAV-A549_VIM_24hours_NoTreat_NA_YL_Ti2e_2022-12-21_T265_XY16_DIC.tif.png',
 265: '../datasets/EBSS_Starvation/tif_STAV-A549_VIM_24hours_NoTreat_NA_YL_Ti2e_2022-12-21/out/XY16/seg/seg_STAV-A549_VIM_24hours_NoTreat_NA_YL_Ti2e_2022-12-21_T266_XY16_DIC.tif.png',
 266: '../datasets/EBSS_Starvation/tif_STAV-A549_VIM_24hours_NoTreat_NA_YL_Ti2e_2022-12-21/out/XY16/seg/seg_STAV-A549_VIM_24hours_NoTreat_NA_YL_Ti2e_2022-12-21_T267_XY16_DIC.tif.png',
 267: '../datasets/EBSS_Starvation/tif_STAV-A549_VIM_24hours_NoTreat_NA_YL_Ti2e_2022-12-21/out/XY16/seg/seg_STAV-A549_VIM_24hours_NoTreat_NA_YL_Ti2e_2022-12-21_T268_XY16_DIC.tif.png',
 268: '../datasets/EBSS_Starvation/tif_STAV-A549_VIM_24hours_NoTreat_NA_YL_Ti2e_2022-12-21/out/XY16/seg/seg_STAV-A549_VIM_24hours_NoTreat_NA_YL_Ti2e_2022-12-21_T269_XY16_DIC.tif.png',
 269: '../datasets/EBSS_Starvation/tif_STAV-A549_VIM_24hours_NoTreat_NA_YL_Ti2e_2022-12-21/out/XY16/seg/seg_STAV-A549_VIM_24hours_NoTreat_NA_YL_Ti2e_2022-12-21_T270_XY16_DIC.tif.png',
 270: '../datasets/EBSS_Starvation/tif_STAV-A549_VIM_24hours_NoTreat_NA_YL_Ti2e_2022-12-21/out/XY16/seg/seg_STAV-A549_VIM_24hours_NoTreat_NA_YL_Ti2e_2022-12-21_T271_XY16_DIC.tif.png',
 271: '../datasets/EBSS_Starvation/tif_STAV-A549_VIM_24hours_NoTreat_NA_YL_Ti2e_2022-12-21/out/XY16/seg/seg_STAV-A549_VIM_24hours_NoTreat_NA_YL_Ti2e_2022-12-21_T272_XY16_DIC.tif.png',
 272: '../datasets/EBSS_Starvation/tif_STAV-A549_VIM_24hours_NoTreat_NA_YL_Ti2e_2022-12-21/out/XY16/seg/seg_STAV-A549_VIM_24hours_NoTreat_NA_YL_Ti2e_2022-12-21_T273_XY16_DIC.tif.png',
 273: '../datasets/EBSS_Starvation/tif_STAV-A549_VIM_24hours_NoTreat_NA_YL_Ti2e_2022-12-21/out/XY16/seg/seg_STAV-A549_VIM_24hours_NoTreat_NA_YL_Ti2e_2022-12-21_T274_XY16_DIC.tif.png',
 274: '../datasets/EBSS_Starvation/tif_STAV-A549_VIM_24hours_NoTreat_NA_YL_Ti2e_2022-12-21/out/XY16/seg/seg_STAV-A549_VIM_24hours_NoTreat_NA_YL_Ti2e_2022-12-21_T275_XY16_DIC.tif.png',
 275: '../datasets/EBSS_Starvation/tif_STAV-A549_VIM_24hours_NoTreat_NA_YL_Ti2e_2022-12-21/out/XY16/seg/seg_STAV-A549_VIM_24hours_NoTreat_NA_YL_Ti2e_2022-12-21_T276_XY16_DIC.tif.png',
 276: '../datasets/EBSS_Starvation/tif_STAV-A549_VIM_24hours_NoTreat_NA_YL_Ti2e_2022-12-21/out/XY16/seg/seg_STAV-A549_VIM_24hours_NoTreat_NA_YL_Ti2e_2022-12-21_T277_XY16_DIC.tif.png',
 277: '../datasets/EBSS_Starvation/tif_STAV-A549_VIM_24hours_NoTreat_NA_YL_Ti2e_2022-12-21/out/XY16/seg/seg_STAV-A549_VIM_24hours_NoTreat_NA_YL_Ti2e_2022-12-21_T278_XY16_DIC.tif.png',
 278: '../datasets/EBSS_Starvation/tif_STAV-A549_VIM_24hours_NoTreat_NA_YL_Ti2e_2022-12-21/out/XY16/seg/seg_STAV-A549_VIM_24hours_NoTreat_NA_YL_Ti2e_2022-12-21_T279_XY16_DIC.tif.png',
