Image recognition is the first breakthrough in artificial intelligence technology such as deep learning, and has been widely used in image search, automatic driving, and face recognition. In the field of medical health, it seems that medical imaging is also the area where artificial intelligence and medical care are the most likely to be developed first. In simple terms, medical image intelligence analysis refers to the use of artificial intelligence technology to identify and analyze medical images, to help doctors locate the disease and analyze the condition, and to assist in making a diagnosis. At present, more than 90% of medical data comes from medical images. Most of these data are analyzed manually. If you can use algorithms to automatically analyze images and compare them with other case records, you can greatly reduce medical misdiagnosis and help make accurate diagnosis. The application of artificial intelligence to medical imaging has become a hot pioneering direction. A number of star companies that use artificial intelligence for medical imaging have already appeared in foreign countries, such as EnliTIc, Butterfly Network, VisExcell, VoxelCloud and so on. IBM, the longest-serving company in the field of medical intelligence, also spent $1 billion in acquisition of medical imaging processing and processing company Merge in August to integrate its technology into the IBM Watson cognitive intelligence system. The country is not far behind, especially since this year, we have seen a number of start-up companies, such as Deepcare, Imagine Technology, Tumasenwei and so on. At the same time, companies starting with medical imaging cloud platforms have gradually entered the field of artificial intelligence, such as medical doctors and Huihui. At present, there are not many companies engaged in intelligent analysis of medical images in China. Based on public information, Lei Feng has compiled more than a dozen of the many medical technology companies to explicitly use artificial intelligence to analyze medical images, thereby improving the efficiency and accuracy of diagnosis. the company. From the situation of these companies, we can get a glimpse of the status quo in the field in China. Survey cannot cover all companies Domestic artificial intelligence + medical imaging company list Company name established time recently financing investor regional technology and products Yasen Technology 2006 A round of 30 million yuan unknown Beijing based on PET / SPECT / fMRI / US and other medical image quantitative analysis, using mathematical models and artificial intelligence technology to improve diagnostic accuracy. Jian Pei Technology 2012 50 million yuan, the round is unknown unknown Hangzhou It has a medical image cloud platform, medical image output, smart medical and intelligent diagnosis, and other medical systems supplemented by big data support equipment and platform construction; it provides case retrieval and medical image intelligent diagnosis services to help doctors locate diseases and analyze diseases. And guided surgery; also developed laser thermal medical film. Ruida Image 2012 Pre-A round of 10 million yuan in the road capital, fast-growing camp Shanghai development has an imaging platform, while exploring the intelligence of different fields, the existing breast-assisted detection, virtual colonoscopy, etc., are preliminary professional domain technology. Medical Duyun 2013 A round of 200 million yuan unknown Beijing has a medical big data platform that integrates, mines and utilizes medical data to assist in the development of new clinical, scientific, hospital management services. The clinical data involved include textual data such as image data and cases. Zhiying Medical 2014 A round unknown Shenzhen has a digital imaging medical-based health analysis management platform that provides early cancer screening, disease-assisted diagnosis, and health index analysis. Huiyi Huiying 2015 A round of tens of millions of yuan Lanchi Ventures, Shuimu Yide Investment Beijing provides medical imaging cloud platform and reading outsourcing services, and through the establishment of human organ models and neural network technology, identify lesions, involving chest X Light, brain nuclear magnetic tumor, chest CT. Medical image 2015 unknown unknown Beijing It has a medical image data cloud platform and a structured knowledge base for image diagnostic data. At present, a large number of historical image diagnosis reports can be intelligently structured and standardized, which can assist doctors in diagnosis. Ruijia Medical Shadow RayPlus 2015 Unknown Unknown Wuhan combines image processing and cloud computing to provide doctors with RayPlus, an image-based computer-aided diagnosis and treatment tool, which is designed to meet the specific diagnostic needs of specialists. DeepCare 2016 Angel Wheel 6 million Fengrui Capital Beijing will use deep learning for medical imaging, reduce reading time and reduce the probability of misdiagnosis. The current main direction is the intelligent imaging diagnosis of chest and lung CT. Imagine Technology 2016 Angel Wheel 11 million Innocent Angel Fund, Jin Yuyun Venture Capital Beijing uses deep learning technology to analyze and identify lesions on medical images, recommend treatment programs, assist doctors to diagnose, and is currently mainly used for the diagnosis of chest and lung diseases. Lianxin Medical 2016 Angel Wheel 3 million unknown Beijing mainly provides tumor data platform construction and medical data analysis, which involves medical image processing, segmentation, registration, etc., and guides radiotherapy optimization. Tuma Deep Dimension 2016 Angel Wheel $1.5 million Reality Fund, Jingwei China Beijing will introduce deep learning into computer-aided diagnosis system, which can be applied to various medical image analysis and diagnosis, pathological image analysis under microscope, and discovery of DNA binding. The sequence specificity of the protein and assist in genome diagnosis and the like. Di Yingjia Unknown Chengdu in 2016 provides medical imaging big data analysis solutions based on artificial intelligence for precision medicine, such as cancer diagnosis and grading based on pathological image analysis. basic information According to statistics, the annual growth rate of medical imaging data in the United States is 63%, while the annual growth rate of radiologists is only 2%; according to the data of the arterial network, the growth data of domestic medical imaging data and radiologists are 30% respectively. And 4.1%. If the image can be interpreted by means of artificial intelligence to aid diagnosis, it can effectively compensate for the gap. The shortage of medical staff in China will only be worse than in the United States, and the income and status of imaging doctors in hospitals is not high. The misplacement of image requirements and the number of doctors has also caused