柏视医疗完成数千万元A轮融资,致力开发多病种多模态产品

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On May 24th, recently, the domestic artificial intelligence medical company Baishi Medical announced that it has completed tens of millions of A round of financing. This round of financing was led by the National Small and Medium Enterprise Development Fund managed by China State Venture Capital, and the angel investor Huachuang Capital and other institutions voted.

Founded in 2017, Perspect Medical is committed to the development of multi-modal multi-modal products that meet the habits of the medical industry . At present, it has introduced AI diagnostic modular products for diseases commonly used in the lung, breast cancer, cervical cancer, liver cancer and other diseases. Technology covers ultrasound, nuclear magnetics, CT, X-RAY, and pathology.

Lu Yao, the founder of Baishi Medical, is a professor of the National Youth Thousand Talents Program. Before he founded the company, he worked at the University of Michigan Medical School for many years. He has more than 15 years of research in medical imaging and computer-aided diagnosis (CAD). After returning to China, he served as a professor at Sun Yat-sen University, deputy director of the Guangdong Provincial Key Laboratory of Computational Science, and director of the Computational Medical Imaging Laboratory at Sun Yat-Sen University.

On the team side, Baixuan Medical CEO Shen Shuo is a Ph.D. in mathematics and a master of electronics and computer engineering from Purdue University. He served as the director of the China Internet Information Center Laboratory and the chief engineer of the National Internet of Things Logo Management Public Service Platform of the National Development and Reform Commission. He also worked for Huawei. Years of industry experience and management experience. As a managing partner, Xu Chenyang holds a Ph.D. in Electrical and Computer Engineering from Johns Hopkins University in the United States, and has made important contributions in the fields of computer vision, image analysis theory, and medical imaging applications. Previously, Dr. Xu served as the chief technology officer and general manager of the Siemens Silicon Valley Innovation Center.

It is reported that in the product of the cancer treatment stage of Baishi Medical, the current detonation system for the target area of ​​nasopharyngeal carcinoma has been developed. All data of the system are marked by the chief physician of the Affiliated Tumor Hospital of Sun Yat-sen University, which can not only automatically delineate GTV (tumor area), but also automatically delineate CTV (clinical target area).

CTV delineation is the key to radiotherapy to control tumor recurrence and metastasis, and it is also the most difficult and time-consuming part of target delineation. Lu Yao said that under the premise of fully ensuring the precision of the target area, the delineation time can be shortened from several hours to several minutes, which greatly improves the clinician's diagnosis rate. The product of nasopharyngeal carcinoma has been clinically verified at the Cancer Center of Sun Yat-sen University.

At 2017 RSNA, Philips released the artificial intelligence platform IntelliSpace Discovery 2.0 (ISD2.0), which is the only selected AI company, which has attracted the attention of the industry. Its CT/MRI-based clinical target for radiotherapy for nasopharyngeal carcinoma. The automatic sketching system has been embedded in the ISD platform, which is the only mature AI product in the industry that has been strictly reviewed and commercialized by top medical device manufacturers.

Li Chengyu, vice president of China Venture Capital, believes that the essence of medical care is a human- and intellectual-intensive industry. The fundamental problem facing China's medical reform is that the number of doctors is small and the level of doctors is uneven. With AI algorithms, computing power, big data, and capital investment, AI's penetration of medical care is expected to dramatically change the cost and efficiency of medical services, fundamentally solve the supply bottleneck of medical service resources, and improve the difficulty of seeing a doctor.

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