 279: '../datasets/EBSS_Starvation/tif_STAV-A549_VIM_24hours_NoTreat_NA_YL_Ti2e_2022-12-21/out/XY16/seg/seg_STAV-A549_VIM_24hours_NoTreat_NA_YL_Ti2e_2022-12-21_T280_XY16_DIC.tif.png',
 280: '../datasets/EBSS_Starvation/tif_STAV-A549_VIM_24hours_NoTreat_NA_YL_Ti2e_2022-12-21/out/XY16/seg/seg_STAV-A549_VIM_24hours_NoTreat_NA_YL_Ti2e_2022-12-21_T281_XY16_DIC.tif.png',
 281: '../datasets/EBSS_Starvation/tif_STAV-A549_VIM_24hours_NoTreat_NA_YL_Ti2e_2022-12-21/out/XY16/seg/seg_STAV-A549_VIM_24hours_NoTreat_NA_YL_Ti2e_2022-12-21_T282_XY16_DIC.tif.png',
 282: '../datasets/EBSS_Starvation/tif_STAV-A549_VIM_24hours_NoTreat_NA_YL_Ti2e_2022-12-21/out/XY16/seg/seg_STAV-A549_VIM_24hours_NoTreat_NA_YL_Ti2e_2022-12-21_T283_XY16_DIC.tif.png',
 283: '../datasets/EBSS_Starvation/tif_STAV-A549_VIM_24hours_NoTreat_NA_YL_Ti2e_2022-12-21/out/XY16/seg/seg_STAV-A549_VIM_24hours_NoTreat_NA_YL_Ti2e_2022-12-21_T284_XY16_DIC.tif.png',
 284: '../datasets/EBSS_Starvation/tif_STAV-A549_VIM_24hours_NoTreat_NA_YL_Ti2e_2022-12-21/out/XY16/seg/seg_STAV-A549_VIM_24hours_NoTreat_NA_YL_Ti2e_2022-12-21_T285_XY16_DIC.tif.png',
 285: '../datasets/EBSS_Starvation/tif_STAV-A549_VIM_24hours_NoTreat_NA_YL_Ti2e_2022-12-21/out/XY16/seg/seg_STAV-A549_VIM_24hours_NoTreat_NA_YL_Ti2e_2022-12-21_T286_XY16_DIC.tif.png',
 286: '../datasets/EBSS_Starvation/tif_STAV-A549_VIM_24hours_NoTreat_NA_YL_Ti2e_2022-12-21/out/XY16/seg/seg_STAV-A549_VIM_24hours_NoTreat_NA_YL_Ti2e_2022-12-21_T287_XY16_DIC.tif.png',
 287: '../datasets/EBSS_Starvation/tif_STAV-A549_VIM_24hours_NoTreat_NA_YL_Ti2e_2022-12-21/out/XY16/seg/seg_STAV-A549_VIM_24hours_NoTreat_NA_YL_Ti2e_2022-12-21_T288_XY16_DIC.tif.png',
 288: '../datasets/EBSS_Starvation/tif_STAV-A549_VIM_24hours_NoTreat_NA_YL_Ti2e_2022-12-21/out/XY16/seg/seg_STAV-A549_VIM_24hours_NoTreat_NA_YL_Ti2e_2022-12-21_T289_XY16_DIC.tif.png',
 289: '../datasets/EBSS_Starvation/tif_STAV-A549_VIM_24hours_NoTreat_NA_YL_Ti2e_2022-12-21/out/XY16/seg/seg_STAV-A549_VIM_24hours_NoTreat_NA_YL_Ti2e_2022-12-21_T290_XY16_DIC.tif.png',
 290: '../datasets/EBSS_Starvation/tif_STAV-A549_VIM_24hours_NoTreat_NA_YL_Ti2e_2022-12-21/out/XY16/seg/seg_STAV-A549_VIM_24hours_NoTreat_NA_YL_Ti2e_2022-12-21_T291_XY16_DIC.tif.png'}
[4]:
time2url = sorted(glob.glob(str((Path(dataset_dir_path) / Path("*_DIC.tif")))))
time2url = {i: path for i, path in enumerate(time2url)}
dic_dataset = LiveCellImageDataset(time2url=time2url, ext="tif")
# dic_dataset = LiveCellImageDataset(dataset_dir_path, ext="tif")

