Review Article
Open Access

The application of mammography imaging in the diagnosis and prediction of breast diseases

Siyan Liu
Siyan Liu
School of Health Sciences and Engineering, University of Shanghai for Science and Technology, Shanghai 200093, China.
,
Guihua Wu
Guihua Wu
Department of Sonography, People's Hospital Affiliated to Shandong First Medical University, Jinan 271100, Shandong, China.
,
Changjiang Zhou
Changjiang Zhou
390585866@ qq.com
Department of Sonography, People's Hospital Affiliated to Shandong First Medical University, Jinan 271100, Shandong, China.
,
Shiju Yan
Shiju Yan
yanshiju@usst.edu.cn
School of Health Sciences and Engineering, University of Shanghai for Science and Technology, Shanghai 200093, China.
,
Haipo Cui
Haipo Cui
School of Health Sciences and Engineering, University of Shanghai for Science and Technology, Shanghai 200093, China.
Address correspondence to
Article notes
Highlights
Changjiang Zhou, Department of Sonography, People's Hospital Affiliated to Shandong First Medical University, Changshao North Road, Laiwu District, Jinan 271100, China. E-mail: 390585866@ qq.com/jnsrmyybgs@jn.shandong.cn. Shiju Yan, School of Health Science and Engineering, University of Shanghai for Science and Technology, No.516 Jungong Road, Yangpu District, Shanghai 200093, China. Tel: 18217617984. E-mail: yanshiju@usst.edu.cn.

Received September 22, 2023; Accepted December 6, 2023; Published March 31, 2024

Computer-assisted detection, diagnosis, and prediction systems have played an effective role in diagnosing and treating female breast diseases and monitoring the course of disease. Especially in mammography imaging, they provide key support for the early diagnosis of breast cancer. This highlights the significance of modern technology in enhancing breast disease management and improving women's health.
Review Article
Open Access
The application of mammography imaging in the diagnosis and prediction of breast diseases
Siyan Liu
Siyan Liu
School of Health Sciences and Engineering, University of Shanghai for Science and Technology, Shanghai 200093, China.
,
Guihua Wu
Guihua Wu
Department of Sonography, People's Hospital Affiliated to Shandong First Medical University, Jinan 271100, Shandong, China.
,
Changjiang Zhou
Changjiang Zhou
390585866@ qq.com
Department of Sonography, People's Hospital Affiliated to Shandong First Medical University, Jinan 271100, Shandong, China.
,
Shiju Yan
Shiju Yan
yanshiju@usst.edu.cn
School of Health Sciences and Engineering, University of Shanghai for Science and Technology, Shanghai 200093, China.
,
Haipo Cui
Haipo Cui
School of Health Sciences and Engineering, University of Shanghai for Science and Technology, Shanghai 200093, China.
Address correspondence to
Changjiang Zhou, Department of Sonography, People's Hospital Affiliated to Shandong First Medical University, Changshao North Road, Laiwu District, Jinan 271100, China. E-mail: 390585866@ qq.com/jnsrmyybgs@jn.shandong.cn. Shiju Yan, School of Health Science and Engineering, University of Shanghai for Science and Technology, No.516 Jungong Road, Yangpu District, Shanghai 200093, China. Tel: 18217617984. E-mail: yanshiju@usst.edu.cn.
Article notes

Received September 22, 2023; Accepted December 6, 2023; Published March 31, 2024

Highlights
Computer-assisted detection, diagnosis, and prediction systems have played an effective role in diagnosing and treating female breast diseases and monitoring the course of disease. Especially in mammography imaging, they provide key support for the early diagnosis of breast cancer. This highlights the significance of modern technology in enhancing breast disease management and improving women's health.
2024 Mar;2(1):1-11
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Abstract

Breast diseases pose a significant threat to women's health, so early detection and treatment are extremely important. In this context, early disease identification has become crucial in the diagnosis and treatment of breast diseases. This paper begins by outlining the pivotal role of mammography in the early diagnosis of breast cancer, comparing the structural similarities and differences between normal and diseased breast tissues. This comparison underscores the primary role of mammography in the diagnosis and treatment of breast diseases. Additionally, our paper provides an overview of fundamental concepts related to breast cancer detection, diagnosis, and prediction systems. It delves into the latest research developments in auxiliary diagnostic detection, examination, and risk prediction systems associated with breast cancer. Our objective is to offer a comprehensive understanding of the role of computer-aided detection, diagnosis, and prediction systems in breast diseases, fostering further development and application. This work aims to explore and drive innovation in the field, enhance early detection rates of breast diseases, and guide readers towards novel directions, thus contributing to female healthcare management.

Keywords: Mammography, imaging, computer-aided diagnosis, deep learning, multi-modality
Progress in Medical Devices

ISSN: 2957-5478

Volume 2, Issue 1

March 2024

Pages: 1-43

PDF CITE Accesses: 7
Progress in Medical Devices
ISSN: 2957-5478
ZENTIME PUBLISHING CORPORATION LIMITED
On This Page
CITE
On This Page
Abstract