scholarly journals Round breast calcification

2019 ◽  
Author(s):  
Francis Deng
Keyword(s):  
2018 ◽  
Vol 7 (2.16) ◽  
pp. 29
Author(s):  
Gaurav Makwana ◽  
Lalita Gupta

Breast cancer is most common disease in women of all ages. To identify & confirm the state of tumor in breast cancer diagnosis, patients are undergo biopsy number of times to identify malignancy. Early detection of cancer can save the patient. In this paper a novel approach for automatic segmentation & classification of breast calcification is proposed. The diagnostic test technique for detection of breast condition is very costly & requires human expertise whereas proposed method can help in automatically identifying the disease by comparing the data with the standard database. In proposed method a database has been created to define various stage of breast calcification & testing images are pre-processed to resize, enhance & filtered to remove background noise. Clustering is performed by using k-means clustering algorithm. GLCM is used to extract out statistical feature like area, mean, variance, standard deviation, homogeneity, skewness etc. to classify the state of tumor. SVM classifier is used for the classification using extracted feature. 


2017 ◽  
Vol 78 (9) ◽  
pp. 1999-2004 ◽  
Author(s):  
Ayana IKARI ◽  
Satoru TANAKA ◽  
Toshikatsu NITTA ◽  
Hiroyuki TANISHIMA ◽  
Tetsuya HORIUCHI ◽  
...  

Author(s):  
Vaia Koukou ◽  
Niki Martini ◽  
George Fountos ◽  
Christos Michail ◽  
Panagiota Sotiropoulou ◽  
...  

2012 ◽  
Vol 20 (1) ◽  
pp. 107-120 ◽  
Author(s):  
Jiangkun Liu ◽  
Ruola Ning ◽  
Weixing Cai ◽  
Ricardo Betancourt Benitez

2004 ◽  
Vol 10 (4) ◽  
pp. 355-358 ◽  
Author(s):  
Alissa M. Connors ◽  
William E. Svensson ◽  
Sami Shousha
Keyword(s):  

1988 ◽  
Vol 39 (3) ◽  
pp. 257-261 ◽  
Author(s):  
H.E. Fewins ◽  
G.H. Whitehouse ◽  
S.J. Leinster

2008 ◽  
Vol 35 (6Part24) ◽  
pp. 2941-2941
Author(s):  
M Kallergi ◽  
J Heine ◽  
A Vourtsi

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