Coupled level set framework for retinal segmentation and atlasing in SD-OCT

描述（由申请人提供）：一些眼部疾病表现出视网膜异常或萎缩，这可能会损害视力并导致失明。传统上认为与大脑完全相关的某些其他疾病现在已知与视网膜的变化或差异有关，这也会损害视力。光学相干断层扫描（OCT）是一种能够对视网膜进行现代体内高分辨率研究的成像设备，它正在迅速成为眼科学和神经学的关键成像技术，在眼科学中，临床诊断和疾病监测正在经历一场巨大的技术革命，在神经学中，脑疾病的非侵入性视网膜标记物开始出现。当前技术的一个关键限制是缺乏对在典型的三维谱域（SD）-OCT检查中观察到的整个视网膜的视网膜层的详细、准确和全自动分析。虽然工具开始与商业设备相关联地出现，但它们目前缺乏复杂性，并且没有在制造商之间进行验证或标准化。这种缺陷对于SD-OCT的临床和科学应用都是有问题的，因为测量不具有已知的精度，因此在同一受试者中纵向和群体横截面中不易比较。拟议的研究利用了计算机视觉和医学成像中出现的最先进的算法，并将其应用，调整和扩展到三维视网膜SD-OCT中的层分割的具体应用。还将专门针对视网膜SD-OCT数据开发用于在归一化空间中进行群体平均的高级工具。该方法将针对正常受试者和经历视网膜变性的患者两者的手动分割和归一化进行验证，所述视网膜变性主要与视网膜的选择性层变薄相关。将对患有引起显著视网膜病变（如囊肿、脱离或瘢痕）的疾病的患者进行扫描，但预计需要在目前研究之外进行进一步开发，以正确分割和量化此类病例。开发的软件将在开源Java Image Science Toolkit（JIST）框架内开发，并作为开源软件发布。 公共卫生相关性：该项目将开发视网膜光学相干断层扫描（OCT）图像分析软件。视网膜内的神经层的特征的分割和量化预期在眼科学和神经学上都有很大的用途，其中视网膜可以是视觉和神经问题或疾病的敏感指标。以高度可移植语言编写的开放源码软件将在研究资助结束时提供给研究界。

DESCRIPTION (provided by applicant): Some eye diseases exhibit abnormalities or atrophy of the retina, which can impair vision and cause blindness. Certain other diseases traditionally thought to be exclusively associated with the brain are now known to be associated with changes or differences in the retina, which can also impair vision. Optical coherence tomography (OCT), an imaging device that is enabling modern in-vivo high-resolution studies of the retina, is rapidly becoming a key imaging technology both in ophthalmology, where clinical diagnoses and disease monitoring are experiencing a dramatic technical revolution, and also in neurology, where noninvasive retinal markers of brain disease are beginning to emerge. A key limitation in the current technology is the lack of detailed, accurate, and fully-automated analysis of the retinal layers that are observed throughout the retina in a typical three-dimensional spectral domain (SD)-OCT exam. Although tools are beginning to appear in association with commercial devices, they are currently lacking in sophistication and are not validated or standardized across manufacturers. This deficiency is problematic for both clinical and scientific application of SD-OCT since the measurements are not of known precision and are therefore not easily compared both in the same subject longitudinally and in population cross sections. The proposed research takes advantage of state-of-the-art algorithms that are emerging in both computer vision and medical imaging and will apply, adapt, and extend them to the specific application of layer segmentation in three-dimensional retinal SD-OCT. Advanced tools for population averaging in a normalized space will also be developed specifically for retinal SD-OCT data. The methods will be validated against manual segmentation and normalization on both normal subjects and patients experiencing retinal degeneration largely associated with thinning of selective layers of the retina. Scans of patients with diseases causing significant retinopathy such as cysts, detachment, or scarring will be evaluated, but further development beyond the present research is expected to be needed to properly segment and quantify such cases. The developed software will be developed within the open-source Java Image Science Toolkit (JIST) framework and released as open source software. PUBLIC HEALTH RELEVANCE: The project will develop software for the image analysis of optical coherence tomography (OCT) scans of the retina. Segmentation and quantification of the characteristics of nerve layers within the retina is expected to be of great use on both ophthalmology and neurology, where the retina can be a sensitive indicator of both vision and neurological problems or diseases. Open source software written in a highly portable language will be made available to the research community at the conclusion of the research grant.