An Inventory of Breast Cancer: A Comprehensive Approach

被引:0
|
作者
Rajeshwar, V. V. N. Sai [1 ]
Dattatreya, V. [2 ]
机构
[1] ACE Engn Coll, Hyderabad, Telangana, India
[2] CVR Coll Engn, Hyderabad, Telangana, India
来源
SMART TRENDS IN COMPUTING AND COMMUNICATIONS, VOL 5, SMARTCOM 2024 | 2024年 / 949卷
关键词
Biomedical imaging; Machine learning; Deep learning; Medical imaging techniques; ANN; CNN; CLASSIFICATION;
D O I
10.1007/978-981-97-1313-4_20
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
Many pre-designed diagnostics are a part of identifying breast cancer and detecting lesions in the breast. The most effective and accurate screening modalities are Mammography, Ultrasound, Histopathology, and Magnetic Resonance Imaging (MRI). Some diagnostic methods use Computer-Aided Diagnostics (CAD) which determines the characteristics like color, form, texture, etc. When evaluating the performance of these ML models, many attributes like sensitivity, specificity, and accuracy will be considered. Receiver Operating Characteristics (ROC) graphs are sketched, and the sole purpose is to detect lesions in the breast. Malignant lesions are more invasive than benign lesions, which makes them more complicated to have a cure for. The motto of this corresponding enigmatic review was to gain substantial knowledge over various biomedical imaging and detection of breast cancers which are either benign or malignant. This paper suggests that there were many ML and DL models to determine breast cancer. To conclude the abstract, it's just the beginning of an in-depth journey to unveil the enigmatic diagnosis and prediction of breast cancer in women.
引用
收藏
页码:235 / 243
页数:9
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