In modern photolithography, model based optical proximity correction (MBOPC) has evolved from a nice-to-have feature to a must-have feature and has been widely adopted to improve the process throughput. The purpose of MBOPC is to adjust the designed pattern on the photomask to introduce mask perturbations such that the layout printed on the wafer is as close as possible to the drawn layout. In regular MBOPC process, the polygons are dissected into segments and corrections are conducted segment by segment. While it is relatively easy and straightforward to find the optimal segment size for most one-dimensional features, it is hard for many two-dimensional features, especially line-end areas. By solving a few segments around line-end areas together, multisegment solver (MSS) showed a good contour match. However, this method is expensive on model calculation, as there is more than one segment size to be optimized and a large number of searching iterations is needed, which makes its runtime sensitive to the number kernels retained in OPC model. In this study, a novel method of computing the signal change in the MBOPC process with MSS is proposed by analyzing the optical kernel sensitivity to mask perturbation. The experimental results show that while the correction accuracy of the MBOPC process with a simplified model is maintained, the MBOPC runtime is reduced by 37%.