What are some typical challenges faced when integrating machine learning into microscopy workflows?

Integrating machine learning into microscopy workflows often involves challenges such as handling large, complex datasets, ensuring high-quality data labeling, and adapting models to diverse sample types. Collaboration between data scientists, biologists, and imaging specialists is essential to overcome these hurdles and optimize model performance. Additionally, maintaining reproducibility and transparency in analysis pipelines is crucial for scientific rigor and regulatory compliance.