A Systematic Review on Breast Cancer Detection Using Deep Learning Techniques

被引:16
|
作者
Rautela, Kamakshi [1 ]
Kumar, Dinesh [1 ]
Kumar, Vijay [2 ]
机构
[1] Delhi Technol Univ, New Delhi, India
[2] Natl Inst Technol, Hamirpur, Himachal Prades, India
关键词
NEURAL-NETWORKS; THERMAL IMAGES; MAMMOGRAPHY; ULTRASOUND; CLASSIFICATION; DIAGNOSIS; DENSITY; ULTRASONOGRAPHY; TOMOSYNTHESIS; THERMOGRAPHY;
D O I
10.1007/s11831-022-09744-5
中图分类号
TP39 [计算机的应用];
学科分类号
081203 ; 0835 ;
摘要
Breast cancer is a common health problem in women, with one out of eight women dying from breast cancer. Many women ignore the need for breast cancer diagnosis as the treatment is not secure due to the exposure of radioactive rays. The breast cancer screening techniques suffer from non-invasive, unsafe radiations, and specificity of diagnosis of tumor in the breast. The deep learning techniques are widely used in medical imaging. This paper aims to provide a detailed survey dealing with the screening techniques for breast cancer with pros and cons. The applicability of deep learning techniques in breast cancer detection is studied. The performance measures and datasets for breast cancer are also investigated. The future research directions associated with breast cancer are studied. The primary aim is to provide a comprehensive study in this field and to help motivate the innovative researchers.
引用
收藏
页码:4599 / 4629
页数:31
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