Pulmonary Circulation Vessels Dataset for pathology аssessment using Machine Learning-based Image Segmentation

Pulmonary hypertension (PH) is a symptom complex that accompanies a number of diseases of different etiologies, associated with basic mechanisms of structural and functional changes of the pulmonary circulation vessels and revealed pressure increasing in the pulmonary artery. The structural changes in the pulmonary circulation vessels are the main limiting factor determining the prognosis of patients with PH. Thickening and irreversible deposition of collagen in the pulmonary artery branches walls leads to rapid disease progression and a therapy effectiveness decreasing. In this regard, histological examination of the pulmonary circulation vessels is critical both in preclinical studies and clinical practice. However, measurements of quantitative parameters such as the average vessel outer diameter, the vessel walls area, and the hypertrophy index claimed significant time investment and the requirement for specialist training to analyze micrographs.

肺动脉高压（Pulmonary Hypertension, PH）是一类伴随多种不同病因疾病的症候群，其病理生理基础为肺循环血管的结构与功能改变，临床表现为肺动脉压力升高。肺循环血管的结构改变是决定肺动脉高压患者预后的主要限制因素。肺动脉分支管壁的胶原增厚与不可逆沉积，可导致疾病快速进展，并降低治疗有效性。鉴于此，肺循环血管的组织学检查在临床前研究与临床实践中均至关重要。然而，诸如血管平均外径、管壁面积以及肥厚指数等量化参数的测量，不仅需要耗费大量时间，还要求专业人员接受相关训练以分析显微图像。