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Title: TU-H-206-04: An Effective Homomorphic Unsharp Mask Filtering Method to Correct Intensity Inhomogeneity in Daily Treatment MR Images

Abstract

Purpose: The daily treatment MRIs acquired on MR-IGRT systems, like diagnostic MRIs, suffer from intensity inhomogeneity issue, associated with B1 and B0 inhomogeneities. An improved homomorphic unsharp mask (HUM) filtering method, automatic and robust body segmentation, and imaging field-of-view (FOV) detection methods were developed to compute the multiplicative slow-varying correction field and correct the intensity inhomogeneity. The goal is to improve and normalize the voxel intensity so that the images could be processed more accurately by quantitative methods (e.g., segmentation and registration) that require consistent image voxel intensity values. Methods: HUM methods have been widely used for years. A body mask is required, otherwise the body surface in the corrected image would be incorrectly bright due to the sudden intensity transition at the body surface. In this study, we developed an improved HUM-based correction method that includes three main components: 1) Robust body segmentation on the normalized image gradient map, 2) Robust FOV detection (needed for body segmentation) using region growing and morphologic filters, and 3) An effective implementation of HUM using repeated Gaussian convolution. Results: The proposed method was successfully tested on patient images of common anatomical sites (H/N, lung, abdomen and pelvis). Initial qualitative comparisons showed that thismore » improved HUM method outperformed three recently published algorithms (FCM, LEMS, MICO) in both computation speed (by 50+ times) and robustness (in intermediate to severe inhomogeneity situations). Currently implemented in MATLAB, it takes 20 to 25 seconds to process a 3D MRI volume. Conclusion: Compared to more sophisticated MRI inhomogeneity correction algorithms, the improved HUM method is simple and effective. The inhomogeneity correction, body mask, and FOV detection methods developed in this study would be useful as preprocessing tools for many MRI-related research and clinical applications in radiotherapy. Authors have received research grants from ViewRay and Varian.« less

Authors:
; ; ;  [1]
  1. Washington University School of Medicine, Saint Louis, MO (United States)
Publication Date:
OSTI Identifier:
22654041
Resource Type:
Journal Article
Resource Relation:
Journal Name: Medical Physics; Journal Volume: 43; Journal Issue: 6; Other Information: (c) 2016 American Association of Physicists in Medicine; Country of input: International Atomic Energy Agency (IAEA)
Country of Publication:
United States
Language:
English
Subject:
61 RADIATION PROTECTION AND DOSIMETRY; 60 APPLIED LIFE SCIENCES; BIOMEDICAL RADIOGRAPHY; CALCULATION METHODS; CORRECTIONS; FILTERS; IMAGES; NMR IMAGING

