Every new technology is born out of a need for change, but it is artificial intelligence (AI) that is redefining modern medicine. The introduction of AI into radiology is not only changing the way patients are diagnosed, but also speeding up the process and increasing the precision of analysis. The Radpoint project has become a prime example of how modern technology is changing the face of medical diagnostics. Together, we have built a system that can not only speed up diagnoses, but also improve their quality.

Diagnosis of need ​

We were faced with a project that has the potential to transform the entire radiology industry. Radpoint was looking for a way to innovate its RIS/PACS/VNA infrastructure. Although radiology, as a discipline, had benefited from digitisation, it still lacked advanced tools to support diagnostics.

Radiologists, despite the digital tools available, had to spend significant amounts of time analysing images manually, which prolonged the diagnostic process and increased the risk of errors. The problem was the lack of technology that could support diagnostic imaging, reducing the time required for analysis and increasing the precision of anomaly detection.

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Motivations for introducing AI in modern radiology ​

Radpoint's motivation was clear - they wanted to innovate to revolutionise diagnostic processes. Their goal was to create an advanced system to support radiologists in their daily work. The client expected that, thanks to AI, the time needed to analyse images would be significantly reduced and the accuracy of diagnoses would increase.

What's more, they wanted to lead the market by offering modern and reliable solutions for radiology.

The solution, or AI in radiology ​

The solution we proposed was to integrate advanced AI tools directly into the RIS/PACS/VNA systems already used by Radpoint. A key element of the project was the introduction of systems based on artificial intelligence algorithms that can analyse medical images, identify potential abnormalities and support radiologists in making diagnostic decisions.

The systems automatically analyse each image, indicating potential lesions, which significantly relieves the radiologists' workload, leaving them more time for complex and unusual cases.

A key element was the use of artificial intelligence, which not only automates the analysis of the images, but also provides a preliminary diagnostic report. This report can be reviewed by the radiologist and, if necessary, adjusted to become part of the final diagnosis.

However, the AI in the Radpoint system is more than just automated analysis. The system is designed to support radiologists in prioritising cases. Thanks to artificial intelligence, specialists can better manage their worklist, focusing on urgent or emergency cases. This impacts on work efficiency and reduces response times at crucial moments.

Artificial intelligence also triggers mobile alerts, which are instantly delivered to radiologists' devices in critical cases. This allows them to respond instantly to cases that require urgent attention, significantly improving the standard of care and speeding up interventions.

The integration of these functions with RIS/PACS/VNA systems makes the radiologists' work more automated and the diagnostic process gains in precision and speed.

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Designing a system to introduce AI into radiology ​

Designing the solution required close collaboration with the Radpoint team. Thanks to modern image and data processing tools, the AI system was flexibly integrated into the existing infrastructure. This meant that the radiologists did not have to learn how to use a completely new system - the AI simply appeared as an additional layer of functionality in their daily work. You can read more about the design of the solution on the Radpoint website.

The iterative approach to design allowed us to test and optimise individual functions on an ongoing basis, ensuring that every step of the implementation went smoothly. It was also crucial to ensure the security and privacy of medical data, which we achieved with advanced encryption and data protection solutions.

Radpoint technologies and tools ​

The project uses state-of-the-art tools based on artificial intelligence, including deep learning algorithms that can recognise patterns in medical images. These algorithms learn from thousands of examples, allowing them to automatically detect abnormalities such as strokes, white matter lesions, lung nodules or other lesions. These solutions support radiologists, allowing them to make fast and accurate diagnoses.

The RIS/PACS/VNA system, enriched with artificial intelligence functions, becomes an even more versatile tool that not only catalogues and archives images, but also actively supports the diagnostic process.

Effects of implementing AI in radiology ​

The algorithms implemented in the Radpoint system are primarily intended to assist the radiologist in diagnosis and medical record creation.

• Intelligent prioritisation of the worklist allows focus on urgent cases and rapid response in critical situations
• AI-based tools reduce diagnostic time by up to 30%
• The ability to automatically detect a large number of lesions and compare images can increase the accuracy of diagnosis
• Implemented automation maximises efficiency and optimises radiology practitioners' performance

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What if Radpoint had not introduced AI in radiology? ​

In the medical industry, where time and precision are crucial, digitalisation and innovative solutions have great potential.

The implementation of artificial intelligence at Radpoint has changed the way radiologists work, improving the quality of diagnosis. Thanks to AI, it has become possible to automatically analyse medical images, speeding up the diagnostic process and improving the accuracy of diagnoses. With the growing needs of the medical industry, artificial intelligence is becoming an important tool to support doctors. The Radpoint project is proof that AI has the potential to become the future of radiology.

If you are planning to implement innovation into your project, we can help you!