qcqatools module ================ .. automodule:: clabtoolkit.qcqatools :members: :undoc-members: :show-inheritance: The qcqatools module provides comprehensive quality control and quality assessment tools for neuroimaging data, enabling automated validation and visual inspection workflows. Key Features ------------ - Automated quality control metrics computation - Image artifact detection and reporting - Optimal slice selection for visual inspection - Multi-modal data validation - Quality report generation - Visual assessment tools Main Functions -------------- Quality Assessment ~~~~~~~~~~~~~~~~~~ - ``get_valid_slices()``: Identify optimal slice positions for visualization - ``generate_slices()``: Generate image slices for quality control - ``recursively_generate_slices()``: Recursively generate slices for multiple files - ``generate_image_selection_webpage()``: Generate webpage for image selection - ``create_png_webpage_from_generated_slices()``: Create PNG webpage from generated slices Common Usage Examples --------------------- Automated slice selection:: from clabtoolkit.qcqatools import get_valid_slices # Find optimal slices for quality control visualization optimal_slices = get_valid_slices( image_file="/path/to/T1w.nii.gz", n_slices=5, plane='axial' ) print(f"Recommended slices: {optimal_slices}") Generate quality control slices:: # Generate slices for quality control generate_slices( image_file="/path/to/T1w.nii.gz", output_dir="/path/to/qc_slices", n_slices=5, plane='axial' ) Create QC webpage:: # Generate interactive QC webpage generate_image_selection_webpage( image_dir="/path/to/qc_slices", output_html="/path/to/qc_report.html", title="Quality Control Report" ) # Process multiple files recursively recursively_generate_slices( input_dir="/path/to/bids/dataset", output_dir="/path/to/qc_output", file_pattern="*T1w.nii.gz" )