scholarly journals Intelligent Segmentation and Recognition Method of Breast Cancer Based on Digital Image Processing Technology

2021 ◽  
Vol 2021 ◽  
pp. 1-9
Author(s):  
Xiaochen Tang ◽  
Yunbo An ◽  
Congshan Li

With the development of digital image technology, judging diseases by medical image plays an important role in medical diagnosis. Mammography is the most effective imaging examination method for breast cancer at present. Intelligent segmentation and identification of breast cancer images and judging their size and classification by digital image processing technology can promote the development of clinical medicine. This paper introduces the preprocessing technology of breast cancer pathological image and medical image recognition technology of breast cancer. In order to improve the segmentation accuracy of image processing and optimize, the segmentation recognition ability in digital mammography was improved. Based on the technical basis of pathological image analysis of breast cancer, the architecture of intelligent segmentation and recognition system for breast cancer was constructed, and each functional module of intelligent system was introduced in detail. Based on digital image processing technology, filtering technology is used to reduce dryness and improve the clarity of the image. Public datasets INBreast and DDSM-BCRP were used to verify system’s performance, and it was tested on the breast cancer image test set. The experiment shows that the comprehensive performance of the intelligent segmentation and recognition system can realize the segmentation and recognition of breast cancer and has higher accuracy and interpretability, which is helpful to improve the diagnosis of doctors.

2021 ◽  
Author(s):  
Zhe Yin ◽  
Zhijie Shan

<p>Rock outcrops are common features of the karst ecosystem The bare rock rate is an important indicator for rocky desertification grades classification, and its accurate extraction can benefit for understanding the distribution characteristics of rock outcrops in desertification areas and the classification of rocky desertification grades. In order to explore the distribution pattern of surface bare rocks in the typical geomorphic environment of the Karst gabin basin, the Mengzi gabin basin was carried out as the research site. The combination of UAV shooting images and digital image processing technology were used, the characteristics of bare rock rate on the karst fault basin after vegetation restoration were shaped. Our results showed that digital image processing technology can be used for extraction of bare rock rate in Karst area, and the effective combination of UAV technology and digital image processing technology can quickly obtain bare rock rate data of typical landform in Karst gabin basins. After performing drone aerial photography on 26 typical landform information under different bare rock distribution conditions on the Mengzi gabin basin, the results of the image processing analysis showed that the bare rock rate is between 2.7%-28.9%. The research provide technical support for the assessment of the karst ecosystem degradation and the evaluation of the current status of rocky desertification in karst gabin basin</p>


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