Check if the time2url mapping is correct

[5]:
dic_dataset.time2url
[5]:
{0: '../datasets/EBSS_Starvation/tif_STAV-A549_VIM_24hours_NoTreat_NA_YL_Ti2e_2022-12-21/XY16/STAV-A549_VIM_24hours_NoTreat_NA_YL_Ti2e_2022-12-21_T001_XY16_DIC.tif',
 1: '../datasets/EBSS_Starvation/tif_STAV-A549_VIM_24hours_NoTreat_NA_YL_Ti2e_2022-12-21/XY16/STAV-A549_VIM_24hours_NoTreat_NA_YL_Ti2e_2022-12-21_T002_XY16_DIC.tif',
 2: '../datasets/EBSS_Starvation/tif_STAV-A549_VIM_24hours_NoTreat_NA_YL_Ti2e_2022-12-21/XY16/STAV-A549_VIM_24hours_NoTreat_NA_YL_Ti2e_2022-12-21_T003_XY16_DIC.tif',
 3: '../datasets/EBSS_Starvation/tif_STAV-A549_VIM_24hours_NoTreat_NA_YL_Ti2e_2022-12-21/XY16/STAV-A549_VIM_24hours_NoTreat_NA_YL_Ti2e_2022-12-21_T004_XY16_DIC.tif',
 4: '../datasets/EBSS_Starvation/tif_STAV-A549_VIM_24hours_NoTreat_NA_YL_Ti2e_2022-12-21/XY16/STAV-A549_VIM_24hours_NoTreat_NA_YL_Ti2e_2022-12-21_T005_XY16_DIC.tif',
 5: '../datasets/EBSS_Starvation/tif_STAV-A549_VIM_24hours_NoTreat_NA_YL_Ti2e_2022-12-21/XY16/STAV-A549_VIM_24hours_NoTreat_NA_YL_Ti2e_2022-12-21_T006_XY16_DIC.tif',
 6: '../datasets/EBSS_Starvation/tif_STAV-A549_VIM_24hours_NoTreat_NA_YL_Ti2e_2022-12-21/XY16/STAV-A549_VIM_24hours_NoTreat_NA_YL_Ti2e_2022-12-21_T007_XY16_DIC.tif',
 7: '../datasets/EBSS_Starvation/tif_STAV-A549_VIM_24hours_NoTreat_NA_YL_Ti2e_2022-12-21/XY16/STAV-A549_VIM_24hours_NoTreat_NA_YL_Ti2e_2022-12-21_T008_XY16_DIC.tif',
 8: '../datasets/EBSS_Starvation/tif_STAV-A549_VIM_24hours_NoTreat_NA_YL_Ti2e_2022-12-21/XY16/STAV-A549_VIM_24hours_NoTreat_NA_YL_Ti2e_2022-12-21_T009_XY16_DIC.tif',
 9: '../datasets/EBSS_Starvation/tif_STAV-A549_VIM_24hours_NoTreat_NA_YL_Ti2e_2022-12-21/XY16/STAV-A549_VIM_24hours_NoTreat_NA_YL_Ti2e_2022-12-21_T010_XY16_DIC.tif',
 10: '../datasets/EBSS_Starvation/tif_STAV-A549_VIM_24hours_NoTreat_NA_YL_Ti2e_2022-12-21/XY16/STAV-A549_VIM_24hours_NoTreat_NA_YL_Ti2e_2022-12-21_T011_XY16_DIC.tif',
 11: '../datasets/EBSS_Starvation/tif_STAV-A549_VIM_24hours_NoTreat_NA_YL_Ti2e_2022-12-21/XY16/STAV-A549_VIM_24hours_NoTreat_NA_YL_Ti2e_2022-12-21_T012_XY16_DIC.tif',
 12: '../datasets/EBSS_Starvation/tif_STAV-A549_VIM_24hours_NoTreat_NA_YL_Ti2e_2022-12-21/XY16/STAV-A549_VIM_24hours_NoTreat_NA_YL_Ti2e_2022-12-21_T013_XY16_DIC.tif',
 13: '../datasets/EBSS_Starvation/tif_STAV-A549_VIM_24hours_NoTreat_NA_YL_Ti2e_2022-12-21/XY16/STAV-A549_VIM_24hours_NoTreat_NA_YL_Ti2e_2022-12-21_T014_XY16_DIC.tif',
