Fig. 1
Workflow comparison of probabilistic interactive segmentation and mask-based automatic quantification for mitochondrial morphology analysis with manual segmentation and quantification approach. The diagram presents two approaches for segmenting and quantifying mitochondria. The Probabilistic Interactive Segmentation method (left) integrates user feedback to generate multiple segmentation hypotheses, identifying regions of uncertainty that require further refinement. Based on this analysis, the system suggests areas for user input to refine the segmentation. The user can respond to these suggestions with positive or negative feedback, or alternatively, provide input independently. The Mask-based Automatic quantification method (bottom) performs contour detection on masks using a connected component-based approach, followed by morphological quantification of each contour through minimum bounding rectangles derived from the rotating calipers algorithm. In contrast, the Manual Segmentation and Quantification method (right) involves segmentation in Photoshop and quantification in ImageJ, demanding significant manual effort and time.
