Evaluation of radiological features for breast tumour classification in clinical screening with machine learning methods
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摘要
Objective:In this work, methods utilizing supervised and unsupervised machine learning are applied to analyze radiologically derived morphological and calculated kinetic tumour features. The features are extracted from dynamic contrast enhanced magnetic resonance imaging (DCE-MRI) time-course data.
论文关键词：Breast cancer,Magnetic resonance imaging,Clinical screening,Computer aided diagnosis,Machine learning,Artificial neural networks,Support vector machine (SVM),Decision trees
论文评审过程：Received 14 February 2004, Revised 2 September 2004, Accepted 27 September 2004, Available online 16 December 2004.
论文官网地址：https://doi.org/10.1016/j.artmed.2004.09.001
