designed by Ryan Wang from Dr. Ke Yuan lab in Boston Children's Hospital
This application uses AI (YOLO) to detect and analyze cells in microscopy images. To ensure the app works correctly, your files must follow the naming conventions described below.
The app identifies the imaging channel based on the filename. You must use a separator (underscore _, dash -, or space) before the channel indicator.
Channel Format: Use ch# or ch## where # is a digit (0-9).
Sample1_ch0.tif, Sample1_ch00.tif, Experiment-A_ch1.jpg, Cell ch02.pngSample1ch00.tif (Missing separator before 'ch'), ch0image.tif (channel at start)Grouping: Files with the same prefix (base name) are grouped together as one sample.
Example: S1_ch0.tif and S1_ch1.tif are processed together, or S1_ch00.tif and S1_ch01.tif.
ch00, ch01, ch02, ch03_ch00: Smooth muscle_ch01: Pericyte_ch02: Fibrolast C_ch03: DAPI (Nuclei)ch00, ch01_ch00: Pericyte_ch01: Nuclei/DAPIdapi (case-insensitive), it is automatically treated as Channel 1.Smart Detection: If you upload human cell images with only channels 0, 1, and 2 (missing channel 3), the app will automatically remap them:
ch0 → becomes ch1ch1 → becomes ch2ch2 → becomes ch3 (DAPI)This ensures your images are processed with the correct models even if you named them starting from 0.
.tif, .tiff, .jpg, .jpeg, .png, .bmp.processed.zip file will be generated containing: