Analysis of the application status and industry development of AI technology in medical imaging

With the rapid development of technology, the continuous expansion of medical data, and the continuous upgrading of hardware equipment, the combination of artificial intelligence and medical methods is becoming more and more diverseAt present, AI's landing application in the medical field mainly includes medical imaging, intelligent diagnosis and treatment, intelligent diagnosis, intelligent voice, health management, case analysis, hospital management, new drug research and development and medical robots, among which the most widely used in medical imaging, the development of imaging medicinemedical imaging is the main basis for doctors to complete diagnosis, through the analysis and comparison of images, so as to complete the diagnosis of the basisHowever, in the actual process, there will often be the following problems:(1) imaging diagnostic talent resources are scarceMedical institutions generally lack a high level of imaging physicians, in the diagnosis of disease stoic, disease, and so on(2) There are diagnostic errors in traditional qualitative analysisDoctors are generally good at qualitative analysis, many small quantitative changes can not be judged by the naked eye, it is difficult to do quantitative analysis(3) The doctor's length of time is longThe current way of image presentation is data and images, rather than the most effective information, which greatly limits the speed of the doctor's manual viewingII, AI plus medical imaging to help disease diagnosisthrough the introduction of artificial intelligence can effectively solve some problems, the current application of artificial intelligence in the field of medical imaging mainly in the following categories:1Image reconstruction of image equipmentAI can be through the algorithmic image mapping technology, the acquisition of a small number of signals to restore the same quality as the full sample image, and the use of image reconstruction technology, can be rebuilt by low-dose CT and PET images to obtain high-dose quality imagesThis also reduces the risk of radiation while meeting clinical diagnostic needs 2 Intelligent Assisted Diagnosis of Disease
(1) Intelligent Assisted Diagnosis of Lung Disease the most mature areas of domestic application of AI-CT imaging in the identification of pulmonary nodules AI can effectively identify the easy-to-miss knots such as 6mm or less actual nodules and grinding glass nodules, and the accuracy is around 90%, while providing nodule position, size, density and properties In addition, lung diseases such as tuberculosis, chest and lung cancer can be screened (2) Intelligent Assisted Diagnosis of Undereye Disease
is currently the most widely used screening of sugar mesh disease Sugar mesh disease is a common retinal vascular lesions, but also diabetics of the pharmaceutical blinding eye disease, early often without any clinical symptoms, once symptoms have missed the best treatment time about 27 million patients with sugar mesh disease in China, with people's attention to screening for sugar mesh disease, the demand for eye-bottom reading tablets increased, but engaged in eye-bottom medical services and researchers only 800 to 100 people, serious shortage of medical resources, misdiagnosis, missed diagnosis more Applying artificial intelligence to eye-base readings and conducting initial screening can greatly improve the current efficiency of screening for sugar mesh disease AI through deep learning of images at the bottom of the eye, it is possible to achieve the diagnosis of some under-eye diseases, in addition to glycopathy, glaucoma, geriatric macular degeneration, cataracts and macular fissures (3) Intelligent assisted diagnosis of brain disease
The current intelligent diagnosis of brain disease includes brain haemorrhage, internal atherosclerosis diagnosis, intracranial aneurysm diagnosis and cervical artery vulnerability plaque assessment among the , cerebral hemorrhage is a difficult disease with a high fatal disability rate in the internal and external neuroscience AI-head CT, based on machine vision and deep learning technology, can quickly locate the cerebral hemorrhage area, accurately quantify the volume of bleeding, determine the presence of cerebral palsy, at the same time, can complete the professional high requirements, long-term image evaluation, to assist doctors to accurately judge, so that patients get the best treatment plan the first time (4) Intelligent assisted diagnosis of neurological disease
AI is used in neurological disorders mainly including epilepsy, Alzheimer's disease and Parkinson's disease AI can process and analyze the patient's image data and compare it with the normal population group, so as to calculate the size and location of the lesions with metabolic abnormalities, and give the recommendations of the treatment plan and the prediction of the treatment effect through cognitive technology (5) Intelligent Assisted Diagnosis of Cardiovascular Disease
AI can use deep learning technology and image processing technology on the basis of chest CT data, design specific algorithms to evaluate coronary artery fragile plaques, perform intelligent auxiliary diagnosis of coronary heart disease, plan stent surgery placement program, etc At the same time, it can also intelligently diagnose complex diseases such as aortic disease type and aortic aneurysm 3 Intelligent mapping target area At present, radiotherapy is one of the main treatment methods for cancer patients, and the correct positioning and precision mapping of diseased organs is the basis and key technology of radiotherapy Therefore, before radiotherapy, it is necessary to mark the location of organs and tumors on the CT image, which, according to traditional methods, generally takes 3 to 5 hours for the doctor the application of AI technology can greatly improve efficiency, AI intelligent mapping target area of high accuracy can greatly avoid the target area of inaccurate induced ineffective treatment At present, the AI-plus target area has been successfully used in lung cancer, breast cancer, nasopharyngeal cancer, liver cancer, prostate cancer, esophageal cancer and skin cancer 4 Intelligent judgement of pathological slices pathological slicing is a complex task that often requires a doctor with a wealth of expertise and experience, and even with professional experience, it is easy to ignore imperceptible details leading to diagnostic bias The study of introducing artificial intelligence into pathological slicing, and perfecting the knowledge system of pathological diagnosis by learning the characteristics of pathological slicing cell level, is the best way to solve the efficiency of reading and the accurate value of diagnosis 5 Other intelligent assisted diagnostic solutions the use of artificial intelligence in medical imaging includes 3D imaging of organs, ultrasound-assisted thyroid nodules, bone age analysis, and intelligent diagnosis of fractures , some AI-plus medical imaging enterprises and their business models
AI-plus medical imaging products and enterprises continue to emerge, according to the Firestone creation database shows that the current number of domestic AI-plus medical imaging enterprises more than 100, a single financing of nearly 20 cases, the total financing of more than 2.6 billion yuan Some companies and their business models are included in the Schedule: Schedule Part Of AI plus Medical Imaging And its business model
IV, Summary Medical Imaging has now become the most popular direction of artificial intelligence in the medical field, but there are still some challenges in the practical application process, such as data acquisition and data labeling issues, lack of industry standards, lack of guidelines for registration approval, technology innovation issues, etc However, with the continuous development of AI-related technology, the continuous improvement of national policies, I believe that AI-plus medical imaging will be rapidly commercialized in the future original title: Application of AI Technology in Medical Imaging and Status of Industry Development