Sang Ho Lee1, Jong Hyo Kim1,2, Jeong Yeon Cho2,3, Sang Youn Kim2,3, in Chan Song3, Hyeon Jin Kim3, Seung Hyup Kim2,3
in Radiation Applied Life Science,
DCE-MRI plays an essential role for cancer detection and characterization. The significant tissue parameters for lesion classification may take the form of synergistic subsets in the combinatorial space of multifarious kinetic features. In this study, we postulate that extending the individual analysis schemes of contrast enhancement kinetics to a hybrid analysis scheme and that selecting a meaningful feature subset from a combined feature pool may allow an improved performance for lesion classification. Based on this postulation, we presented a novel approach to prostate MRI computer-aided diagnosis (CAD) using multifarious kinetic parameters in DCE-MR images.