No abstract

No abstract

Purpose:The detection of abdomino-pelvic tumors embedded in or nearby radioactive urine containing 18F-FDG activity is a challenging task on PET/CT scan. In this study, we propose and validate the suprathreshold stochastic resonance-based image processing method for the detection of these tumors.Methods:The method consists of the addition of noise to the input image, and then thresholding it that creates one frame of intermediate image. One hundred such frames were generated and averaged to get the final image. The method was implemented using MATLAB R2013b on a personal computer. Noisy image was generated using random Poisson variates corresponding to each pixel of the input image. In order to verify the method, 30 sets of pre-diuretic and its corresponding post-diuretic PET/CT scan images (25 tumor images and 5 control images with no tumor) were included. For each sets of pre-diuretic image (input image), 26 images (at threshold values equal to mean counts multiplied by a constant factor ranging from 1.0 to 2.6 with increment step of 0.1) were created and visually inspected, and the image that most closely matched with the gold standard (corresponding post-diuretic image) was selected as the final output image. These images were further evaluated by two nuclear medicine physicians.Results:In 22 out of 25 images, tumor was successfully detected. In five control images, no false positives were reported. Thus, the empirical probability of detection of abdomino-pelvic tumors evaluates to 0.88.Conclusion:The proposed method was able to detect abdomino-pelvic tumors on pre-diuretic PET/CT scan with a high probability of success and no false positives.

Introduction:In this study, we have developed a simple image processing application in MATLAB that uses suprathreshold stochastic resonance (SSR) and helps the user to visualize abdominopelvic tumor on the exported prediuretic positron emission tomography/computed tomography (PET/CT) images.Methods:A brainstorming session was conducted for requirement analysis for the program. It was decided that program should load the screen captured PET/CT images and then produces output images in a window with a slider control that should enable the user to view the best image that visualizes the tumor, if present. The program was implemented on personal computer using Microsoft Windows and MATLAB R2013b.Results:The program has option for the user to select the input image. For the selected image, it displays output images generated using SSR in a separate window having a slider control. The slider control enables the user to view images and select one which seems to provide the best visualization of the area(s) of interest.Conclusion:The developed application enables the user to select, process, and view output images in the process of utilizing SSR to detect the presence of abdominopelvic tumor on prediuretic PET/CT image.

Objectives:The aim of this study was to develop and verify a personal computer-based software tool for calculating uniformity indices of gamma camera.Materials and Methods:The program was developed in MATLAB R2013b under Microsoft Windows operating system. Noise-less digital phantoms with known uniformity parameters were used to verify the accuracy of the program. Two hundred and forty-four Co-57 flood source images were acquired on Symbia T6 and Discovery nuclear medicine/computed tomography 670. The uniformity indices of these images were determined with their respective vendor's software and also by the tool developed. Bland–Altman plots were used for measuring the agreements between the developed program and the vendor's program for the calculation of uniformity indices.Results:The tool for calculating uniformity indices was found to be accurate. Uniformity indices measured with the tool revealed a very good correlation with vendor's software based on Bland–Altman analysis, as almost all measurements were within the ±2 standard deviation range.Conclusion:The software tool for calculation of uniformity indices is accurate, and the uniformity indices calculated by it are in agreement with uniformity indices calculated by the vendor's software.