doctors to be overburdened and affect the diagnostic effect, and there is room for artificial intelligence. The intelligent diagnosis clinical trial conducted by Harvard Medical School in the United States shows that artificial intelligence assisted doctors to diagnose breast cancer can reduce the misdiagnosis rate from 4% to 0.5%. The growing demand and advances in technology can basically explain the rise of artificial intelligence companies in the medical imaging arena. From the time of establishment, this year may be unavoidable, and it is considered to be the "first year" of artificial intelligence + medical imaging (pure subjective judgment). According to the statistics in the above table, there are five companies established this year; the rest of the companies are also integrated in 2012-2015, but in the early days, more image cloud services were provided, and smart business began to expand this year. In contrast, the domestic is not behind. Among the several foreign companies mentioned above, only the Butterfly Network was established earlier, in 2011, and the rest of the company is only about two years old. Geographically, 8 of the 13 companies are located in Beijing, and the rest are located in Shanghai, Shenzhen, Hangzhou, etc. This is in line with the overall geographical distribution of artificial intelligence companies. Financing status in 2016 In foreign countries, medical imaging intelligent analysis companies have developed earlier. At present, some companies are relatively mature, and they are in the stage of A round of financing, and they have obtained B round financing. For example, EnliTIc received $10 million in Series A funding last year, using deep learning technology to help radiologists analyze medical images; Butterfly Network received $100 million last year after $80 million in Series A funding in 2014. Round B financing, a medical imaging technology company that builds a database of thousands of images through a new medical imaging device and then uses artificial intelligence to analyze new clinical treatments. In contrast, domestic companies are generally dominated by angels, especially emerging start-ups. Only some companies that have been established for several years have already reached the A round. At present, the highest amount of financing is Zhiduyun, A round of 200 million yuan, and at the end of 2015, it also led the million-dollar B-round financing of the diabetes management platform micro-sugars. The following is a list of domestic financing events in this area this year: In February 2016, Imagine Technology received 11 million yuan of angel round financing, the investors are Yingnuo Angel Fund and Jinyun Venture Capital; In June 2016, DeepCare received 6 million yuan of angel round financing, the investor is Fengrui Capital; In July 2016, Lianxin Medical received 3 million yuan of angel round financing; In August 2016, Yasen Technology 30 million yuan A round of financing; In October 2016, Tuma Deep won a $1.5 million angel round of financing, the investors are Zhenge Fund and Jingwei China; In October 2016, Huiyi Huiying received tens of millions of yuan in Series A financing, and the investor was Lanchi Ventures. Development path From the perspective of the company's development path, companies that diagnose medical imaging intelligence can be roughly divided into two categories. The first category of companies mainly provide artificial image technology and provide image analysis and diagnosis services, including DeepCare, Imagination Technology, Tuma Deep, Yasen Technology, etc., and generally set up for a short period of time. For example, DeepCare mainly develops medical image detection, identification, screening and analysis technologies, and provides image recognition services for medical device manufacturers and primary medical centers. For new cases entered into the database, it can perform algorithm matching to find similar cases of image data. Yasen Technology focuses on medical image analysis applications, based on quantitative analysis of medical images, using mathematical models and artificial intelligence techniques to improve diagnostic accuracy. The second type of company originally provided medical image cloud services, and then extended the service to the field of intelligent diagnosis. The representative time was set up by Huihui Huiying, Medical Imaging, and Medical Duyun. The establishment time was generally two to three years. For example, Huiyi Huiying is an independent third-party medical imaging consultation platform. In the early days, it focused on the online imaging center based on cloud platform. From this year, it focused on the field of artificial intelligence and assisted image screening. Medical big data and medical cloud platform solutions, while using machine learning, to mine text data and image data in clinical data. From the perspective of products and services provided, medical imaging intelligent diagnostic companies can be divided into two categories. The first category focuses on medical imaging services such as image cloud platforms and image intelligence analysis. The second category is to build a medical big data platform, which includes the analysis and processing of medical image data, such as Lianxin Medical and Medical Duyun. Lianxin Medical focuses on the establishment of tumor big data platform and medical data analysis. The data generated by the system in the process of docking treatment, including the processing, segmentation and registration of medical images, optimizes radiotherapy. As mentioned above, the medical data of Medical Duyun also includes such text data as cases. The three major thrusts of the popularization of artificial intelligence applications are new technologies, computational power and massive data represented by deep learning. The former two are common in various industries. Therefore, for the artificial intelligence companies in the medical field, the most important problem may be data. . For example, the current medical images have almost no labeling of the lesions, and this systematic data collation process is very professional and requires professional doctors to cooperate, which is also unique in the medical industry. Since medical data has not yet been interconnected, domestic medical image data applications are still in their infancy. This is also true in foreign countries. Data sharing in the US medical industry is difficult and data formats are difficult to unify. However, with the strengthening of informatization, there will be more and more artificial intelligence companies in the future, just like the information system promotes the development of cloud platforms for images. Lead Acid Battery categories are described as follows: Solar system 12V, Uninterrupted Power Supply with battery,12V lead acid battery Foshan Keylewatt Technology Co., LTD , https://www.keylewatt.com
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