 14: '../datasets/EBSS_Starvation/tif_STAV-A549_VIM_24hours_NoTreat_NA_YL_Ti2e_2022-12-21/XY16/STAV-A549_VIM_24hours_NoTreat_NA_YL_Ti2e_2022-12-21_T015_XY16_DIC.tif',
 15: '../datasets/EBSS_Starvation/tif_STAV-A549_VIM_24hours_NoTreat_NA_YL_Ti2e_2022-12-21/XY16/STAV-A549_VIM_24hours_NoTreat_NA_YL_Ti2e_2022-12-21_T016_XY16_DIC.tif',
 16: '../datasets/EBSS_Starvation/tif_STAV-A549_VIM_24hours_NoTreat_NA_YL_Ti2e_2022-12-21/XY16/STAV-A549_VIM_24hours_NoTreat_NA_YL_Ti2e_2022-12-21_T017_XY16_DIC.tif',
 17: '../datasets/EBSS_Starvation/tif_STAV-A549_VIM_24hours_NoTreat_NA_YL_Ti2e_2022-12-21/XY16/STAV-A549_VIM_24hours_NoTreat_NA_YL_Ti2e_2022-12-21_T018_XY16_DIC.tif',
 18: '../datasets/EBSS_Starvation/tif_STAV-A549_VIM_24hours_NoTreat_NA_YL_Ti2e_2022-12-21/XY16/STAV-A549_VIM_24hours_NoTreat_NA_YL_Ti2e_2022-12-21_T019_XY16_DIC.tif',
 19: '../datasets/EBSS_Starvation/tif_STAV-A549_VIM_24hours_NoTreat_NA_YL_Ti2e_2022-12-21/XY16/STAV-A549_VIM_24hours_NoTreat_NA_YL_Ti2e_2022-12-21_T020_XY16_DIC.tif',
 20: '../datasets/EBSS_Starvation/tif_STAV-A549_VIM_24hours_NoTreat_NA_YL_Ti2e_2022-12-21/XY16/STAV-A549_VIM_24hours_NoTreat_NA_YL_Ti2e_2022-12-21_T021_XY16_DIC.tif',
 21: '../datasets/EBSS_Starvation/tif_STAV-A549_VIM_24hours_NoTreat_NA_YL_Ti2e_2022-12-21/XY16/STAV-A549_VIM_24hours_NoTreat_NA_YL_Ti2e_2022-12-21_T022_XY16_DIC.tif',
 22: '../datasets/EBSS_Starvation/tif_STAV-A549_VIM_24hours_NoTreat_NA_YL_Ti2e_2022-12-21/XY16/STAV-A549_VIM_24hours_NoTreat_NA_YL_Ti2e_2022-12-21_T023_XY16_DIC.tif',
 23: '../datasets/EBSS_Starvation/tif_STAV-A549_VIM_24hours_NoTreat_NA_YL_Ti2e_2022-12-21/XY16/STAV-A549_VIM_24hours_NoTreat_NA_YL_Ti2e_2022-12-21_T024_XY16_DIC.tif',
 24: '../datasets/EBSS_Starvation/tif_STAV-A549_VIM_24hours_NoTreat_NA_YL_Ti2e_2022-12-21/XY16/STAV-A549_VIM_24hours_NoTreat_NA_YL_Ti2e_2022-12-21_T025_XY16_DIC.tif',
 25: '../datasets/EBSS_Starvation/tif_STAV-A549_VIM_24hours_NoTreat_NA_YL_Ti2e_2022-12-21/XY16/STAV-A549_VIM_24hours_NoTreat_NA_YL_Ti2e_2022-12-21_T026_XY16_DIC.tif',
 26: '../datasets/EBSS_Starvation/tif_STAV-A549_VIM_24hours_NoTreat_NA_YL_Ti2e_2022-12-21/XY16/STAV-A549_VIM_24hours_NoTreat_NA_YL_Ti2e_2022-12-21_T027_XY16_DIC.tif',
 27: '../datasets/EBSS_Starvation/tif_STAV-A549_VIM_24hours_NoTreat_NA_YL_Ti2e_2022-12-21/XY16/STAV-A549_VIM_24hours_NoTreat_NA_YL_Ti2e_2022-12-21_T028_XY16_DIC.tif',
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If you wish to only consider a subset of the data (e.g., the first ten timepoints), use:

