Application of Deep Learning Algorithm in Cervical Cancer MRI Image Segmentation Based on Wireless Sensor

• Published in: Journal of medical systems Vol. 43; no. 6; pp. 156 - 7
• Main Authors: Liang, Peng, Sun, Guijun, Wei, Sirong
• Format: Journal Article
• Language: English
• Published: New York Springer US 01.06.2019; Springer Nature B.V
• Subjects: Algorithms; Cancer; Cervical cancer; Cervix; Data processing; Deep Learning; Early Detection of Cancer; Female; Health Informatics; Health Sciences; Humans; Image & Signal Processing; Image processing; Image Processing, Computer-Assisted - methods; Image segmentation; Information processing; Magnetic resonance imaging; Magnetic Resonance Imaging - methods; Medical imaging; Medical technology; Medicine; Medicine & Public Health; Statistics for Life Sciences; Technology; Traditional medicine; Uterine Cervical Neoplasms - diagnostic imaging; Uterine Cervical Neoplasms - pathology; Wearable Computing Techniques for Smart Health; Wireless networks; Wireless Technology; Wireless network; MRI image segmentation technology; Cervical cancer; Degree learning algorithm
• ISSN: 0148-5598; 1573-689X; 1573-689X
• DOI: 10.1007/s10916-019-1284-7

With the development of medical technology in China, new difficulties are gradually emerging in traditional medicine. Cervical cancer MRI image segmentation technology based on wireless network is one of the most famous means. But the traditional technology is not strong enough for information processing and analysis. Manual data processing alone may lead to errors in data processing and so on. Therefore, this research was aimed at the MRI image segmentation technology of cervical cancer based on wireless network, using depth learning algorithm to calculate and analyze. Through this kind of wireless network and the computer algorithm form, the data processing ability can be improved and increase the data processing ability be increased.