In the field of medical application, artificial intelligence in medical image has made rapid progress in the aspect of industry, education and research. The research of artificial intelligence in medical imaging has produced good research and development situation and broad clinical application, and its the progress is exhibited in medical imaging equipment, image diagnosis and intelligent service. Academic exchanges are becoming increasingly active in exploring the academic progress and the development of artificial intelligence. Authoritative reports on the development of medical artificial intelligence have also been released. This issue focuses on a number of research articles on artificial intelligence in medical imaging, and shows the latest research findings on artificial intelligence and product application from different angles.
With the advent of the era of big data, artificial intelligence (AI) has emerged and rapidly developed in the field of medicine. The application of AI has huge potential in achieving prompt and accurate analysis of tumor information aggregation. Moreover, AI can reflect the distribution of imaging data in the real environment by using key technologies, such as automatic image segmentation and extraction. Accordingly, tumor diagnosis can change from subjective perception into objective science. Therefore, AI can assist doctors in efficiently and accurately diagnosing the presence of tumors and providing a solid foundation for the formulation of an appropriate diagnosis plan and informed judgment of the prognosis. This paper reviews the key AI technologies and their current applications in tumor diagnosis.
Artificial intelligence techniques have been widely applied in computer-aided diagnosis and disease mechanism studies for Alzheimer's disease (AD). Graph-based complex network analysis is one of the common data mining methods. A combination of complex network analysis technology and multimodal brain imaging information from neuroimaging methods, such as structural magnetic resonance imaging, functional magnetic resonance imaging, and positron emission computer imaging, could identify the abnormal changes of topological properties in brain structure and functional networks. This result provided new ideas on achieving early diagnosis and mechanism research in patients with AD. In this paper, the clinical application of complex network analysis method in structure and functional AD brain imaging was discussed, and its development trend was prospected.
Chest CT scan is the primary medical imaging method performed for the early screening and diagnosis of lung cancer. Deep-learning based computer aided diagnosis (CAD) system for chest CT imaging is helpful for detecting and classifying pulmonary nodules. Deep-learning techniques can improve the performance of CAD systems, especially in enhancing the accuracy of pulmonary nodule detection and reducing false-positive rates. This article reviewed the current application status of deep-learning models in CAD systems and the progress that has been achieved in using these systems for imaging pulmonary nodules.
With its application to various fields, artificial intelligence (AI) has become a research hotspot in today's society. The current shortage of personnel in the medical industry and the increased rated of medical diagnosis are crucial for AI application in the medical industry, especially in imaging diagnosis. AI-assisted diagnosis can improve the detection rate of diseases, provide effective diagnostic and treatment information for clinicians, and reduce the repetitive work of imaging physicians, thereby saving time for the research of difficult cases. In this paper, medical imaging AI is briefly introduced, and the latest and most influential research results at home and abroad are combined to explore the new development of medical imaging AI.
A high level of thyroid stimulating hormone (TSH) is required to stimulate sufficient radioiodine uptake for diagnostic imaging or therapy. The current methods for improving TSH level include thyroid hormone withdrawal and recombinant human TSH. However, acute hypothyroidism caused by thyroid hormone withdrawal (THW) before radioactive iodine remnant ablation/treatment or diagnostic scanning significantly influences lipid metabolism, renal function, cardiovascular and neuropsychiatric diseases, and quality of life. This review aimed to summarize these methods and their effect on the clinical and quality of life in patients with differentiated thyroid cancer.
With its rapid development, 3D printing technology has been widely used and achieved breakthrough progress in the medical field, especially in orthopedics, oral and maxillofacial surgery, organ transplantation, and other aspects. As a major cancer treatment, radiation therapy combined with 3D printing technology provides a powerful guarantee for the precise radiotherapy of tumors. This review presents the application and prospects of 3D printing technology in tumor radiotherapy.