Welcome to Francis Academic Press

Frontiers in Medical Science Research, 2022, 4(1); doi: 10.25236/FMSR.2022.040104.

Research and Practice on the Integration and Development of Artificial Intelligence and Medical Image

Author(s)

Bing Li

Corresponding Author:
Bing Li
Affiliation(s)

Nanning Saimao Information Technology Co., Ltd., Nanning, China

Abstract

The innovative development of medicine is synchronized with the innovative application of technology. Also, artificial intelligence technology brings new breakthroughs for medical research in the era of artificial intelligence. In particular, artificial intelligence technology has achieved conspicuous application expectations in medical image, realized the integration of intelligent technology and medical image research, and provided assistance for tumor diagnosis and cardiovascular disease diagnosis. As a computer technology operating in human thinking mode, artificial intelligence technology realized the imitation of human brain thinking process and overcame the subjective bias of human brain thinking, which is of great application value. The integration of artificial intelligence technology and medical image is an inevitable trend and the dawn of medical progress. In the new era, it is valuable to increase the research on the integration of artificial intelligence technology and medicine in order to realize the new development of medicine supported by artificial intelligence technology. In this context, this work mainly discussed the integration and development of artificial intelligence technology and medical image and analyzed the application of artificial intelligence technology in medical image on the basis of clarifying the current situation of medical application of artificial intelligence technology.

Keywords

Artificial intelligence, Medical image, Integration and development

Cite This Paper

Bing Li. Research and Practice on the Integration and Development of Artificial Intelligence and Medical Image. Frontiers in Medical Science Research (2022) Vol. 4, Issue 1: 19-22. https://doi.org/10.25236/FMSR.2022.040104.

References

[1] Stoitsis, J., Valavanis, I., Mougiakakou, S. G., Golemati, S., Nikita, A., & Nikita, K. S. (2006). Computer aided diagnosis based on medical image processing and artificial intelligence methods. Nuclear Instruments and Methods in Physics Research Section A: Accelerators, Spectrometers, Detectors and Associated Equipment, 569(2), 591-595.

[2] Fourcade, A., & Khonsari, R. H. (2019). Deep learning in medical image analysis: A third eye for doctors. Journal of stomatology, oral and maxillofacial surgery, 120(4), 279-288.

[3] Shi, F., Wang, J., Shi, J., Wu, Z., Wang, Q., Tang, Z. & Shen, D. (2020). Review of artificial intelligence techniques in imaging data acquisition, segmentation, and diagnosis for COVID-19. IEEE reviews in biomedical engineering, 14, 4-15.

[4] Langlotz, C. P., Allen, B., Erickson, B. J., Kalpathy-Cramer, J., Bigelow, K., Cook, T. S. & Kandarpa, K. (2019). A roadmap for foundational research on artificial intelligence in medical imaging: from the 2018 NIH/RSNA/ACR/The Academy Workshop. Radiology, 291(3), 781-791.

[5] Goldenberg, S. L., Nir, G., & Salcudean, S. E. (2019). A new era: artificial intelligence and machine learning in prostate cancer. Nature Reviews Urology, 16(7), 391-403.