Big data-based system and method for the management of limb volume measurement data in lymphedema

Abstract

The invention discloses a big data-based system and method for the management of limb volume measurement data in lymphedema, specifically relating to the technical field of measurement data management. By constructing a multimodal volume raw dataset and analyzing the differences in spatial sampling and volume calculation models across different measurement modalities, modality bias characteristic parameters representing measurement physical hypothesis differences are extracted, and inter-modality volume offset description relationships are established to achieve quantitative characterization of cross-modality volume offset. The volume offset description relationships are jointly analyzed with the patient's historical follow-up volume variation data, enabling automatic identification of systematic volume offset segments caused by measurement modality switching without manual intervention, and differentiation and labeling from true limb swelling variation segments. This effectively avoids confusion between measurement errors and disease progression, establishes a unified volume reference index, and constructs cross-modality volume mapping and traceable management relationships.