Abstract #1115

Combination of pharmacokinetic parameters and texture features of DCE-MRI for predicting preoperative classification of breast cancer

Xia Wu^1,2,3, Zhou Liu⁴, Meng Wang⁴, Zhe Ren^1,2,3, Ya Ren⁴, Jie Wen⁴, Qian Yang⁴, Xin Liu^1,2,3, Hairong Zheng^1,2,3, and Na Zhang^1,2,3

¹Paul C. Lauterbur Research Center for Biomedical Imaging, Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences Synopsis, ShenZhen, China, ²Key Laboratory for Magnetic Resonance and Multimodality Imaging of Guangdong Province, Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences, ShenZhen, China, ³CAS key laboratory of health informatics, Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences, ShenZhen, China, ⁴Department of Radiology, National Cancer Center/Cancer Hospital and Shenzhen Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, ShenZhen, China

We have achieved preoperative classification of breast cancer by combination of pharmacokinetic parameters and texture features using machine learning. Using the information available in each feature space, an appropriate feature fusion method using information from the two feature spaces can help the classification process and improve diagnosis accuracy. Among them, SVM and KNN have better performance.

How to access this content:

For one year after publication, abstracts and videos are only open to registrants of this annual meeting. Registrants should use their existing login information. Non-registrant access can be purchased via the ISMRM E-Library.

After one year, current ISMRM & ISMRT members get free access to both the abstracts and videos. Non-members and non-registrants must purchase access via the ISMRM E-Library.

After two years, the meeting proceedings (abstracts) are opened to the public and require no login information. Videos remain behind password for access by members, registrants and E-Library customers.

Click here for more information on becoming a member.