De-enhancing the dynamic contrast-enhanced breast MRI for robust registration.
Dynamic enhancement causes serious problems for registration of contrast enhanced breast MRI, due to variable uptakes of agent on different tissues or even same tissues in the breast. We present an iterative optimization algorithm to de-enhance the dynamic contrast-enhanced breast MRI and then register them for avoiding the effects of enhancement on image registration. In particular, the spatially varying enhancements are modeled by a Markov Random Field, and estimated by a locally smooth function with boundaries using a graph cut algorithm. The de-enhanced images are then registered by conventional B-spline based registration algorithm. These two steps benefit from each other and are repeated until the results converge. Experimental results show that our two-step registration algorithm performs much better than conventional mutual information based registration algorithm. Also, the effects of tumor shrinking in the conventional registration algorithms can be effectively avoided by our registration algorithm.
Zheng
Yuanjie
Y
Department of Radiology, University of Pennsylvania, Philadelphia, PA 19104, USA.
Yu
Jingyi
J
Kambhamettu
Chandra
C
Englander
Sarah
S
Schnall
Mitchell D
MD
Shen
Dinggang
D
D000465:Algorithms; D001185:Artificial Intelligence; D001940:Breast / Q000473:pathology*; D001943:Breast Neoplasms / Q000175:diagnosis*; D003287:Contrast Media; D005260:Female; D006801:Humans; D007089:Image Enhancement / Q000379:methods*; D007090:Image Interpretation, Computer-Assisted / Q000379:methods; D021621:Imaging, Three-Dimensional / Q000379:methods; D008279:Magnetic Resonance Imaging / Q000379:methods*; D010363:Pattern Recognition, Automated / Q000379:methods*; D015203:Reproducibility of Results; D012680:Sensitivity and Specificity; D013382:Subtraction Technique
D003287:Contrast Media