Extracellular volume fraction mapping (ECV Map) can provide quantitative measurements of myocardial tissue with amyloid deposition and myocardial edema. ECV measurements have been shown to correlate well with myocardial fibrosis. Pixel-wise ECV Maps are calculated from acquired precontrast and postcontrast T1 Maps calibrated by blood hematocrit. The maps are acquired with ECG triggering and breath holding. However, ECV measurement is not accurate when heart motion occurs because of inconsistent and inadequate breath holding during image acquisition. We present an application of motion-correction algorithm for ECV Maps in cardiac MRI. Our proposed method is based on aligning the position of the heart between precontrast and postcontrast T1 Maps before calculating the ECV Map. The problem with this registration is spatial displacement of the myocardium because of different diaphragm positions. We have developed an automatic approach to detect the displacement before and after contrast injection, and the ECV Map is measured with correction of the myocardium position considering the displacement. We confirmed that our proposed method improves the accuracy of the ECV Map regardless of the size of displacement.