Abstract: The non-rigid registration is slow due to large number of control points and the high cost of iterative strategy and the normalized mutual information(NMI).A parallel algorithm with a B-spline coefficient optimization is proposed to accelerate such registration.In this approach,the data parallel algorithm computes NMI and the task parallel algorithm,in which the data parallel algorithm is embedded,computes the gradient descent flow.Control points are restrained to be distributed on the targets according to the image local entropy for further reduction on computational cost.A balanced algorithm is presented to solve the computational imbalance problem caused by the uneven distribution of control points.Experiments showed that the use of the B-spline coefficient optimization can reduce about 50% coefficient computation.The introduced parallel algorithm can accelerate the non-rigid registration about 60⁸0 times compared to the serial version,about 6 times compared to the existing data parallel approaches.