Milvue : Revolutionizing Medical Imaging with AI

Healthcare is undergoing a rapid transformation, driven by artificial intelligence. Milvue, a pioneer in applying AI to medical imaging, stands at the forefront of this revolution. In this article, based on an interview with Ilana Sultan, Radiographer and author of  “Artificial Intelligence in Medical Imaging” , we explore how Milvue was founded, its significant impact on medical imaging, and its ambitious vision for the future, as shared by its co-founder, Alexandre Parpaleix.

In the beginning

The idea for Milvue emerged during the first year of Alexandre Parpaleix’s radiology internship, co-founder of the company. “During my first year of residency in radiology, I became interested in AI because at the time, people were talking about Watson, the AI solution offered by IBM in 2016, which was a precursor to diagnostic assistance and decision-making in medical imaging,” he recalls. But in everyday practice, he noticed a major problem : “In the hospital, I observed a lack of coordination and communication between different doctors in the medical decision-making process for patients.”

With the shortage of radiologists and the growing number of imaging prescriptions, the need for a solution became evident. “There aren’t enough radiologists for the number of images that need to be interpreted,” he explains. While teleradiology improved organization through the sharing of medical records, Dr. Parpaleix saw even greater potential in artificial intelligence. “Artificial intelligence is another solution that offers a real advancement in managing a larger number of patients,” he concludes. This observation, combined with the shortage of radiologists and the increase in imaging prescriptions, led to the creation of Milvue.

The Tool That’s Revolutionizing Medical Imaging

Artificial intelligence is transforming the field of medical imaging by automating simple and administrative tasks. This delegation allows healthcare professionals to save time and increase their autonomy, thereby enhancing their expertise.

“AI has proven its effectiveness with an average radiologist due to its knowledge and diagnostic performance,” explains Alexandre Parpaleix. “It allows radiologists to simply verify their work, simplifying their tasks and daily routine for so-called simple diagnoses.” However, AI is not yet capable of diagnosing complex cases, such as a combination of pathologies or rare conditions.

The Impact on Radiographers

Alexandre Parpaleix explains that AI simplifies and optimizes the work of radiographers. “Machine manufacturers are incorporating AI to facilitate patient positioning, dose settings, image acquisition, and reconstruction,” he says. Milvue offers automatic measurement modules for tasks such as Cobb angles and limb lengths. The radiographer “verifies and supervises the algorithm with their expertise. It’s much more beneficial to work with radiographers coupled with AI because it frees up time for them to focus on diagnostics and assist the radiologist in decision-making.”

The Future of Radiologists

According to Alexandre Parpaleix, artificial intelligence will not replace radiologists but will assist them. “The goal is to make the radiologist’s work as easy as possible and to create an augmented healthcare professional,” he says. Radiologists bring clinical context to images, a task that AI cannot yet perform on its own. Dr. Parpaleix emphasizes, “Moreover, we realize that the AI-radiologist duo is more effective than the radiologist alone,” highlighting the efficiency of this synergy.

AI could influence healthcare reimbursement policies in France. In the United States, some algorithms already have reimbursement codes. “AI will never operate independently. It reinforces the central role of the radiologist and their expertise,” he adds, noting that AI will enable the interpretation of more cases and the treatment of more patients. In the future, the use of AI could become mandatory in the medical diagnostic process.

In Conclusion

The future of AI in medical imaging is very promising. Alexandre Parpaleix envisions AI playing a crucial role in advanced diagnostics. “AI companies are growing, acquiring more data, partners, and expanding their products towards complex diagnostics,” he explains. In the future, he believes, “We will also be able to detect biomarkers in images that will predict the onset of a disease in a patient, predict the effectiveness of a treatment for a cancer patient, or predict the progression of a disease based on their medical history.”

However, these advancements present challenges, particularly in terms of regulation and algorithmic complexity. Despite these obstacles, Dr. Parpaleix remains optimistic about AI’s potential to transform medicine. “This is a long-term effort that will not be accomplished by a single actor but through teamwork and close collaboration among various partners and healthcare stakeholders, with a collective goal of improving the quality of care.”

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