AI 足部模型：基於 Transformer 和點雲技術的三維足骨建模

Abstract

足踝複合體作為身體的重要支點，在承載體重的同時需要保持足夠的靈活性以適應各種地形。足部結構的錯位以及腳和踝部的受傷或疾病可能導致功能障礙。瞭解足部表面形態變化與內部力學之間的關係，可以提升臨床診斷的準確性和治療的效率。然而，由於現有測量技術的限制，我們尚缺乏非侵入性和無放射性的骨骼測量手段，並且無法取得動態的骨骼資訊，骨骼排列對足底表面形態的影響也仍不明確。此外，現有的足部模型理論大多基於研究人員的主觀判斷，缺乏足夠的實驗論證，且使用外部儀器測量會導致結果不精準，在臨床使用上有所限制。因此，本研究提出了一種創新的兩階段 AI 足部模型框架，結合 3D 點雲建模技術和基於深度學習及注意力機制的 Transformer 模型，可以有效利用足部皮膚生成足部骨骼結構。這種框架為 3D 足部建模提供了一種更快速、更病患友好的方法，填補了非侵入性、無放射性的骨骼測量技術缺口，並解決了現有足部模型在臨床應用上的困難。我們期望此 AI 足部模型能成為治療複雜足踝疾病的重要技術貢獻，增強對足踝複雜機制的理解和治療能力。不僅讓醫生更容易進行診斷，也能減少患者的負擔，並為足部醫療研究提供助力。

The foot and ankle complex serves as a crucial support point for the body, balancing the need to bear weight while maintaining sufficient flexibility to adapt to various terrains. Misalignments in the foot structure, as well as injuries or diseases of the foot and ankle, can lead to functional impairments. Understanding the relationship between foot surface morphology and internal mechanics can enhance clinical diagnostic accuracy and treatment efficiency. However, current measurement technologies lack non-invasive and non-radiative methods for bone measurement, and dynamic bone information cannot be obtained. The impact of bone alignment on the plantar surface morphology also remains unclear. Additionally, existing foot model theories are mostly based on researchers' subjective judgments, lacking sufficient experimental validation, and the use of external instruments for measurement often results in inaccuracies, limiting their clinical applicability. To address these challenges, this study proposes an innovative two-stage AI foot model framework that combines 3D point cloud modeling techniques with Transformer models based on deep learning and attention mechanisms. This framework effectively uses foot skin data to generate foot bone structures. It offers a faster, more patient-friendly method for 3D foot modeling, filling the gap in non-invasive, non-radiative bone measurement technologies, and addressing the difficulties in clinical applications of existing foot models. We anticipate that this AI foot model will become a significant technological contribution to treating complex foot and ankle conditions, enhancing our understanding and treatment capabilities for the intricate mechanisms of the foot and ankle. It will not only make diagnosis easier for doctors but also reduce the burden on patients and support foot and ankle medical research.