HIGH ACCURACY BACK-RETREAT DIFFUSION-FUZZY CLUSTERING OF BREAST CANCER DATA FOR THE DETECTION OF MALIGNANCY

机译：高精度反向扩散扩散-模糊数据在乳腺癌检测中的应用

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A novel fuzzy clustering method has been proposed here for separating the breast cancer data, which operates with reasonable accuracy, allows flexibility in dataset and is modestly time consuming. This method can be applied to any type of cancer data set with some initial labels to obtain high accuracy result in the classification of unlabeled samples. Further, the curse of dimensionality is not an issue for the proposed scheme as it can be applied to data having any number of dimensions or attributes. The Dif-FUZZY unsupervised clustering algorithm is applied at the initial stage, giving an accuracy of 96.28% over Wisconsin Breast Cancer Dataset (WBCD); the result is further improved to 98.14% by using the proposed Back-Retreat algorithm. The formed clusters are estimated using three internal cluster validation indices and the performance of the method is evaluated using receiver operating characteristic (ROC) curves. The clustering algorithm is compared with Fuzzy C-Means (FCM) algorithm and the results are compared with different classifiers and clustering techniques.

机译：在此提出了一种新颖的模糊聚类方法，用于分离乳腺癌数据，该方法以合理的准确性运行，允许数据集具有灵活性并且非常耗时。该方法可以应用于带有一些初始标记的任何类型的癌症数据集，以获得未标记样本分类的高精度结果。此外，对于所提出的方案，维数诅咒不是问题，因为它可以应用于具有任意数量的维数或属性的数据。在初始阶段采用了Dif-FUZZY无监督聚类算法，与威斯康星州乳腺癌数据集（WBCD）相比，其准确性为96.28％；通过使用提出的后退算法，结果进一步提高到98.14％。使用三个内部群集验证指标估算形成的群集，并使用接收器工作特性（ROC）曲线评估方法的性能。将聚类算法与模糊C均值（FCM）算法进行比较，并将结果与不同的分类器和聚类技术进行比较。

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来源
《Proceedings of the 17th IASTED international conference on robotics applications ; Proceedings of the 11th IASTED international conference on biomedical engineering》|2014年|7-15|共9页
会议地点 Zurich(CH)
作者
Ashutosh Patri; Abhijit Nayak; Anup Anurag;
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作者单位

Department of Mining Engineering National Institute of Technology, Rourkela Rourkela, 769008, India;

Department of CSE National Institute of Technology, Rourkela Rourkela, 769008, India;

Department of Information Technology and Electrical Engineering ETH, Zurich Zurich, Switzerland;

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正文语种 eng
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关键词
DifFUZZY; Wisconsin Breast Cancer Data; Fuzzy C-Means; Breast Cancer; Fuzzy Clustering;

机译：DifFUZZY;威斯康星州乳腺癌数据；模糊C均值;乳腺癌;模糊聚类;

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1. Accuracy of breast cancer detection with full-field digital mammography and integral computer-aided detection correlated with breast density as assessed by a new automated volumetric breast density measurement system [J] . K Pinker, N Perry, S Milner, Breast Cancer Research . 2010,第Suppla3期

机译：通过新型自动容积式乳腺密度测量系统评估的全视野数字化乳腺X线摄影术以及与乳腺密度相关的整体计算机辅助检测对乳腺癌的准确性
2. 593 Accuracy of breast cancer detection with full-field digital mammography (FFDM) and integral computer-aided detection (CAD) correlated with breast density as assessed by a new automated volumetric breast density measurement system [J] . K.Pinker, S.Milner, D.Stephen, European Journal of Cancer Supplements . 2010,第3期

机译：593通过新型自动容积式乳腺密度测量系统评估的全视野数字化乳腺摄影（FFDM）和集成计算机辅助检测（CAD）与乳腺密度相关的乳腺癌检测准确性
3. Breast Imaging Reporting and Data Systems category 3 (probably benign) breast lesions detected on diagnostic breast ultrasound: The prevalence, outcome and malignancy detection rate in Zaria, Nigeria [J] . Sefiya A. Olarinoye-Akorede, Garba H. Yunusa, Halima Aliyu, SA Journal of Radiology . 2018,第2期

机译：诊断性乳房超声检查发现的乳房成像报告和数据系统第3类（可能是良性）乳腺病变：尼日利亚Zaria的患病率，预后和恶性检测率
4. HIGH ACCURACY BACK-RETREAT DIFFUSION-FUZZY CLUSTERING OF BREAST CANCER DATA FOR THE DETECTION OF MALIGNANCY [C] . Ashutosh Patri, Abhijit Nayak, Anup Anurag IASTED International Conference on Biomedical Engineering . 2014

机译：高精度后退撤退扩散 - 模糊聚类乳腺癌数据检测恶性肿瘤
5. Early breast cancer detection utilizing clustered electrode arrays in impedance imaging. [D] . Larson-Wiseman, Julie Lynn. 1998

机译：在阻抗成像中利用簇状电极阵列的早期乳腺癌检测。
6. Accuracy of breast cancer detection with full-field digital mammography and integral computer-aided detection correlated with breast density as assessed by a new automated volumetric breast density measurement system [O] . K Pinker, N Perry, S Milner, 2010

机译：通过新型自动容积式乳腺密度测量系统评估的全视野数字化乳腺X线摄影术和与乳腺密度相关的整体计算机辅助检测对乳腺癌的准确性
7. Accuracy of breast cancer detection with full-field digital mammography and integral computer-aided detection correlated with breast density as assessed by a new automated volumetric breast density measurement system [O] . Pinker, K, Perry, N, Milner, S, 2010

机译：通过新型自动容积式乳腺密度测量系统评估的全视野数字化乳腺X线摄影术以及与乳腺密度相关的整体计算机辅助检测对乳腺癌的准确性
8. Accuracy and Significance of Polymerase Chain Reaction Detection of Sentinel Node Metastases in Breast Cancer Patients [R] . Verbanac, K. M. , Tafra, L. 2000

机译：乳腺癌患者前哨淋巴结转移聚合酶链反应检测的准确性和意义

HIGH ACCURACY BACK-RETREAT DIFFUSION-FUZZY CLUSTERING OF BREAST CANCER DATA FOR THE DETECTION OF MALIGNANCY

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