Improving technetium-99m methylene diphosphonate bone scan images using histogram specification technique

Abstract

In this study, we have proposed and validated that histogram of a good-quality bone scan image can enhance a poor-quality bone scan image. The histograms of two good-quality technetium-99m methyl diphosphonate bone scan images IAand IBrecommended by nuclear medicine physicians (NMPs) were used to enhance 87 poor-quality bone scan images. Processed images and their corresponding input images were compared visually by two NMPs with scoring and also quantitatively using entropy, Structural similarity index measure, edge-based contrast measure, and absolute brightness mean error. Barnard's unconditional test was applied with a null hypothesis that the histogram of both IAand IBproduces similar output image at α =0.05. The mean values of quantitative metrices of the processed images obtained using IAand IBwere compared using Kolmogorov—Smirnov test. Histogram of a good-quality bone scan image can enhance a poor-quality bone scan image. Visually, histogram of IBimproved statistically significantly higher proportion (P < 0.0001) of images (86/87) as compared to histogram of IA(51/87). Quantitatively, IBperformed better than IA,and the Chi-square distance of input and IBwas smaller than that of IA. In addition, a statistically significant (P < 0.05) difference in all the quantitative metrics among the outputs obtained using IAand IBwas observed. In our study, reference histogram of good-quality bone scan images transformed the majority of poor-quality bone scan images (98.85%) into visually good-quality images acceptable by NMPs.

Designing and Comparing Performances of Image Processing Pipeline for Enhancement of I-131-metaiodobenzylguanidine Images

“…Histogram transformation is considered as one of the fundamental processes for contrast enhancement of gray level images, which facilitates subsequent higher level operations such as detection and identification. [ 3 4 5 12 ] Gaussian filters remove noise from the image and improve signal to noise. [ 3 4 5 ] The minimum and maximum pixel value (i.e., counts) in the output image (obtained with different image processing pipeline) might not be same.…”

“…The selection of good quality I-131 images was based on the expectation that the resultant image after histogram specification will have quality similar to these images; however, it should not be far from the characteristic of input image. [ 12 ]…”