Breast cancer detection using image processing techniques

2002 ◽  
Author(s):  
T.C. Cahoon ◽  
M.A. Sutton ◽  
J.C. Bezdek
Keyword(s):  
Breast Cancer ◽  
Image Processing ◽  
Cancer Detection ◽  
Breast Cancer Detection ◽  
Image Processing Techniques ◽  
Processing Techniques

Breast Cancer Detection Using Image Processing and CNN Algorithm with K-Fold Cross-Validation

2021 ◽  
pp. 481-490
Author(s):  
Pruthvi Tilekar ◽  
Purnima Singh ◽  
Nagnath Aherwadi ◽  
Sagar Pande ◽  
Aditya Khamparia
Keyword(s):  
Breast Cancer ◽  
Image Processing ◽  
Cancer Detection ◽  
Cross Validation ◽  
Breast Cancer Detection ◽  
Fold Cross Validation

scholarly journals Breast histopathological image analysis using image processing techniques for diagnostic puposes: A methodological review

2021 ◽  
Vol 46 (1) ◽  
Author(s):  
R Rashmi ◽  
Keerthana Prasad ◽  
Chethana Babu K Udupa
Keyword(s):  
Breast Cancer ◽  
Image Processing ◽  
Medical Image ◽  
Human Life ◽  
Medical Image Processing ◽  
Histopathological Analysis ◽  
Image Processing Techniques ◽  
Computer Aided ◽  
Histopathological Images ◽  
Processing Techniques

AbstractBreast cancer in women is the second most common cancer worldwide. Early detection of breast cancer can reduce the risk of human life. Non-invasive techniques such as mammograms and ultrasound imaging are popularly used to detect the tumour. However, histopathological analysis is necessary to determine the malignancy of the tumour as it analyses the image at the cellular level. Manual analysis of these slides is time consuming, tedious, subjective and are susceptible to human errors. Also, at times the interpretation of these images are inconsistent between laboratories. Hence, a Computer-Aided Diagnostic system that can act as a decision support system is need of the hour. Moreover, recent developments in computational power and memory capacity led to the application of computer tools and medical image processing techniques to process and analyze breast cancer histopathological images. This review paper summarizes various traditional and deep learning based methods developed to analyze breast cancer histopathological images. Initially, the characteristics of breast cancer histopathological images are discussed. A detailed discussion on the various potential regions of interest is presented which is crucial for the development of Computer-Aided Diagnostic systems. We summarize the recent trends and choices made during the selection of medical image processing techniques. Finally, a detailed discussion on the various challenges involved in the analysis of BCHI is presented along with the future scope.

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