[6]:
max_time = 10
mask_dataset = mask_dataset.subset_by_time(0, max_time)
dic_dataset = dic_dataset.subset_by_time(0, max_time)

Processing and visualizing single cells:

After loading the data, the next step involves processing the data to identify individual cells and visualize them:

[7]:
from skimage.measure import regionprops
from livecellx.segment.utils import prep_scs_from_mask_dataset
single_cells = prep_scs_from_mask_dataset(mask_dataset, dic_dataset)
100%|██████████| 10/10 [00:10<00:00,  1.04s/it]
[8]:
for sc in single_cells:
    assert sc.mask_dataset
[10]:
len(single_cells)
[10]:
190
[11]:
single_cells_by_time = {}
for cell in single_cells:
    if cell.timeframe not in single_cells_by_time:
        single_cells_by_time[cell.timeframe] = []
    single_cells_by_time[cell.timeframe].append(cell)

Visualize one single cell

[12]:
sc = single_cells[0]

fig, axes = plt.subplots(1, 4, figsize=(10, 5))
sc.show(ax=axes[0])
sc.show_mask(ax=axes[1])
sc.show_contour_img(ax=axes[2])
sc.show_contour_mask(ax=axes[3])
[12]:
<Axes: >
../../_images/livecellx_notebooks_tutorials_tutorial_application_EBSS_16_1.png
[13]:
sc.show_panel(figsize=(15, 5))
[13]:
array([<Axes: title={'center': 'img'}>, <Axes: title={'center': 'mask'}>,
       <Axes: title={'center': 'contour_img'}>,
       <Axes: title={'center': 'contour_mask'}>,
       <Axes: title={'center': 'mask_crop'}>], dtype=object)
../../_images/livecellx_notebooks_tutorials_tutorial_application_EBSS_17_1.png
[14]:
sc1 = single_cells[1]
sc2 = single_cells[2]

Feature extraction:

For each identified cell, you can compute various features, such as shape and texture, which can help further in the analysis:

[15]:
from livecellx.trajectory.feature_extractors import compute_skimage_regionprops, compute_haralick_features

skimage_features = compute_skimage_regionprops(sc1)
sc1.add_feature("skimage", skimage_features)
[16]:
# haralick_features = compute_haralick_features(sc1)
# sc1.add_feature("haralick", haralick_features)
[17]:
sc1.get_feature_pd_series()
[17]:
skimage_area                 3173.000000
skimage_area_bbox            4488.000000
skimage_area_convex          3311.000000
skimage_area_filled          3173.000000
skimage_axis_major_length     101.795961
                                ...
skimage_orientation            -1.542148
skimage_perimeter             252.852814
skimage_perimeter_crofton     242.401016
skimage_solidity                0.958321
t                               0.000000
Length: 148, dtype: float64

