The startup develops AI-driven diagnostic technologies for X-ray analysis, focusing on the detection of abnormalities, spine curvatures, dislocations, and fractures. By providing detailed assessments of X-ray images, the technology enhances radiologists' ability to interpret complex cases accurately and efficiently.
Funding
$280K raised to dateRaised to date based on public sources. This may differ from the amount the company actually raised and is based only on what is publicly available on the internet.
Founders
Product
Problem
Radiologists face challenges in efficiently and accurately interpreting X-ray images, particularly in detecting subtle abnormalities, spinal curvatures, dislocations, and fractures. Manual analysis can be time-consuming and prone to human error, potentially leading to delayed or inaccurate diagnoses.
Solution
Oxytech provides AI-powered diagnostic tools for the automated analysis of X-ray images, enabling faster and more accurate detection of a range of conditions. The platform utilizes deep learning models trained on a large dataset of X-ray studies to identify abnormalities in chest, spine, sinuses, knees, and pelvis images. By automating the detection process and providing quantitative measurements, Oxytech aims to improve diagnostic accuracy, reduce reporting times, and enhance clinical decision-making. The solution is available through a web interface, API, and integration with PACS and DICOM storage systems.
Target Audience
The primary target audience includes radiologists, medical institutions, and healthcare providers seeking to improve the efficiency and accuracy of X-ray image analysis.
Features
- AI-driven analysis of chest X-rays for detecting multiple lung abnormalities in under 1 minute
- Automated detection and measurement of spine curvatures and bone abnormalities in spine X-rays in under 30 seconds
- AI-powered analysis of skull X-rays for sinusitis detection and sinus fullness percentage in under 30 seconds
- Algorithms for analyzing knee and pelvis X-rays to assess degenerative processes in under 1 minute
- API for integration into existing systems
- Web-based access with a built-in DICOM viewer
- Integration capabilities with PACS and DICOM storage systems
- Option for an out-of-the-box solution that does not require a cloud connection