scholarly journals Automated Classification of Breast Cancer Stroma Maturity From Histological Images

2017 ◽  
Vol 64 (10) ◽  
pp. 2344-2352 ◽  
Author(s):  
Sara Reis ◽  
Patrycja Gazinska ◽  
John H. Hipwell ◽  
Thomy Mertzanidou ◽  
Kalnisha Naidoo ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Automated Classification ◽  
Cancer Stroma ◽  
Histological Images

AUTOMATED CLASSIFICATION OF BREAST CARCINOMA CELL BASED ON IMAGE PROCESSING AND SUPPORT VECTOR MACHINE

2010 ◽  
Vol 22 (02) ◽  
pp. 127-135 ◽  
Author(s):  
Yung-Lung Kuo ◽  
Chien-Chuan Ko ◽  
Yueh-Min Lin ◽  
Yong-Min Chen
Keyword(s):  
Breast Cancer ◽  
Image Processing ◽  
Breast Cancer Diagnosis ◽  
Support Vector ◽  
Automated Classification ◽  
Processing Technologies ◽  
Major Health ◽  
Suitable Treatment ◽  
Breast Tissues

As breast cancer is a substantial threat to the lives of women, it has become a major health issue in the world over the past 50 years, and its incidence has increased in the recent years. Early diagnosis and suitable treatment is relatively important. In the process of breast screening, tissue biopsy is an important operation in determining the presence of breast cancer. It not only provides an accurate diagnosis of the disease but also determines the prognosis for breast cancer. The main goal of this study is to develop a breast cancer diagnosis system based on histopathology and a sequence of image-processing technologies to analyze H&E stained images of breast tissues. The proposed system can automatically detect the mitosis of nuclei and analyze the size and the shape of nuclei to evaluate the duct structure of the breast tissue. Moreover, it provides physicians quantitative prognosis and classification of tissue malignancy, which will improve the diagnostic accuracy and efficiency of the cancer.

Bilateral image subtraction features for multivariate automated classification of breast cancer risk

2014 ◽  
Author(s):  
Jose M. Celaya-Padilla ◽  
Juan Rodriguez-Rojas ◽  
Jorge I. Galván-Tejada ◽  
Antonio Martínez-Torteya ◽  
Victor Treviño ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Breast Cancer Risk ◽  
Cancer Risk ◽  
Automated Classification ◽  
Image Subtraction

Classification of breast cancer stroma as a tool for prognosis

2016 ◽  
Author(s):  
Sara Reis ◽  
Patrycja Gazinska ◽  
John H. Hipwell ◽  
Thomy Mertzanidou ◽  
Kalnisha Naidoo ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Cancer Stroma

scholarly journals Automated Classification of Breast Cancer Lesions for Digitised Mammograms via Computer-Aided Diagnosis System

2021 ◽  
Vol 8 (2) ◽  
pp. 892-902
Author(s):  
Saifullah Harith Suradi ◽  
Kamarul Amin Abdullah ◽  
Nor Ashidi Mat Isa
Keyword(s):  
Breast Cancer ◽  
Early Stage ◽  
Computer Aided Diagnosis ◽  
Image Processing Technique ◽  
Automated Classification ◽  
Cad System ◽  
Risk Of Death ◽  
Computer Aided ◽  
Aided Diagnosis

Women with breast cancer have a high risk of death. Digitised mammograms can be used to detect the early stage of breast cancer. However, digitised mammograms suffer low contrast appearances that may lead to misdiagnosis. This paper proposes a Computer-Aided Diagnosis (CAD) system of automated classification of breast cancer lesions using a modified image processing technique of Fuzzy Anisotropic Diffusion Histogram Equalization Contrast Adaptive Limited (FADHECAL) incorporated with Multilevel Otsu Thresholding on digitised mammograms. Four main blocks were used in this CAD system, namely; (i) Pre-processing and Enhancement block; (ii) Segmentation block; (iii) Region of Interests (ROIs) Extraction block; and (iv) Classification block. The CAD system was tested on 30 digitised mammograms retrieved from the Mini-Mammographic Image Analysis Society (MIAS) database with various degrees of severity and background tissues. The proposed CAD system showed a high accuracy of 96.67% for the detection of breast cancer lesions.

scholarly journals Automated classification of breast cancer morphology in histopathological images

2013 ◽  
Vol 8 (S1) ◽  
Author(s):  
Ville Ojansivu ◽  
Nina Linder ◽  
Esa Rahtu ◽  
Matti Pietikäinen ◽  
Mikael Lundin ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Automated Classification ◽  
Histopathological Images
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