Algorithms for MR and OCT-based Architectonic and Laminar Segmentation

 描述（由申请人提供）：人脑由一系列功能和结构上定义的区域组成。定位这些区域对于阿尔茨海默病（AD）等一系列疾病的早期诊断以及旨在了解大脑功能和结构特性的神经科学研究以及耐药性抑郁症的临床干预至关重要。不幸的是，直接可视化的层状属性，是一个定义的特点，皮层区是超越目前 成像技术，除了在特殊情况下，代表整个皮层的一小部分。在这个项目中，我们建议开发工具，用于分割皮质区和层流边界，使用超高分辨率的离体MRI和光学相干断层扫描（OCT），然后通过概率建模在体内推断。这将使我们能够开发和分发允许自动区域和层流定位的工具， 临床和神经科学研究。拟议的分析流持有的承诺，自动获得新的层状和区域特定的形态测量，在我们的目标检测神经退行性疾病的早期在他们的过程中，当治疗干预仍然是可能的，以及指导疾病的治疗和分期患有抑郁症或多发性硬化症等疾病的个体患者的关键进展。

 DESCRIPTION (provided by applicant): The human brain is made up of an array of functionally and structurally defined regions. Localizing these regions is critical for early diagnosis of an array of diseases such as Alzheimer's disease (AD), as well as for neuroscientific research aimed at understanding the brain's functional and structural properties and clinical intervention in drug-resistant depression. Unfortunately, direct visualization of the laminar properties that are one of the defining characteristics of cortical areas is beyond current imaging technology, except in specialized cases that represent a small fraction of the entire cortex. In this project we propose to develop tools for segmenting cortical areas and laminar boundaries using ultra-high resolution ex vivo MRI and optical coherence tomography (OCT), then to make in vivo inferences via probabilistic modeling. This will allow us to develop and distribute tools that should permit automated areal and laminar localization, facilitating an array of clinical and neuroscientific research. The proposed analysis stream holds the promise of automatically deriving new laminar and area-specific morphometric measures, a critical advance in our goal of detecting neurodegenerative disorders early in their course, when therapeutic intervention is still possible, as well as for guiding disease treatment and staging in individual patients suffering from diseases such as depression or multiple sclerosis.