Acute ischemic stroke detection using wavelet based fusion of CT and MRI images

Abstract

Ischemic stroke is a condition which causes death of brain cells due to lack of blood supply and hence stops normal brain functioning. Due to finite academic studies of ischemic stroke detection, the success rate to detect stroke initial period is low using only CT image. Fusion of CT and DW-MRI images creates a composite image which provides more information than any of the input signals provided by a single modality alone. Diffusion Weighted MRI is widely used for the detection of acute ischemic stroke compared to CT. In this paper, image of both modalities i.e. CT and DW-MRI are used. The proposed algorithm consists of four phases. Pre-processing of both images is the first phase. Finding equivalent CT image of an input pathological MRI image for image fusion is done in second phase. Third phase includes image registration and fusion of CT and MRI image. Segmentation of stroke lesion from fused image is performed in fourth phase. The performance evaluation of fusion is computed using Peak Signal to Noise Ratio (PSNR) and Root Mean Square Error (RMSE).