Calculate overlap between two single cells

[18]:
sc1.compute_iou(sc2), sc1.compute_overlap_percent(sc2)
[18]:
(0.0, 0.0)

Single-cell tracking:

One of the main challenges in analyzing data is tracking individual cells as they move, grow, and divide. Here, we uses the SORT algorithm for tracking:

[19]:
from typing import List
from livecellx.track.sort_tracker_utils import (
    gen_SORT_detections_input_from_contours,
    update_traj_collection_by_SORT_tracker_detection,
    track_SORT_bbox_from_contours,
    track_SORT_bbox_from_scs
)


traj_collection = track_SORT_bbox_from_scs(single_cells, dic_dataset, mask_dataset=mask_dataset, max_age=1, min_hits=1)
matching image path: ../datasets/EBSS_Starvation/tif_STAV-A549_VIM_24hours_NoTreat_NA_YL_Ti2e_2022-12-21/XY16/STAV-A549_VIM_24hours_NoTreat_NA_YL_Ti2e_2022-12-21_T001_XY16_DIC.tif
matching image path: ../datasets/EBSS_Starvation/tif_STAV-A549_VIM_24hours_NoTreat_NA_YL_Ti2e_2022-12-21/XY16/STAV-A549_VIM_24hours_NoTreat_NA_YL_Ti2e_2022-12-21_T002_XY16_DIC.tif
matching image path: ../datasets/EBSS_Starvation/tif_STAV-A549_VIM_24hours_NoTreat_NA_YL_Ti2e_2022-12-21/XY16/STAV-A549_VIM_24hours_NoTreat_NA_YL_Ti2e_2022-12-21_T003_XY16_DIC.tif
matching image path: ../datasets/EBSS_Starvation/tif_STAV-A549_VIM_24hours_NoTreat_NA_YL_Ti2e_2022-12-21/XY16/STAV-A549_VIM_24hours_NoTreat_NA_YL_Ti2e_2022-12-21_T004_XY16_DIC.tif
matching image path: ../datasets/EBSS_Starvation/tif_STAV-A549_VIM_24hours_NoTreat_NA_YL_Ti2e_2022-12-21/XY16/STAV-A549_VIM_24hours_NoTreat_NA_YL_Ti2e_2022-12-21_T005_XY16_DIC.tif
matching image path: ../datasets/EBSS_Starvation/tif_STAV-A549_VIM_24hours_NoTreat_NA_YL_Ti2e_2022-12-21/XY16/STAV-A549_VIM_24hours_NoTreat_NA_YL_Ti2e_2022-12-21_T006_XY16_DIC.tif
matching image path: ../datasets/EBSS_Starvation/tif_STAV-A549_VIM_24hours_NoTreat_NA_YL_Ti2e_2022-12-21/XY16/STAV-A549_VIM_24hours_NoTreat_NA_YL_Ti2e_2022-12-21_T007_XY16_DIC.tif
matching image path: ../datasets/EBSS_Starvation/tif_STAV-A549_VIM_24hours_NoTreat_NA_YL_Ti2e_2022-12-21/XY16/STAV-A549_VIM_24hours_NoTreat_NA_YL_Ti2e_2022-12-21_T008_XY16_DIC.tif
matching image path: ../datasets/EBSS_Starvation/tif_STAV-A549_VIM_24hours_NoTreat_NA_YL_Ti2e_2022-12-21/XY16/STAV-A549_VIM_24hours_NoTreat_NA_YL_Ti2e_2022-12-21_T009_XY16_DIC.tif
matching image path: ../datasets/EBSS_Starvation/tif_STAV-A549_VIM_24hours_NoTreat_NA_YL_Ti2e_2022-12-21/XY16/STAV-A549_VIM_24hours_NoTreat_NA_YL_Ti2e_2022-12-21_T010_XY16_DIC.tif

Trajectory Length Histogram

[21]:
traj_collection.histogram_traj_length()
[21]:
<Axes: ylabel='Count'>
../../_images/livecellx_notebooks_tutorials_tutorial_application_EBSS_28_1.png

