文章基本信息

标题：Classification Algorithms for the Detection of the Primary Tumor Based on Microscopic Images of Bone Metastases
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作者：Slađan Kantar ; Aleksandar Pluškoski ; Igor Ciganovic 等
期刊名称：Computer Science & Information Technology
电子版ISSN：2231-5403
出版年度：2017
卷号：7
期号：8
页码：41-56
DOI：10.5121/csit.2017.70804
出版社：Academy & Industry Research Collaboration Center (AIRCC)
摘要：This paper presents the analysis of techniques for microscopic images in order to find a primarytumor based on the of bone metastases. Was done algorithmic classification into three groups,kidney, lung and breast. In order to speed up the treatment of the patient and easier for doctorsand therefore reduce room for human error. Digital microscope images of bone metastaseswere analyzed, for which it is known that the primary tumor is in one of the three humanorgans: kidney, lung or breast. We tested several solutions for classification, were tested twomethods of image analysis. Multifractal analysis and convolutional neural network. Bothmethods were tested with and without preprocessing image. Results of multifractal analysiswere then classified using different algorithms. Images were processed using CLAHE and kmeansalgorithm. At the end, the results obtained using a variety of techniques are presented.
关键词：Cancer classification; Microscopic images; Image preprocessing; Multifractal analysis;Classification algorithms