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Decrease in False Assumption for Detection Using Digital Mammography
Published in Springer India
Volume: 411
Pages: 325 - 333
Our research work elaborated in the design and construction of a method that bring sustenance for a reduction in false assumptions during the detection of breast cancer. Our key drive of this research work was to elude the false assumptions in the detection practice in a cost effective manner. We proposed a unique method to decrease false assumption in breast cancer detection cases and split this method in three different modules as preprocessing, formation of homogeneous blocks and color quantization. The preprocessing convoluted in eradicating the extraneous slices. The formation homogeneous blocks sub-method was to do segmentation of the image. The task of the third sub-method (i.e. color quantization) was to break the colors amid different regions. © Springer India 2016.
About the journal
JournalData powered by TypesetAdvances in Intelligent Systems and Computing Computational Intelligence in Data Mining—Volume 2
PublisherData powered by TypesetSpringer India
Open Access0