Classification of Breast Lesions using Histopathology Images and Neural Network

Authors(4) :-Sonali Nandish Manoli, Anand Raj Ulle, N.M Nandini, T.S Rekha

Breast cancer occurs when a malignant tumor originates in the breast. As breast tumors mature, they may metastasize to other parts of the body. However, it is important to keep in mind that, if identified and properly treated while still in its early stages, breast cancer can be cured [1].To achieve the above target it is necessary to develop a computer-aided Diagnosis system which helps in better diagnosis of the condition. It can be achieved by using Digital Image Processing techniques to obtain the regions of interest which show extra growth in the breast. So, a system is developed to classify lesions into Benign (non-cancerous) and Malignant (cancerous) condition. To classify the lesions the stain-color is considered as the important criteria to remove the noise from the digital images. To achieve this, initially the region of interest is obtained using k-means clustering and shape features are extracted. The binary image obtained as the result is further given as an input to obtain the regions of interest using the marker-controlled watershed image segmentation approach. The result of the hybrid approach gives us texture features. Further, the combination of these features is considered for classification. The performance measures namely accuracy , sensitivity , specificity , precision of the system are calculated for Na´ve Bayes , Support Vector Machine , Adaptive Boosting , Classification Tree, Random Forest and Feed-Forward Neural Network Classifier.

Authors and Affiliations

Sonali Nandish Manoli
Department of Information Science and Engineering, JSS Science &Technological University, Mysore, Karnataka, India
Anand Raj Ulle
Department of Information Science and Engineering, JSS Science &Technological University, Mysore, Karnataka, India
N.M Nandini
Department of Pathology, JSS Medical College affiliated to JSS University, Mysore, Karnataka, India
T.S Rekha
Department of Pathology, JSS Medical College affiliated to JSS University, Mysore, Karnataka, India

Histopathology, Digital Images, Stain-Color Normalization, Stain-Color Deconvolution, Image Sharpening, K-means, Shape Features, Foreground Markers, Background Markers, Marker-Controlled Watershed, Texture Features, Classifier, Feed-Forward Neural Network.

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Publication Details

Published in : Volume 3 | Issue 6 | July-August 2018
Date of Publication : 2018-08-30
License:  This work is licensed under a Creative Commons Attribution 4.0 International License.
Page(s) : 641-648
Manuscript Number : CSEIT1836130
Publisher : Technoscience Academy

ISSN : 2456-3307

Cite This Article :

Sonali Nandish Manoli, Anand Raj Ulle, N.M Nandini, T.S Rekha, "Classification of Breast Lesions using Histopathology Images and Neural Network", International Journal of Scientific Research in Computer Science, Engineering and Information Technology (IJSRCSEIT), ISSN : 2456-3307, Volume 3, Issue 6, pp.641-648, July-August-2018.
Journal URL : http://ijsrcseit.com/CSEIT1836130

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