title: Smoothing low-SNR molecular images via anisotropic median-diffusion.
abstract: We propose a new anisotropic diffusion filter for denoising low-signal-to-noise molecular images. This filter, which incorporates a median filter into the diffusion steps, is called an anisotropic median-diffusion filter. This hybrid filter achieved much better noise suppression with minimum edge blurring compared with the original anisotropic diffusion filter when it was tested on an image created based on a molecular image model. The universal quality index, proposed in this paper to measure the effectiveness of denoising, suggests that the anisotropic median-diffusion filter can retain adherence to the original image intensities and contrasts better than other filters. In addition, the performance of the filter is less sensitive to the selection of the image gradient threshold during diffusion, thus making automatic image denoising easier than with the original anisotropic diffusion filter. The anisotropic median-diffusion filter also achieved good denoising results on a piecewise-smooth natural image and real Raman molecular images.
authors.affiliation: Southwest Research Institute, Bioengineering Department, San Antonio, TX 78238-5166, USA. jling@swri.edu
authors.forename: Jian
authors.initials: J
authors.lastname: Ling
authors.forename: Alan C
authors.initials: AC
authors.lastname: Bovik
mesh_terms: D016880:Anisotropy; D001943:Breast Neoplasms / Q000000981:diagnostic imaging / Q000378:metabolism; D003198:Computer Simulation; D006801:Humans; D007089:Image Enhancement / Q000295:instrumentation / Q000379:methods*; D015233:Models, Statistical; D017239:Paclitaxel / Q000493:pharmacokinetics; D019047:Phantoms, Imaging; D011859:Radiography; D015203:Reproducibility of Results; D012680:Sensitivity and Specificity; D013059:Spectrum Analysis, Raman / Q000379:methods*; D013269:Stochastic Processes; D014018:Tissue Distribution
chemical_list: D017239:Paclitaxel