Cardiac Ultrasound App
Highlights
- Real-time video streaming
- Data export and storage in the DICOM medical format
- Connection with the ultrasound device via BLE
- Compliance with FDA submission requirements
Challenge
The US-based client approached SoftTeco with a goal: build a mobile app that would help intensive care physicians make faster and more accurate decisions. Existing ultrasound analysis methods were available, but they lacked the speed, precision, and real-time data required in critical settings. The client wanted a solution capable of analyzing ultrasound images, extracting key metrics such as volume responsiveness, chamber function, and heart contractility, and providing instant insights to improve patient outcomes.
The application had to connect to ultrasound probes and process data on mobile devices. Since no ready-made algorithms or integrated software existed, the client needed a team with proven expertise in healthcare software development and algorithm engineering to build the product entirely from scratch. In addition, one of the client’s requests was to prepare the software solution for FDA certification.
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Solution
SoftTeco’s team developed an Android application, including backend, frontend, and architecture design. A key part of the solution was the machine learning model and algorithm that our engineers created to process ultrasound images. Since no ready-made libraries or models existed for this task, the algorithm was created and tied to the specifics of cardiac ultrasound. It leverages TensorFlow models for deep learning-based image analysis, including image segmentation and feature extraction. These models detect heart structures and calculate critical parameters needed for intensive care, ensuring high accuracy and reliability.
Data management was also a crucial part of the solution. The application allows physicians to store ultrasound data in the DICOM format, which ensures compatibility with medical imaging systems and compliance with healthcare standards.
Tech Stack
How it works
The process begins when the user installs the Clarius App on their Android device and connects it to a Clarius ultrasound scanner (US-scanner) via the app. Once connected, the Clarius SDK takes over, linking the Android device to the Clarius App. It retrieves real-time data from the US-scanner and allows full control of the device. Using a bound service, the SDK communicates directly with the app, enabling the app to both receive a live video feed from the scanner and send commands to adjust the scanner’s settings and parameters. This seamless integration between the Clarius App, SDK, and US-scanner ensures a smooth and efficient workflow for medical professionals. Beyond simple playback, the solution integrates intelligent processing. The application extracts individual frames from the live video stream and runs them through custom-built algorithms built on TensorFlow and OpenCV. This enables image segmentation, filtering, and feature detection to calculate critical health parameters, including how the body responds to fluids, how effectively the heart chambers function, and how strongly the heart pumps blood.
We also introduced file import and export modules, along with synchronization with a remote server when needed. Our developers ported the DCMTK library to support the DICOM format, allowing physicians to store, import, export, and synchronize data securely with remote servers. Moreover, the SoftTeco team used JUnit 5 to conduct automated testing and implemented security measures in line with healthcare industry requirements and FDA regulations. Together, these functions create an integrated workflow: connect the device, visualize the video, analyze heart activity, and securely store or share the results. The process is designed to support physicians in making faster, more informed decisions in critical care settings.
Results
The project was delivered on time, within twelve months, by a compact team of four specialists. The application proved its value in clinical use, supporting physicians in nearly two-thirds of therapeutic decisions where timely insights were critical.
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