Medipixel

Medipixel is a MedTech startup that aims to contribute to the improvement of the quality of human life by innovating the way we diagnose diseases and controlling surgical robots with the power of AI. Consisting of a group of AI experts in computer vision, deep learning, and reinforcement learning, Medipixel conducts research and product development for cardiovascular disease diagnosis and coronary intervention robots together with the best healthcare professionals in Korea such as Seoul Asan Medical Center. In November 2018, MediPixel won the championship in the QuickFire Challenge hosted by Johnson & Johnson.

MediPixel currently offers three solutions for intervention surgeons:

1. An AI Based Diagnosis Solution makes it possible for doctors to spot lesions while performing a coronary angiography, perform segmentation of the vessel in question within just one second and analyze the lesion’s status.

2. A Guide & Planning Solution clearly visualizes the hidden part of the coronary artery to make doctors perform guidewire manipulation with more ease and confidence, which is quite useful especially in case of CTO. Furthermore, the solution frees doctors from the need to use contrast — this is important because contrast can cause potentially fatal reactions in 5 to 10% of patients.

3. An Automated Navigation Engine automates navigation through coronary arteries. Once the destination is reached, it controls a robotic unit by giving the most appropriate real-time commands in its existing situation, thus delivering devices such as guidewire to the destination in the most efficient way.

We’re open to any candidates who are excited to apply their knowledge and skill in deep learning to real-world medical data and surgery robots. Do you have any questions? Email us at [email protected]

Company’s Keywords:

deep learning, artificial intelligence, machine learning, reinforcement learning, cancer diagnosis, robotics, surgery robot, medical images, coronary intervention, cardiology, robotic surgery, healthcare, digital surgery, pci