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 lO2 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.
翻译:本文探讨了红外线成像(IR)在乳腺癌检测中的潜在贡献,比较了使用某些算法检测恶性乳腺状况的结果,如支持矢量机(SVM)在应用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,并推广使用高分辨率IR成像的研究,我们认为使用由经过可靠培训的乳房医生修改的公共数据库至关重要,我们在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(54正常和48及一些发现)的LO2IR单乳房图像,这些图像是从联邦伯南布科大学医院收集的,我们采用了提出最佳结果并达到61.7%的精确度的工作作者提出的相同特征,以及使用Squenal Minminal最佳化(SMO)分类仪的0.24的Youden指数。