A prospective case study of high boost, high frequency emphasis and two-way diffusion filters on MR images of glioblastoma multiforme

Abstract

Glioblastoma multiforme (GBM) appears undifferentiated and non-enhancing on magnetic resonance (MR) imagery. As MRI does not offer adequate image quality to allow visual discrimination of the boundary between GBM focus and perifocal vasogenic edema, surgical and radiotherapy planning become difficult. The presence of noise in MR images influences the computation of radiation dosage and precludes the edge based segmentation schemes in automated software for radiation treatment planning. The performance of techniques meant for simultaneous denoising and sharpening, like high boost filters, high frequency emphasize filters and two-way anisotropic diffusion is sensitive to the selection of their operational parameters. Improper selection may cause overshoot and saturation artefacts or noisy grey level transitions can be left unsuppressed. This paper is a prospective case study of the performance of high boost filters, high frequency emphasize filters and two-way anisotropic diffusion on MR images of GBM, for their ability to suppress noise from homogeneous regions and to selectively sharpen the true morphological edges. An objective method for determining the optimum value of the operational parameters of these techniques is also demonstrated. Saturation Evaluation Index (SEI), Perceptual Sharpness Index (PSI), Edge Model based Blur Metric (EMBM), Sharpness of Ridges (SOR), Structural Similarity Index Metric (SSIM), Peak Signal to Noise Ratio (PSNR) and Noise Suppression Ratio (NSR) are the objective functions used. They account for overshoot and saturation artefacts, sharpness of the image, width of salient edges (haloes), susceptibility of edge quality to noise, feature preservation and degree of noise suppression. Two-way diffusion is found to be superior to others in all these respects. The SEI, PSI, EMBM, SOR, SSIM, PSNR and NSR exhibited by two-way diffusion are 0.0016±0.0012, 0.2049±0.0187, 0.0905±0.0408, 2.64×1012±1.6×1012, 0.9955±0.0024, 38.214±5.2145 and 0.3547±0.0069, respectively.