In recent years, new technologies have significantly improved the quality of medical imaging diagnostics. Their adoption, combined with the soaring demands for imaging within medical establishments, has led to a sharp increase in medical image data volumes… which poses several challenges for radiologists.

Firstly, the ever-increasing volumes to be processed make radiologists’ work more complex. What’s more, data is often hosted on multiple separate platforms, making it difficult to use and wasting precious time for healthcare professionals. How can medical establishments meet the challenge of simplifying data management in medical imaging?

Centralize and facilitate access to medical imaging data

Medical imaging professionals often work in a number of different establishments (hospitals, private practices, etc.) and follow patients who themselves use different structures for consultations. Accessibility of data is therefore a real challenge. To practice in the best possible conditions, medical staff must have permanent access to images and patient files… wherever they work.

It is therefore important to break free from the physical barriers of on-premise medical applications. Adopting cloud-based medical imaging solutions is the best way to benefit from rapid data access.

Data centralization is another strategic lever to facilitate radiologists’ day-to-day work. Picture Archiving and Communication Systems (PACS) make it possible to store all medical images in a central database that can be shared with other healthcare professionals. These images can be integrated into electronic medical records directly from the platform. As well as saving considerable time for medical staff, these solutions also reduce diagnosis times and make decision-making more reliable. The accessibility and centralization of imaging data directly improves patient care.

This is the backdrop to part 2 of the “Ségur du numérique” program, which includes the deployment of a single platform called DRIMbox, which will interface all imaging data from hospitals and radiology practices.

Emerging trends in medical image processing

The medical imaging sector relies on new technologies such as artificial intelligence and machine learning to perfect image processing and analysis. For example, AI algorithms can be trained to automatically detect anomalies in medical images, such as tumors and fractures, thus simplifying the radiologist’s job. These technologies can also sort images by order of processing priority, or assist interpretation by highlighting areas of interest on an image.

These new technologies assist radiologists by simplifying their work and giving them more time to devote to patient care. Olea Medical has developed several solutions with this in mind, such as an MRI solution that automates breast cancer screening, as well as solutions for neurology and oncology to detect lesions more quickly, assess their evolution and implement the best treatment strategy.

Combined with centralized data management, new medical imaging technologies improve the efficiency of radiologists’ work and the quality of patient care. They also facilitate collaboration between institutions and enhance radiologists’ job satisfaction by relieving them of the most tedious tasks. As such, they are the first step towards finding a response to the personnel shortage in the imaging sector.