Objective:
Our client is a leading player in the field of molecular biology, offering cutting-edge technology that addresses complex challenges in the industry. Their platform provides scientists with deep contextual data sets, shedding light on molecular interactions at the subcellular level while preserving sample tissue integrity. Initially focused on delivering high-resolution transcriptomic data, this platform empowers researchers to investigate hundreds of genes simultaneously.
Challenge:
Our client faced a significant challenge related to the processing and analysis of images generated by their Carl Zeiss microscope image station. These images contained crucial data for their research, and efficient analysis was paramount.
Our team was entrusted with designing and implementing a robust backend solution to support image processing and analysis. This solution aimed to enhance the efficiency and accuracy of data extraction from microscope-generated images.
During the project, the team encountered various technical challenges. These included optimizing image processing algorithms, ensuring real-time data synchronization, and integrating complex image analysis techniques. These challenges were addressed through close collaboration with our client's scientific experts, iterative testing, and the application of innovative solutions.
Solution:
The project resulted in the development of a cross-platform backend service, which was deployed to our client's local server in their bio-laboratory. This service was designed to seamlessly handle image processing and analysis tasks.
The project was completed in three months. The project team consisted of dedicated professionals with expertise in software development, image processing, and data analysis.
While there were no business trips, our team regularly interacted with our client's researchers, ensuring that the solution aligned with their scientific objectives.
Technologies:
The technology stack used for this project included:
- C# for application development
- .NET framework for building the backend
- SQLite Database for data storage
- MQTT (Message Queuing Telemetry Transport) for efficient messaging
- Docker for containerization
- OpenCV, a powerful image-processing framework
- Python for advanced image analysis
Results:
Our main accomplishments with this project include:
- Designing and implementing a robust backend service tailored to our client's specific needs.
- Enhancing the efficiency and accuracy of image processing and analysis.
- Facilitating real-time data synchronization.
- Enabling our client to extract valuable insights from microscope-generated images.
Our collaboration with our client has not only addressed their immediate challenges but has also contributed to the advancement of molecular research in the field of biology.
