## 2 Research Status and Development Trends for Computer Aided Detection and Diagnosis of MRI
### Image Feature Extraction of Breast Tumours and Pattern Classification of Breast Fibrous Glands
However, most current state-of-the-art techniques generally extract the features globally using kernels. These global features are the most used for image classification. It must be noted, however, that features extracted for classification do not always carry the same importance. Some features may even contribute to a degradation of the classifier performance. Inappropriate prioritization of some features can increase the classifier load as well as increase the model complexity. In contrast successful prioritization has the additional benefit of reducing computational time. For an in-depth discussion on feature extraction of breast tumours, the reader is referred to [9]. To improve the detection efficiency of breast tumours and reduce the cost of detection, BI-RADS emphasises the importance of observing the breast parenchyma, fibrous gland and background parenchymal enhancement in the structured MRI [10]. In the improved 2013 version of BI-RADS, previous breast parenchymal background classification based on the percentage of fibrous gland tissue and fat was remodelled and sub-divided into more classes: a predominantly fatty tissue class, a scattered sparse tissue class and a heterogeneously dense or extremely dense tissue class [11]. [PERSON] and [PERSON] found that if FGT (Fibroglandular tissue) is dense, then the possibility of breast cancer developing is higher [2,3]. It has been found that women with a glandular tissue density of 75% or higher had an increased risk of breast cancer compared to women with a glandular tissue density of less than 10% in mammograms. Further, women with high breast density and proliferative benign breast disease have a high risk of breast cancer in the future, while women with low breast density have a low risk even if they have benign proliferative diseases. Background parenchymal enhancement (BPE) is the normal manifestation of enhanced fibrous gland tissue during DCE-MRI examination. Based on the enhancement of the image volume and the degree of FGT on the fat-suppressed sequences T1-weighted, BPE is also further divided into an almost no enhancement type, slight enhancement type, moderate enhancement type and obvious enhancement type. Studies have shown that the incidence of breast cancer increases with the increase of BPE [4]. In addition, [PERSON] et al. [5] pointed out that, at multiple monitoring points of neo-adjuvant chemotherapy in patients with unilateral invasive breast cancer, the quantitative BPE of contralateral normal breast showed a continuous downward trend, similar to the change in tumour size during neo-adjuvant chemotherapy. Their work showed that there was a predictive aspect of BPE on the therapeutic effect of a treatment. Furthermore, it also showcased that an early reduction of bacterial artificial chromosome (BAC) in neo-adjuvant chemotherapy was positively correlated with pathological complete remission, especially in patients with hormone receptor-negative status [5]. Therefore, breast fibrous gland state was introduced as a supplementary feature for breast tumour detection, establishing the evaluation of BPE as a useful biological indicator of breast cancer proliferation [12, 13, 14].