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Comparing results of thermographic images based diagnosis for breast diseases

机译:基于热成像图像的乳腺疾病诊断结果比较

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This paper examines the potential contribution of infrared (IR) imaging in breast diseases detection. It compares obtained results using some algorithms for detection of malignant breast conditions such as Support Vector Machine (SVM) regarding the consistency of different approaches when applied to public data. Moreover, in order to avail the actual IR imaging's capability as a complement on clinical trials and to promote researches using high-resolution IR imaging we deemed the use of a public database revised by confidently trained breast physicians as essential. Only the static acquisition protocol is regarded in our work. We used 102 IR single breast images from the Pro Engenharia (PROENG) public database (54 normal and 48 with some finding). These images were collected from Universidade Federal de Pernambuco (UFPE) University?s Hospital. We employed the same features proposed by the authors of the work that presented the best results and achieved an accuracy of 61.7 % and Youden index of 0.24 using the Sequential Minimal Optimization (SMO) classifier.
机译:本文研究了红外(IR)成像在乳腺疾病检测中的潜在作用。它比较了使用某些检测恶性乳房疾病的算法(例如支持向量机(SVM))获得的结果,这些算法涉及应用于公共数据时不同方法的一致性。此外,为了利用实际的IR成像能力作为临床试验的补充,并促进使用高分辨率IR成像的研究,我们认为必须使用经过自信培训的乳房医师修订的公共数据库。在我们的工作中只考虑静态获取协议。我们使用了Pro Engenharia(PROENG)公共数据库中的102个IR单乳图像(54个正常图像和48个发现的图像)。这些图像是从伯南布哥联邦大学(UFPE)大学医院收集的。我们采用了由作者提出的相同功能,这些功能提出了最佳结果,使用顺序最小优化(SMO)分类器实现了61.7%的准确性和0.24的Youden指数。

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