New motion correction models for automatic identification of renal transplant rejection.
Acute rejection is the most common reason of graft failure after kidney transplantation and early detection is crucial to survive the transplanted kidney function. In this paper, we introduce a new approach for the automatic classification of normal and acute rejection transplants from Dynamic Contrast Enhanced Magnetic Resonance Imaging (DCE-MRI). The proposed algorithm consists of three main steps; the first step isolates the kidney from the surrounding anatomical structures. In the second step, new motion correction models are employed to account for both the global and local motion of the kidney due to patient moving and breathing. Finally, the perfusion curves that show the transportation of the contrast agent into the tissue are obtained from the kidney and used in the classification of normal and acute rejection transplants.
Bioengineering Department, University of Louisville, Louisville, KY, USA.
Ayman
A
El-Baz
Georgy
G
Gimel'farb
Mohamed A
MA
El-Ghar
D000465:Algorithms; D016477:Artifacts; D001185:Artificial Intelligence; D003198:Computer Simulation; D003287:Contrast Media; D038524:Diffusion Magnetic Resonance Imaging / Q000379:methods*; D019786:Gadolinium DTPA; D006084:Graft Rejection / Q000175:diagnosis* / Q000209:etiology; D006801:Humans; D007089:Image Enhancement / Q000379:methods*; D007090:Image Interpretation, Computer-Assisted / Q000379:methods; D021621:Imaging, Three-Dimensional / Q000379:methods; D016030:Kidney Transplantation / Q000009:adverse effects / Q000473:pathology*; D008954:Models, Biological; D009068:Movement; D010363:Pattern Recognition, Automated / Q000379:methods; D015203:Reproducibility of Results; D012680:Sensitivity and Specificity
D003287:Contrast Media; D019786:Gadolinium DTPA