Content-based visual information retrieval (CBVIR) or content-based image retrieval (CBIR)
has been one on the most vivid research areas in the field of computer vision over the last …

The aim of this paper is to review existing approaches to the automatic detection and
segmentation of masses in mammographic images, highlighting the key-points and main …

Breast cancer continues to be a significant public health problem in the world. Early
detection is the key for improving breast cancer prognosis. Mammography has been one of …

A new method of feature extraction, based on feature fusion, is proposed in this paper
according to the idea of canonical correlation analysis (CCA). At first, the theory framework …

The American Cancer Society (ACS) recommends women aged 40 and above to have a
mammogram every year and calls it a gold standard for breast cancer detection. Early …

A new strategy of parallel feature fusion is introduced in this paper. A complex vector is first
used to represent the parallel combined features. Then, the traditional linear projection …

For any pattern classification task, an increase in data size, number of classes, dimension of
the feature space, and interclass separability affect the performance of any classifier. A …

摘! 要! 利用典型相关分析的思想& 提出了一种基于特征级融合的组合特征抽取新方法9 首先&
探讨了将典型分析用于模式识别的理论构架& 给出了其合理的描述9 即先抽取同一模式的两组 …

Purpose Breast cancer computer-aided diagnosis (CADx) may utilize image descriptors,
demographics, clinical observations, or a combination. CADx performance was compared …

In this paper, we propose the discriminative multiple canonical correlation analysis
(DMCCA) for multimodal information analysis and fusion. DMCCA is capable of extracting …