|Year : 2017 | Volume
| Issue : 4 | Page : 330-332
Development of a simple image processing application that makes abdominopelvic tumor visible on positron emission tomography/computed tomography image
Anil Kumar Pandey1, Kartik Saroha1, Param Dev Sharma2, Chetan Patel1, Chandrashekhar Bal1, Rakesh Kumar1
1 Department of Nuclear Medicine, All India Institute of Medical Sciences, New Delhi, India
2 Department of Computer Science, SGTB Khalsa College, University of Delhi, New Delhi, India
|Date of Web Publication||12-Oct-2017|
Anil Kumar Pandey
Department of Nuclear Medicine, All India Institute of Medical Sciences, Ansari Nagar, New Delhi - 110 029
Source of Support: None, Conflict of Interest: None
| Abstract|| |
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.
Keywords: Abdominopelvic tumor, prediuretic positron emission tomography/computed tomography image, stochastic resonance
|How to cite this article:|
Pandey AK, Saroha K, Sharma PD, Patel C, Bal C, Kumar R. Development of a simple image processing application that makes abdominopelvic tumor visible on positron emission tomography/computed tomography image. Indian J Nucl Med 2017;32:330-2
|How to cite this URL:|
Pandey AK, Saroha K, Sharma PD, Patel C, Bal C, Kumar R. Development of a simple image processing application that makes abdominopelvic tumor visible on positron emission tomography/computed tomography image. Indian J Nucl Med [serial online] 2017 [cited 2021 Aug 5];32:330-2. Available from: https://www.ijnm.in/text.asp?2017/32/4/330/216561
| Introduction|| |
Abdominopelvic tumors on positron emission tomography/computed tomography (PET/CT) images are hard to visualize due to the presence of radioactive urine (18 F-Fluorodeoxyglucose) in the urinary bladder. Currently, diuretics are administered to flush radioactive urine that makes tumor visible on postdiuretic PET/CT image.,,, It is possible to protect patients from side effect of diuretic administration and an extra radiation burden due to CT scan of PET/CT study. Saroha et al. have claimed 88% probability of detection of abdominopelvic tumor using suprathreshold stochastic resonance (SSR)-based image processing method using a sample of thirty prediuretic PET/CT images. However, to utilize the advantage of this technique, the users need to have a tool that is handy, once the images are exported from the workstation. In this study, we have developed and validated an application that processes PET/CT images based on an SSR image processing method to reveal the presence of tumor.
| Methods|| |
Requirement analysis for the application program was made by conducting a brainstorming session among authors. It was decided that the program should be developed for personal computer, Microsoft Windows, and provide option to load PET/CT images (jpg, bmp, tiff, and dcm format) and display output images in a window with a slider control for selecting best visualization. It was implemented using MATLAB image processing toolbox as it has many verified and tested built-in functions. The flowchart in [Figure 1] shows the steps of the application, including the computation performed for generating SSR.
|Figure 1: Flow chart of the program. The steps pertaining to the technique of suprathreshold stochastic resonance are indicated such. Dgdfm is the degree of freedom, an input parameter of Chi-square probability distribution|
Click here to view
| Results and Discussion|| |
The program automatically detects the format of the input file from its file extension. It can process the image files written in dcm, jpeg, jpg, png, and bmp format. If the input file is not from among these formats, the program exits with a descriptive message to the operator specifying correct usage.
The program has been tested on Microsoft Windows ™ to display the output images both on the monochrome as well as on color display devices. The interface of the application is intuitively simple and uses familiar idiom of a graphical user interface experience. The menu-driven interface offers an on-screen list of choices, in which selections can be accomplished by one or more keystrokes [Figure 2] or point-and-click using a mouse. This eases the operator's memorization burden.
|Figure 2: Step-wise program flows. User types “SsrNewScript” on MATLAB command prompt. Program provides option for the selection of input image, displays selected image, user places rectangular region of interest on image, output images with slider|
Click here to view
To begin user types “SsrNewScript” on MATLAB command prompt as shown in [Figure 2]. The program provides option to the user for selection of input image. It displays image in a new window, and when user moves mouse pointer on the image, mouse pointer changes in shape. Holding mouse button down and dragging it, a rectangular region of interest (ROI) can be placed. At a double click on ROI, the program takes the image included within the ROI for processing using SSR image processing method. After processing the input image, the program displays 18 output images to be reviewed in a separate window having slider option so that user can view the processed images one by one.
The application was used to process the same image set as in  and also ten additional images; making a total set of forty prediuretic PET/CT images. It was found that the results reported in  were not only preserved but also were viewable with better ease. It is envisaged that this application should help in familiarization and deciding the usefulness of the SSR method when it is applied on a large number of prediuretic PET/CT images. The only requirement is that the user screen captures the input PET/CT slice image on which he is suspecting the presence of tumor that is not clearly visible on inspection.
The presence of abdominopelvic tumors can be detected even on a prediuretic PET/CT image using the developed application.
| 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.
Financial support and sponsorship
Conflicts of interest
There are no conflicts of interest.
| References|| |
Kamel EM, Jichlinski P, Prior JO, Meuwly JY, Delaloye JF, Vaucher L, et al.
Forced diuresis improves the diagnostic accuracy of 18F-FDG PET in abdominopelvic malignancies. J Nucl Med 2006;47:1803-7.
Nayak B, Dogra PN, Naswa N, Kumar R. Diuretic 18F-FDG PET/CT imaging for detection and locoregional staging of urinary bladder cancer: Prospective evaluation of a novel technique. Eur J Nucl Med Mol Imaging 2013;40:386-93.
Harkirat S, Anand S, Jacob M. Forced diuresis and dual-phase F-fluorodeoxyglucose-PET/CT scan for restaging of urinary bladder cancers. Indian J Radiol Imaging 2010;20:13-9.
] [Full text]
Anjos DA, Etchebehere EC, Ramos CD, Santos AO, Albertotti C, Camargo EE, et al.
18F-FDG PET/CT delayed images after diuretic for restaging invasive bladder cancer. J Nucl Med 2007;48:764-70.
Saroha K, Pandey AK, Sharma PD, Behera A, Patel C, Bal C, et al.
Development and validation of the Suprathreshold stochastic resonance-based image processing method for the detection of abdomino-pelvic tumor on PET/CT scans. Indian J Nucl Med 2017;32:103-09.
] [Full text]
[Figure 1], [Figure 2]