Vysioneer to Collaborate with National Taiwan University Hospital to Bring a First-ever AI-based Auto Contouring System to Brain Tumor Radiosurgery
Date: Aug. 14th, 2019
Vysioneer Inc. today announced Vbrain, an AI-based brain tumor auto contouring system used to assist radiation oncologists in radiosurgery. The VBrain system was launched at National Taiwan University Hospital (NTUH) in Taipei in July 2019 for clinical trials, the first AI-based brain tumor auto contouring use case in the world. It has been tested on more than 20 patients for the treatment of the three most common types of brain tumors, namely brain metastasis, meningioma, and acoustic neuroma.
VBrain has been seamlessly integrated with existing radiosurgery workflows at NTUH. Radiation Oncologists and Neurosurgeons can have tumors accurately auto-contoured in real-time without changing any current routine practices, reducing tremendous treatment planning time and ultimately improving patient outcomes.
“Over the past few years, Artificial Intelligence is quickly entering the medical field but primarily in research publication. Very few AI solutions have been deployed into clinical workflows to have a true clinical impact. Vysioneer aims to develop and deploy AI-based solutions to assist medical practitioners in streamlining workflows and improving patient outcomes. Take VBrain as an example, the system acts like a second set of eyes and hands: all potential tumors can be identified, prioritized, and clearly delineated. Clinicians only need to validate or fine tune AI’s results.” said Jen-Tang Lu, Co-founder and CEO at Vysioneer.
The VBrain solution is used to auto contour the three most common types of brain tumors: brain metastasis, meningioma, and acoustic neuroma. It only takes less than a minute to complete tumor delineation with a 90%+ accuracy, which would’ve taken tens of minutes to hours in the traditional workflow. The system helps reduce tremendous treatment planning time and enable clinicians to have more time for patient communication and treatment optimization. This collaborative research findings have been accepted as an Oral Presentation at the American Society for Radiation Oncology (ASTRO) Annual Meeting 2019. Vysioneer will present the findings in Chicago in September.
Vysioneer is an AI for Healthcare startup, founded in 2019, with a focus on using deep learning to automate cancer care clinical workflows including treatment and diagnosis throughout cancer patient journey. The company is based in both Boston and Taipei backed up by MIT Sandbox, Princeton Alumni Entrepreneurs Fund, and Nvidia Inception program. The co-founder and CEO, Jen-Tang Lu used to work as a Machine Learning Scientist in the Center for Clinical Data Science jointly operated by the Massachusetts General Hospital (MGH) and Brigham and Women’s Hospital (BWH) in Boston after he received his PhD degree from Princeton University. Dr. Lu orchestrated the development of DeepSPINE (deep learning-based system for spinal stenosis grading) and DeepAAA (deep learning-based system for abdominal aortic aneurysm detection), which have been already in use at MGH and BWH, assisting radiologists in diagnosis in real-time.
Vysioneer comprises of professionals from MIT, Princeton, Harvard, MGH, NTU, and Silicon Valley tech companies with strong passion about transforming cancer treatments with Artificial Intelligence. Vysioneer is currently hiring Machine Learning Scientists and Software Engineers. We welcome anyone who are keen on using AI to transform cancer care to join us!