Whole Body Bone Scan Image Enhancement Algorithm Based on Laplacian and Adaptive Wiener Filter

Whole body bone imaging is a commonly used method for the diagnosis of bone metastases, but the images acquired by this method have some problems such as low resolution and poor contrast. In this paper, we propose an image enhancement algorithm for whole-body bone imaging based on Laplacian and adaptive Wiener filtering. To enhance the image’s contrast, we employ the Laplacian operator as a primary tool. The image is then processed by adaptive Wiener filtering to remove the noise amplified by the enhancement of the Laplacian operator. Experiments show that compared with the traditional Wiener filtering algorithm and the Laplacian operator, the proposed algorithm has better visual effect, and the enhanced image has higher peak signal-to-noise ratio. The results indicate that this approach effectively enhances image contrast while minimizing noise, which is conducive to the detection of lesions and reduce the problems of misdiagnosis, missed diagnosis and poor positioning.