🤖 AI Summary
Medical image registration across heterogeneous imaging devices suffers from fragmented and nontraceable transformation information, impeding clinical diagnosis and collaborative workflows. To address this, we propose a tree-structured documentation framework for multimodal image registration, unifying coordinate transformations—spanning diverse devices and modalities—within a patient-specific reference frame. We introduce the .dpw (Digital Patient Workspace) proprietary file format, enabling hierarchical storage, reversible provenance tracking, and cross-platform reproducibility of transformation chains. Furthermore, we develop dpVision, a software tool supporting interactive visualization, validation, and management of registration workflows. Evaluated in orthodontic analysis, our approach significantly enhances interpretability, reproducibility, and clinical audit efficiency of complex registration pipelines. The method provides a standardized, interoperable foundation for multicenter medical imaging collaboration.
📝 Abstract
The paper presents proposals for the application of a tree structure to the documentation of a set of transformations obtained as a result of various registrations of multimodal images obtained in coordinate systems associated with acquisition devices and being registered in one patient-specific coordinate system. A special file format .dpw (digital patient workspace) is introduced. Examples of different registrations yielded from orthodontic analysis and showing main aspects of the usage of tree structure are illustrated in dpVision software.