📚 What's New Complete documentation coverage with new Batch Label Inspection guide and fixes for broken README links. ✨ Improvements New Documentation ✅ Added comprehensive Batch Label Inspection guide covering: Interactive label verification and editing workflow File matching logic and format validation Tips for efficient batch label quality control Real-world use cases (QC, boundary refinement, removing false positives) Troubleshooting guide for common issues Documentation Fixes ✅ Fixed broken README link for SAM2 Crop Anything (now points to correct crop_anything.md) ✅ Added Batch Label Inspection to Advanced Features section with proper documentation link ✅ Improved README organization and link accuracy 📖 Documentation Coverage napari-tmidas now has complete documentation for all major features: File Processing File Conversion - Multi-format microscopy conversion Batch Processing - Label operations and filters Interactive Tools Batch Crop Anything - AI-powered object segmentation with SAM2 Batch Label Inspection - Manual label verification and editing Deep Learning Features Cellpose Segmentation Trackastra Tracking CAREamics Denoising Spotiflow Detection VisCy Virtual Staining Analysis RegionProps Analysis Intensity Label Filtering Advanced Processing 🎯 User Experience Improvements All documentation now consistent with: Simplified installation instructions (single napari-tmidas[deep-learning] command) Clear workflow examples and use cases Comprehensive troubleshooting sections Performance tips and best practices 📦 Installation # Install napari first mamba create -y -n napari-tmidas -c conda-forge python=3.11 mamba activate napari-tmidas python -m pip install "napari[all]" # Install napari-tmidas with all features pip install 'napari-tmidas[deep-learning]'