光学相干层析成像（OCT）可对人体组织实现三维无损成像，是眼球和软组织疾病诊断的重要手段之一。本项目将深入研究三维OCT图像的高维特性和多种内在结构性，提出面向OCT成像的三维结构化压缩感知方法。研究内容包括：1)利用层析内结构分布不均衡性和层析间结构相似性，提出三维结构自适应压缩采样方法，降低采集数据冗余度并提高成像速度；2)针对眼球和软组织病理结构的高维性和高复杂性，提出三维多结构字典构建方法，精确表示和重构病理结构；3)利用层析内结构相似性和稀疏系数结构性，提出三维结构化稀疏重构算法，提高重构精度和效率。研究成果将有助于解决现有OCT技术采集冗余度高、成像速度慢、复杂结构信息难以有效表示和重构等问题，促进压缩感知理论和OCT成像技术的发展，为眼球和软组织疾病高效、精确的诊断提供技术支撑。

Optical coherence tomography (OCT) can achieve the 3D tomography imaging of the human tissue in a non-invasive way, which is an important tool for the diagnosis of the diseases in the eye and soft tissue. This project will thoroughly study the high-dimensionality and several structural characteristics of the 3D OCT image, and propose a 3D structural compressive sensing (CS) method for the OCT imaging. The main content includes the following parts: 1) by considering the imbalanced distribution of structures within slices and high similarity for structures among slices, propose a 3D structural adaptive compressive sampling, reducing the redundancy in the acquired data and improving the imaging speed; 2) for the high-dimensionality and high-complexity of pathologic structures in the eye and soft tissue, propose a 3D multiple structural dictionary construction method, accurately representing and reconstructing the pathologic structures; 3) by exploiting the high similarity for structures within slices and the structure in sparse coefficients, propose a 3D structural sparse reconstruction method, enhancing the effectiveness and efficiency of the reconstruction. Our research will address several key problems (such as high redundancy in the acquired data, low imaging speed, low effectiveness for the representation and reconstruction of complex structures) in the current OCT technology, and promote the developments of both the CS theory and OCT imaging technique, providing a technical support for the high-efficient and accurate diagnosis of diseases in eye and soft tissue.