Artificial Intelligence in the field of medical imaging applications are as follows:
1, image reconstruction of imaging equipment
AI can be used by algorithmic image mapping techniques to recover a small number of signals captured to the same quality as the full-sampling image, and the use of image reconstruction techniques can be made from low-dose CT and PET images can be reconstructed from low-dose CT and PET images to obtain high-dose quality images. This reduces the risk of radiation exposure while meeting clinical diagnostic needs.
2. Intelligent Aided Diagnosis of Diseases
(1) Intelligent Aided Diagnosis of Lung Diseases
Domestic application of AI+CT imaging is most mature in the identification of lung nodules, AI is able to effectively identify easy-to-miss nodules, such as solid nodules under 6mm and ground glass nodules, with an accuracy rate of 90%, and at the same time, it is able to provide information about the location, size, density, and nature of nodules. nature of the nodule. In addition, it can screen for lung diseases such as tuberculosis, pneumothorax, and lung cancer.
(2) Intelligent assisted diagnosis of fundus diseases
The most widely used is the screening of glycemic retinopathy. Glycologic retinopathy is a common retinal vasculopathy, but also the pharmaceutical blinding eye disease of diabetic patients, early often do not have any clinical symptoms, once the symptoms have missed the best time for treatment.
(3) Intelligent assisted diagnosis of brain diseases
Currently, intelligent diagnosis of brain diseases includes cerebral hemorrhage, diagnosis of internal atherosclerosis, diagnosis of intracranial aneurysm and carotid artery vulnerable plaque assessment.
(4) Intelligent Aided Diagnosis of Neurological Diseases
The application of AI in neurological diseases mainly includes epilepsy, Alzheimer's disease, and Parkinson's disease, etc. AI can process and analyze the patient's image data and make statistical comparison with the normal population group, so as to calculate the size and position of metabolic abnormalities, and then, through cognitive technology, give the information of treatment plan and prediction of treatment effect. The cognitive technology can be used to give suggestions for treatment programs and predict the effect of treatment.
(5) Intelligent assisted diagnosis of cardiovascular disease
AI can assess vulnerable plaques of coronary arteries on the basis of chest CT data, using deep learning technology and image processing technology, and design specific algorithms to carry out intelligent assisted diagnosis of coronary artery disease and plan stent surgery placement programs. It can also intelligently diagnose aortic disease types, aortic aneurysms and other complex diseases.
3. Intelligent outlining of target area
At present, radiotherapy is one of the main treatment modalities for tumor patients, and the correct positioning and precise outlining of diseased organs is the foundation and key technology of radiotherapy. Therefore, the organs and tumor locations on the CT images need to be marked first before radiotherapy, which usually takes doctors 3 to 5 hours according to the traditional method.
The efficiency can be greatly improved by applying AI technology, and the high accuracy of AI intelligent target area sketching can largely avoid ineffective treatment caused by inaccurate target area sketching. Currently, AI+target sketching has been successfully applied to lung cancer, breast cancer, nasopharyngeal cancer, liver cancer, prostate cancer, esophageal cancer and skin cancer.
4. Intelligent judgment of pathology slides
Judgment of pathology slides is a complex task, which often requires doctors to have rich professional knowledge and experience, and even for doctors with professional experience, it is easy to ignore the details that are not easy to notice, thus leading to diagnostic bias.
The introduction of artificial intelligence into the study of pathology slides, by learning the characteristics of the cellular level of the slides, and constantly improving the knowledge system of pathological diagnosis is the best way to solve the problem of reading efficiency and diagnostic accuracy.