Visualization with Napari:

Napari is a multi-dimensional image viewer for python. It provides an interactive platform to visualize and analyze the data:

[23]:
%gui qt
from livecellx.core.napari_visualizer import NapariVisualizer
import napari
from skimage import data

[24]:
for time in dic_dataset.times:
    assert time in dic_dataset.time2url
    assert dic_dataset.time2url[time] is not None
    # assert dic_dataset.read_img_url_func(dic_dataset.time2url[time]) is not None
[25]:
# def to_dask(self, times=None, ram=False):
#     """convert to a dask array for napari visualization"""
#     import dask.array as da
#     from dask import delayed
#     if times is None:
#         times = self.times
#     if ram:
#         return da.stack([da.from_array(self.time2url[time]) for time in times])

#     lazy_reader = delayed(self.read_img_url_func)
#     lazy_arrays = [lazy_reader(self.time2url[time]) for time in times]
#     dask_arrays = [da.from_delayed(lazy_array, shape=(100, 100), dtype=int) for lazy_array in lazy_arrays]
#     return da.stack(dask_arrays)

# shape = dic_dataset.infer_shape()
# to_dask(dic_dataset)
# dic_dataset.to_dask = to_dask
# mask_dataset.to_dask = to_dask
[26]:
from livecellx.core.single_cell import SingleCellStatic, SingleCellTrajectory, SingleCellTrajectoryCollection
import numpy as np
from napari.viewer import Viewer
from livecellx.core.visualizer import Visualizer

Visualize with napari

[27]:
# viewer = napari.view_image(dic_dataset.to_dask(), name='dic_image', cache=True)
# shape_layer = NapariVisualizer.viz_trajectories(traj_collection, viewer, contour_sample_num=20)

Editing trajectories:

Once trajectories are visualized, users can edit or modify them using the provided tools:

[28]:
from napari.layers import Shapes
from livecellx.core.single_cell import SingleCellTrajectoryCollection
from livecellx.core.sct_operator import SctOperator, create_sct_napari_ui


viewer = napari.view_image(dic_dataset.to_dask(), name="dic_image", cache=True)
shape_layer = NapariVisualizer.viz_trajectories(traj_collection, viewer, contour_sample_num=20)
sct_operator = SctOperator(traj_collection, shape_layer, viewer)
sct_operator.setup_shape_layer(shape_layer, viewer=viewer)

create_sct_napari_ui(sct_operator)
[29]:
from livecellx.preprocess.utils import normalize_img_to_uint8

img = normalize_img_to_uint8(dic_dataset.get_img_by_time(2))
import PIL
# save img
PIL.Image.fromarray(img).save("img.png")
[30]:
# sct_operator.update_shape_layer_by_track_id(6, face_color="blue", new_track_id=6)
[31]:
# sct_operator.connect_two_scts()
# sct_operator.disconnect_sct()
[32]:
# sct_operator.clear_selection()
# sct_operator.connect_two_scts()
# sct_operator.add_mother_daughter_relation()
[33]:
event = object()
sct_operator.select_shape(event)
current shape layer shape properties:  <object object at 0x0000019CED8E6650>
No shape selected, please select a shape to connect trajectories
[35]:
sct_operator.select_info
[35]:
[]
[36]:
sct_operator.magicgui_container[2].hide()
[ ]:
# from qtpy.QtWidgets import QPushButton
# connect_btn = QPushButton('Connect two trajectories')
# connect_btn.resize(100, 100)
# connect_btn.clicked.connect(sct_operator.connect_two_scts)
# widget = viewer.window.add_dock_widget(connect_btn, name="edit trajectory")

# clear_btn = QPushButton('Clear selection')
# clear_btn.resize(100, 100)
# clear_btn.clicked.connect(sct_operator.clear_selection)
# viewer.window.add_dock_widget(clear_btn, name="edit trajectory")
[ ]:
shape = shape_layer.data[0]
[ ]:
# viewer.layers.selection.events.active.connect(lambda x: print(dir(x)))