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

Yuxiang Zhou, Jing Qin, Guo Bin, Hanwei Chen, Shiting Feng, Tianfu Wang, Bingsheng Huang

Research output: Journal article publicationReview articleAcademic researchpeer-review

2 Citations (Scopus)


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.

Original languageEnglish
Pages (from-to)794-800
Number of pages7
JournalShengwu Yixue Gongchengxue Zazhi/Journal of Biomedical Engineering
Issue number4
Publication statusPublished - 1 Aug 2016
Externally publishedYes


  • Computer-aided diagnosis
  • Dynamic contrast-enhanced magnetic resonance imaging
  • Malignant tumor

ASJC Scopus subject areas

  • Medicine(all)

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