Stroke is a leading cause of disability and death. Effective treatment
decisions require early and informative vascular imaging. 4D perfusion imaging
is ideal but rarely available within the first hour after stroke, whereas plain
CT and CTA usually are. Hence, we propose a framework to extract a predicted
perfusion map (PPM) derived from CT and CTA images. In all eighteen patients,
we found significantly high spatial similarity (with average Spearman's
correlation = 0.7893) between our predicted perfusion map (PPM) and the T-max
map derived from 4D-CTP. Voxelwise correlations between the PPM and National
Institutes of Health Stroke Scale (NIHSS) subscores for L/R hand motor, gaze,
and language on a large cohort of 2,110 subjects reliably mapped symptoms to
expected infarct locations. Therefore our PPM could serve as an alternative for
4D perfusion imaging, if the latter is unavailable, to investigate blood
perfusion in the first hours after hospital admission.

中风是致残和死亡的主要原因。在有效处理决策中首要是进行早期和信息丰富的血管成像。因此，我们提出了一种从 CT 和 CTA 图像中提取预测灌注图的框架。我们的预测灌注图与 4D-CTP 得到的 T-max 灌注图之间具有显著的空间相似性。通过对 2,110 名患者进行的体素相关性分析，可可靠地将症状与预期的梗塞位置相对应。因此，如果没有 4D 灌注成像，我们的预测灌注图可以作为一种替代方法来研究入院后的前几个小时的血液灌注。

急性缺血性卒中患者 CT 和 CTA 图像生成灌注图的框架：纵向和横向研究

Framework to generate perfusion map from CT and CTA images in patients  with acute ischemic stroke: A longitudinal and cross-sectional study

Segmentation of tubular structures in vascular imaging is a well studied
task, although it is rare that we try to infuse knowledge of the tree-like
structure of the regions to be detected. Our work focuses on detecting the
important landmarks in the vascular network (via CNN performing both
localization and classification of the points of interest) and representing
vessels as the edges in some minimal distance tree graph. We leverage geodesic
methods relevant to the detection of vessels and their geometry, making use of
the space of positions and orientations so that 2D vessels can be accurately
represented as trees. We build our model to carry tracking on Ultrasound
Localization Microscopy (ULM) data, proposing to build a good cost function for
tracking on this type of data. We also test our framework on synthetic and eye
fundus data. Results show that scarcity of well annotated ULM data is an
obstacle to localization of vascular landmarks but the Orientation Score built
from ULM data yields good geodesics for tracking blood vessels.

通过使用卷积神经网络对感兴趣的点进行定位和分类，并将血管表示为一些最小距离树状图的边，基于地形测量方法检测血管及其几何特征，我们的研究聚焦于在血管网络中检测重要的地标，并利用位置和方向的空间，准确地将 2D 血管表示为树状结构。我们构建了适用于超声定位显微镜（ULM）数据跟踪的模型，提出在这种类型数据上构建良好的成本函数用于跟踪。我们还对合成数据和眼底图像数据进行了测试。结果表明，缺乏良好注释的 ULM 数据是血管地标定位的障碍，但基于 ULM 数据建立的方向得分对于追踪血管具有良好的测地线效果。

利用 CNN 和测地线拟合树模型以跟踪血管并应用于超声定位显微镜数据

Fitting tree model with CNN and geodesics to track vesselsand  application to Ultrasound Localization Microscopy data

Circulatory system abnormalities might be an indicator of diseases or tissue
damage. Early detection of vascular abnormalities might have an important role
during treatment and also raise the patient's awarenes. Current detection
methods for vascular imaging are high-cost, invasive, and mostly
radiation-based. In this study, a low-cost and portable microcomputer-based
tool has been developed as a near-infrared (NIR) superficial vascular imaging
device. The device uses NIR light-emitting diode (LED) light at 850 nm along
with other electronic and optical components. It operates as a non-contact and
safe infrared (IR) imaging method in real-time. Image and video analysis are
carried out using OpenCV (Open-Source Computer Vision), a library of
programming functions mainly used in computer vision. Various tests were
carried out to optimize the imaging system and set up a suitable external
environment. To test the performance of the device, the images taken from three
diabetic volunteers, who are expected to have abnormalities in the vascular
structure due to the possibility of deformation caused by high glucose levels
in the blood, were compared with the images taken from two non-diabetic
volunteers. As a result, tortuosity was observed successfully in the
superficial vascular structures, where the results need to be interpreted by
the medical experts in the field to understand the underlying reasons. Although
this study is an engineering study and does not have an intention to diagnose
any diseases, the developed system here might assist healthcare personnel in
early diagnosis and treatment follow-up for vascular structures and may enable
further opportunities.

本研究开发了一种使用近红外线（NIR）的便携式显微镜面部血管成像设备，并使用 OpenCV 进行图像和视频分析，通过对糖尿病志愿者和非糖尿病志愿者的成像对比中成功观察到其表面血管结构的缠曲程度，为医疗保健人员提供了早期诊断和治疗跟踪的可能性。