Ongoing research in the fields of medicine and artificial intelligence is enriched by a series of open competitions, designed to challenge data scientists, doctors, and researchers to devise new solutions to ever-challenging problems. KiTS 2023 (Kidney and Kidney Tumor Segmentation Challenge) is the third iteration of a competition focused on the development of a system for automatic image segmentation of kidneys, specifically, renal tumors and cysts.
With over 430,000 individuals diagnosed with kidney cancer each year, the need for effective diagnostic support solutions in the medical sector is more pressing than ever. Kidney tumors, in fact, are quite common, and often the distinction between malignant and benign tumors proves challenging, making the development of reliable and precise methods imperative.
Senticlab participated in KiTS 2023, defining an innovative segmentation algorithm that achieved an accuracy level of 80%, placing them in the top 5 of the proposed solutions. It's particularly noteworthy to see that the accuracy gap between them and the first-place team (from nVIDIA) was just three percentage points. This demonstrates Senticlab's dedication, experience, and ability to provide solutions comparable to those from industry giants.
The technical details of the approach adopted by SenticLab are currently being utilized for drafting in a scientific paper, to share their proposal with the wider scientific community.
Beyond the tangible results obtained in competitions like KiTS, what truly makes the work of Senticlab special is our unwavering dedication to progress and innovation. Collaborating closely with synbrAIn, both teams invest in research and experimentation, harnessing artificial intelligence for purposes ranging from diagnostic decision support to automated medical image analysis.
Our corporate philosophy is clear and consistent: we believe in human empowerment through technology. We firmly believe that AI can and should be used to amplify human capabilities, rather than replace them. In the context of medical diagnosis, this translates to solutions that assist doctors in making more informed decisions, potentially saving lives.
