Computer-aided diagnosis in dynamic contrast-enhanced magnetic resonance imaging of malignant tumor: a technical review of current research

Dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) may provide more information in diagnosis of malignant tumor compared to conventional magnetic resonance imaging (MRI). Nowadays, in order to utilize the information expediently and efficiently, many researchers are aiming at the development of computer-aided diagnosis (CAD) of malignant tumor based on DCE-MRI. In this review, we survey the research in this field and summarize the literature in four parts, i.e. (1) image preprocessing-noise reduction and image registration; (2) region of interests (ROI) segmentation; (3) feature extraction-exploring the image characteristics by analyzing the ROI quantitatively; (4) tumor lesion recognition and classification-distinguishing and classifying tumor lesions by learning the features of ROI. We summarize the application of CAD techniques of DCE-MRI for cancer diagnosis and, finally, give some discussion on how to improve the efficiency of CAD in the future research.