Extended Data Fig. 1: Scheme of preprocessing, segmentation processes and final results with features extracted.

The pipeline starts from (1) optional preprocessing, for example, histogram matching to correct intensity loss due to depth penetration. The preprocessed data is then resized to match the voxel size of 3D StarDist training data. (2) Nuclei are segmented with an AI Stardist pre-trained network (4 different CNNs available). (3) Organoid segmentation was performed using one of the channels or the channels mean, it consists of steps as follows: Enhance Local Contrast (CLAHE), Gaussian blur, Otsu threshold, Morphological operations, Keep largest object. (4) The segmented organoid mask is used for cleaning, that is, debris with centroids outside the organoid are removed and organoid/spheroid borders are dilated to secure the inclusion of all nuclei and cytoplasmic signals. (5) Cell segmentation was performed using seeded watershed based on nuclei segmentation and cell channel (nuclei are considered as seeds). The expansion of the cell watershed is limited to the organoid volume. The distance between a nucleus border and the corresponding cell border is constraint to a maximum value (i.e 14 µm). The label mask of cells is filtered with a 3D median filter.