This startup develops medical image analysis software that uses network analysis to detect abnormalities in vascular, respiratory, and nervous systems. The software identifies structural and connectivity changes in medical images, enabling healthcare professionals to diagnose conditions like aneurysms and malformations more efficiently.
Funding
Funding not disclosed
Founders
Product
Problem
Diagnosing vascular, respiratory, and nervous system diseases often requires manual analysis of medical images, which can be time-consuming and prone to human error. Detecting subtle structural and connectivity changes indicative of conditions like aneurysms, stenosis, or pulmonary embolism can be particularly challenging.
Solution
Vasomaly provides medical image analysis software that leverages supervised deep learning algorithms to automatically segment vascular trees and detect anomalies. Trained on a large dataset, the software identifies a range of pathologies, including aneurysms, stenosis, thrombosis, arteriovenous malformations, and pulmonary embolism. By automating segmentation and anomaly detection, Vasomaly aims to improve the efficiency and accuracy of diagnoses, enabling healthcare professionals to optimize their workflow and enhance patient care. The software provides clinicians with precise and reliable medical insights derived from advanced vascular imaging analysis.
Target Audience
The primary users are healthcare professionals, including clinicians and radiologists, who specialize in diagnosing and treating vascular, respiratory, and nervous system diseases.
Features
- Automatic segmentation of vasculature and pulmonary airways using supervised deep learning algorithms.
- Detection of anomalies such as aneurysms, stenosis, thrombosis, arteriovenous malformations, and pulmonary embolism.
- Algorithms trained on a large dataset of vascular images.
- Solutions for the segmentation and analysis of the vascular and nervous systems.