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Dataset · Figshare · August 13, 2026

Microscopy Image Dataset of pulmonary vessels for Deep Learning-Based Quantitative assessment of fibrosis

Andrei A. Karpov, Aleksandr Sinitca, Nadezda Isakova, Anna S. Dushkova, Ekaterina Semenova, Vladislava Karpenko

Abstract

Structural remodelling of the vascular wall is a universal response to chronic damage, pressure overload or flow overload. Therefore, this process occurs in a wide range of diseases affecting both the systemic and pulmonary circulations. Vascular wall fibrosis is one of the most important factors in the pathogenesis of various types of pulmonary hypertension. In this regard quantitative assessment of collagen deposition in the vascular wall has significant role in both for preclinical studies and directly affects the life prognosis for patients with pulmonary hypertension. Histological analysis is the gold standard for assessing vascular structural remodeling. This dataset includes 705 micrographs of vascular wall region with varying degrees of vascular wall fibrosis that developed against of various types of pulmonary hypertension. All included studies were devoted to the investigation of pulmonary arterial hypertension and chronic thromboembolic pulmonary hypertension in male Wistar rats. Lung sections were stained with Picro-Mallory and digitized using an whole-slide scanner. Pulmonary artery branches were subdivided into vessel segments, and exported as fixed-size micrographs. For each micrograph, the dataset provides a region-of-interest mask and two independent expert annotations, including binary masks of the vascular wall and intramural fibrosis zones. The presented database will be useful for the development of new software solutions for the analysis of histological micrograph. SHA256: afaf08242a4d57e8d48344efa8512ffcefcd1dd2994cb9ef338dc41cd3e3fba4

Pulmonary Hypertension Research and TreatmentsAI in cancer detectionCell Image Analysis Techniquespulmonary hypertensionpulmonary arterial hypertensionchronic thromboembolic pulmonary hypertension

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