BACKGROUND: Immunohistochemistry (IHC) is a widely used method for localizing and semi-quantifying proteins in tissue samples. Traditional IHC analysis often relies on manually counting 200 cells within a designated area, a time-intensive and subjective process that can compromise reproducibility and accuracy. Advances in digital scanning and bioimage analysis tools, such as the open-source software QuPath, enable semi-automated cell counting, reducing subjectivity and increasing efficiency. AIMS: This project developed a QuPath-based script and detailed guide for semi-automatic cell counting, specifically for tissues with low cellularity, such as intervertebral discs and cartilage. METHODS AND RESULTS: The methodology was validated by demonstrating no significant differences between the manual counting and the semi-automatic quantification ( DISCUSSSION: The approach ensures high reproducibility and accuracy, with reduced variability between raters and laboratories. This semi-automated method is particularly suited for tissues with a high extracellular matrix to cell ratio and low cellularity. By minimizing subjectivity and evaluation time, it provides a robust alternative to manual counting, making it ideal for applications where reproducibility and standardization are critical. While the methodology was effective in low-cellularity tissues, its application in other tissue types warrants further exploration. CONCLUSIONS: These findings underscore the potential of QuPath to streamline IHC analysis and enhance inter-laboratory comparability.