Medical Imaging Label Alignment Correction Software

Development BackgroundIn medical image segmentation research based on frameworks such as nnU Net, errors in model evaluation (such as operations could not be broadcast together) are often caused by inconsistencies in physical spatial parameters (such as spacing, origin) or voxel shape between the image and annotation files. Although libraries such as SimpleITK support manual alignment, they require users to have programming skills, and the operation is cumbersome and prone to errors. At present, there is a lack of a lightweight tool for image label consistency verification and repair that is programming free, graphical, and specifically designed for ordinary users. To this end, we have developed this software that encapsulates professional alignment logic into independent executable programs, providing a safe operating experience of "check first, calibrate later", significantly reducing the threshold for use. Software functions and features1) Zero environment dependency: No need to install Python or any third-party libraries, just unzip and use; 2) Dual mode operation: a) Check mode: diagnose security issues without modifying any files; b) Correction mode: One click repair and overwrite the original label (with secondary confirmation); 3) Detailed diagnostic report: List the spacing, origin, and shape differences of mismatched files item by item for easy problem tracing; 4) Intelligent interaction: After detecting problems, the interface automatically displays the "Quick Correction" button to improve operational efficiency; 5) Safety priority: Forcefully pop up backup reminders before calibration to prevent data loss caused by misoperation; 6) Graphic interface: Designed with a dark theme, the operation is simple and intuitive, making it easy for non-technical users to get started.