Computer-aided diagnosis for early-stage breast cancer by using Wavelet Transform

Nan-Chyuan Tsai, Hong Wei Chen, Sheng Liang Hsu

研究成果: Article

26 引文 斯高帕斯(Scopus)

摘要

A high-sensitivity computer-aided diagnosis algorithm which can detect and quantify micro-calcifications for early-stage breast cancer is proposed in this research. The algorithm can be divided into two phases: image reconstruction and recognition on micro-calcification regions. For Phase I, the suspicious micro-calcification regions are separated from the normal tissues by wavelet layers and Renyi's information theory. The Morphology-Dilation and Majority Voting Rule are employed to reconstruct the scattered regions of suspicious micro-calcification. For Phase II, total 49 descriptors which mainly include shape inertia, compactness, eccentricity and grey-level co-occurrence matrix are introduced to define the characteristics of the suspicious micro-calcification clusters. In order to reduce the computation load, Principal Component Analysis (PCA) is used to transform these descriptors to a compact but efficient vector expression by linear combination method. The performance of proposed diagnosis algorithm is verified by intensive experiments upon realistic clinic patients. The efficacy of Back-propagation Neural Network classifier exhibits its superiority in terms of high true positive rate (TP rate) and low false positive rate (FP rate), in comparison to Bayes classifier.

原文English
頁(從 - 到)1-8
頁數8
期刊Computerized Medical Imaging and Graphics
35
發行號1
DOIs
出版狀態Published - 2011 一月 1

All Science Journal Classification (ASJC) codes

  • Radiological and Ultrasound Technology
  • Radiology Nuclear Medicine and imaging
  • Computer Vision and Pattern Recognition
  • Health Informatics
  • Computer Graphics and Computer-Aided Design

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