Imagine trying to hit a tiny target inside the body using a needle, but the map you're using is slightly blurry. This system uses AI to merge different medical images into one crystal-clear map and a robot arm to steer the needle with perfect accuracy. It removes the guesswork and shaky hands from the process to ensure the biopsy hits the exact spot every time.
Prostate cancer diagnosis often fails due to uncertain target identification and inaccurate needle positioning. This leads to diagnostic errors and inefficient use of healthcare resources.
A robotic needle positioner integrated into a single cart and a Deep Convolutional Neural Network (PROST-Net) for MRI and Ultrasound image fusion.
If you are a surgical robotics firm dealing with high error rates in soft-tissue biopsies — this project developed a robotic needle positioner and AI image fusion that zeros the positioning error. This allows for the creation of a high-precision biopsy cart ready for clinical trials.
If you are a private oncology clinic dealing with diagnostic errors and repeated biopsies — this project developed an AI-powered segmentation tool that reduces target uncertainty. This improves patient outcomes and reduces the time and cost of diagnosis.
If you are a medical AI software house dealing with the difficulty of merging MRI and Ultrasound data — this project developed a Deep Convolutional Neural Network for prostate segmentation. This technology can be integrated into existing imaging software to improve lesion identification.
Based on available project data, the specific unit price is not mentioned, but the project is analyzing time and cost reductions for European healthcare systems.
Yes, the project focuses on 'engineerization' to move from a proof-of-concept to a product prototype, including a single-cart design to simplify medical certification.
Based on available project data, the specific licensing terms are not listed, but the project involves a consortium of 5 partners including 3 SMEs.
The system divides electronics into interface/data processing and safety-critical controls to reduce operational risks and simplify the medical certification process.
The project runs from 2023-05-01 to 2026-04-30, aiming to produce a prototype ready for clinical trials by the end of the period.
The consortium is lean and commercially oriented, consisting of 5 partners across 3 countries (IT, AT, DE). With a 40% industry ratio and 3 SMEs involved, the project is well-positioned for technology transfer, balancing academic research from 2 universities with the practical engineering and market-entry capabilities of small and medium enterprises.
Contact Universita Degli Studi di Verona regarding the ROBIOPSY prototype
Contact us to explore licensing opportunities for the AI-driven prostate segmentation algorithms.
