This is How RMN.AI Will Help Magnetic Resonance Analysis of the Brain Thanks To Artificial Intelligence
It is with great pleasure that I announce that, thanks to your contributions and the work of a team of experts in the field of computer vision and artificial intelligence, volunteers of Glioblastoma.IT ODV, today we have purchased a first cloud server dedicated to hosting the RMN.AI service.
But you may be wondering what RMN.ai is and how does it work?
Magnetic resonance imaging (MRI) exams provide imaging data of great importance to various medical fields including that of neuro-oncology. Beyond the technological aspect of this imaging technique, the evaluation of these data is essential and specialists are needed. Recent trends are aimed at developing software systems for automating certain tasks. The progress of artificial intelligence and in particular of artificial neural networks (deep neural networks) have made possible the automation of processes such as that of segmentation based on modern mathematical tools, their software implementation and the use of hardware of adequate power such as the one we have just initially rented for 3 months. Due to their complexity, these systems are difficult to access by specialist groups outside the original research group and affiliated institutions. Even in premature stages such systems could provide useful insights to the wider medical community. This is especially true when cross-facility experiments are needed and new research approaches such as virtual clinical trials are implemented. RMN.ai is a system based on web (cloud) technologies that allows access to an artificial intelligence system capable of performing an automated segmentation of magnetic resonance imaging and calculating, for example, the volume of the tumour.
RMN.ai also allows for the collection of feedback and data that can be associated with MRIs for further research such as radiomics. Radiomics is the discipline that seeks to obtain, for example, important information on the characteristics of the tumor and prognosis from MRIs. RMN.ai also enables rapid prototyping of new methods of analysis and when completed will allow access to these important advances in radiomics to a wider audience.
In the coming days, the system will be made accessible to radiology experts who collaborate with Glioblastoma.IT ODV for field tests that will pave the way for its use in new research projects. If you are an expert in radiology and are interested, do not hesitate to get in touch with us immediately.
Many thanks to all of you.
