Automatic region-of-interest segmentation and registration of dynamic contrast-enhanced images of colorectal tumors.
Dynamic contrast-enhanced (DCE) images can be acquired at multiple time points and multiple slice locations of a tumor. Image segmentation and registration are important preprocessing steps that can improve subsequent analysis of DCE images by kinetic modeling. An automatic system for region-of-interest segmentation and registration of DCE images is presented. Tissue segmentation is performed using a combination of thresholding and morphological operations, and further refined using shape information from consecutive images. The segmented regions are subsequently registered based on a mutual information method that accounts for possible tissue movement between slices. The proposed segmentation and registration methods are applied on actual DCE CT datasets to illustrate feasibility of practical implementation in the clinic.
Department of Neural and Biomedical Technology, Institute for Infocomm Research, A-star, 138632, Singapore.
Zujun
Z
Hou
Yue
Y
Wang
Choon Hua
CH
Thng
Quan-Sing
QS
Ng
Vicky
V
Goh
Tong
T
San Koh
D015179:Colorectal Neoplasms / Q000175:diagnosis*; D006801:Humans; D007089:Image Enhancement / Q000379:methods*; D008279:Magnetic Resonance Imaging / Q000379:methods*; D014055:Tomography, Emission-Computed / Q000379:methods*