Healthcare & Pharma
Healthcare & Pharma
Algorithms at the service of diagnostic imaging
This project’s protagonist is a multinational company that produces solutions and tools for diagnostic imaging. Our intervention led to the creation of an algorithm that automatically identifies the presence of possible anomalies in the diagnostic images that will then be submitted to the next and more accurate evaluation of the radiologist.
- Description and benefits
Radiologists use diagnostic tools, such as ultrasound scans with or without contrast, to verify the possible presence of lesions in the human body’s organs.
Sometimes the presence of lesions on images is not clear and their detection requires great attention and expertise from radiologists. For this reason we have developed a deep learning algorithm to quickly scan the hundreds of images that compose an examination and detect the possible existence of lesions.
Increased accuracy
There is an improvement in the diagnostic process both in terms of time and reliability
Sharing of expertise
The objective identification of abnormalities, regardless of the individual experience of the specialist, allows for their sharing
Continuous evolution
The algorithm is based on the knowledge of experienced radiologists and can be updated and evolve following their expertise
Deepening case study
Neural networks and deep learning for lesion detection
In order to carry out this project, we used neural networks. We trained our deep learning algorithm with a series of contrast images in which experienced radiologists had highlighted the presence of abnormalities.
C.F. e P.IVA 07015910966| Via Schiaffino 11/19, 20158 Milano