Periodic Reporting for period 1 - AUTO.DISTINCT (A fully automated deep learning-based software for fast, robust and accurate detection and segmentation of tumours and metastasis)
Okres sprawozdawczy: 2020-10-01 do 2022-03-31
In the AUTO.DISTINCT project we introduce a fully automated software for the robust, accurate and efficient pre-processing, detection, and volumetric segmentation of (lung) tumours and metastases on CT images.
End-users for our developed tool are clinicians / radiologists, assisting them in their workflow. We have just established a working server and environment for our developed software to be deployed (internally running at the premises of Maastricht University). Our developed software has been registered under MDD regulations and obtained it's regulatory approval under MDD. This provides us with additional time to prepare for a full MDR registration in the future, most likely as a Class II Software as Medical Device.
As current end result of the PoC we established a fully working and operational software platform, which we can now push for a first round of testing and receiving back user experiences from the field. With this initial phase of using the platform and receiving back experiences we will further develop our platform to market readyness.
End-users for our developed tool are clinicians / radiologists, assisting them in their workflow. We have just established a working server and environment for our developed software to be deployed (internally running at the premises of Maastricht University). Our developed software has been registered under MDD regulations and obtained it's regulatory approval under MDD. This provides us with additional time to prepare for a full MDR registration in the future, most likely as a Class II Software as Medical Device.
As current end result of the PoC we established a fully working and operational software platform, which we can now push for a first round of testing and receiving back user experiences from the field. With this initial phase of using the platform and receiving back experiences we will further develop our platform to market readyness.