Citation Formats

Yang, D, Gach, H, Li, H, and Mutic, S. TU-H-206-04: An Effective Homomorphic Unsharp Mask Filtering Method to Correct Intensity Inhomogeneity in Daily Treatment MR Images. United States: N. p., 2016. Web. doi:10.1118/1.4957649.
Yang, D, Gach, H, Li, H, & Mutic, S. TU-H-206-04: An Effective Homomorphic Unsharp Mask Filtering Method to Correct Intensity Inhomogeneity in Daily Treatment MR Images. United States. doi:10.1118/1.4957649.
Yang, D, Gach, H, Li, H, and Mutic, S. 2016. "TU-H-206-04: An Effective Homomorphic Unsharp Mask Filtering Method to Correct Intensity Inhomogeneity in Daily Treatment MR Images". United States. doi:10.1118/1.4957649.
@article{osti_22654041,
title = {TU-H-206-04: An Effective Homomorphic Unsharp Mask Filtering Method to Correct Intensity Inhomogeneity in Daily Treatment MR Images},
author = {Yang, D and Gach, H and Li, H and Mutic, S},
abstractNote = {Purpose: The daily treatment MRIs acquired on MR-IGRT systems, like diagnostic MRIs, suffer from intensity inhomogeneity issue, associated with B1 and B0 inhomogeneities. An improved homomorphic unsharp mask (HUM) filtering method, automatic and robust body segmentation, and imaging field-of-view (FOV) detection methods were developed to compute the multiplicative slow-varying correction field and correct the intensity inhomogeneity. The goal is to improve and normalize the voxel intensity so that the images could be processed more accurately by quantitative methods (e.g., segmentation and registration) that require consistent image voxel intensity values. Methods: HUM methods have been widely used for years. A body mask is required, otherwise the body surface in the corrected image would be incorrectly bright due to the sudden intensity transition at the body surface. In this study, we developed an improved HUM-based correction method that includes three main components: 1) Robust body segmentation on the normalized image gradient map, 2) Robust FOV detection (needed for body segmentation) using region growing and morphologic filters, and 3) An effective implementation of HUM using repeated Gaussian convolution. Results: The proposed method was successfully tested on patient images of common anatomical sites (H/N, lung, abdomen and pelvis). Initial qualitative comparisons showed that this improved HUM method outperformed three recently published algorithms (FCM, LEMS, MICO) in both computation speed (by 50+ times) and robustness (in intermediate to severe inhomogeneity situations). Currently implemented in MATLAB, it takes 20 to 25 seconds to process a 3D MRI volume. Conclusion: Compared to more sophisticated MRI inhomogeneity correction algorithms, the improved HUM method is simple and effective. The inhomogeneity correction, body mask, and FOV detection methods developed in this study would be useful as preprocessing tools for many MRI-related research and clinical applications in radiotherapy. Authors have received research grants from ViewRay and Varian.},
doi = {10.1118/1.4957649},
journal = {Medical Physics},
number = 6,
volume = 43,
place = {United States},
year = 2016,
month = 6
}
  • Purpose: With the implementation of Cone-beam Computed-Tomography (CBCT) in proton treatment, we introduces a quick and effective tool to verify the patient’s daily setup and geometry changes based on the Water-Equivalent-Thickness Projection-Image(WETPI) from individual beam angle. Methods: A bilateral head neck cancer(HNC) patient previously treated via VMAT was used in this study. The patient received 35 daily CBCT during the whole treatment and there is no significant weight change. The CT numbers of daily CBCTs were corrected by mapping the CT numbers from simulation CT via Deformable Image Registration(DIR). IMPT plan was generated using 4-field IMPT robust optimization (3.5% rangemore » and 3mm setup uncertainties) with beam angle 60, 135, 300, 225 degree. WETPI within CTV through all beam directions were calculated. 3%/3mm gamma index(GI) were used to provide a quantitative comparison between initial sim-CT and mapped daily CBCT. To simulate an extreme case where human error is involved, a couch bar was manually inserted in front of beam angle 225 degree of one CBCT. WETPI was compared in this scenario. Results: The average of GI passing rate of this patient from different beam angles throughout the treatment course is 91.5 ± 8.6. In the cases with low passing rate, it was found that the difference between shoulder and neck angle as well as the head rest often causes major deviation. This indicates that the most challenge in treating HNC is the setup around neck area. In the extreme case where a couch bar is accidently inserted in the beam line, GI passing rate drops to 52 from 95. Conclusion: WETPI and quantitative gamma analysis give clinicians, therapists and physicists a quick feedback of the patient’s setup accuracy or geometry changes. The tool could effectively avoid some human errors. Furthermore, this tool could be used potentially as an initial signal to trigger plan adaptation.« less
  • Purpose: Grid artifacts are caused when using the antiscatter grid in obtaining digital x-ray images. In this paper, research on grid artifact reduction techniques is conducted especially for the direct detectors, which are based on amorphous selenium. Methods: In order to analyze and reduce the grid artifacts, the authors consider a multiplicative grid image model and propose a homomorphic filtering technique. For minimal damage due to filters, which are used to suppress the grid artifacts, rotated grids with respect to the sampling direction are employed, and min-max optimization problems for searching optimal grid frequencies and angles for given sampling frequenciesmore » are established. The authors then propose algorithms for the grid artifact reduction based on the band-stop filters as well as low-pass filters. Results: The proposed algorithms are experimentally tested for digital x-ray images, which are obtained from direct detectors with the rotated grids, and are compared with other algorithms. It is shown that the proposed algorithms can successfully reduce the grid artifacts for direct detectors. Conclusions: By employing the homomorphic filtering technique, the authors can considerably suppress the strong grid artifacts with relatively narrow-bandwidth filters compared to the normal filtering case. Using rotated grids also significantly reduces the ringing artifact. Furthermore, for specific grid frequencies and angles, the authors can use simple homomorphic low-pass filters in the spatial domain, and thus alleviate the grid artifacts with very low implementation complexity.« less
  • Purpose: Recent clinical outcome studies on prostate cancer have reported the influence of patient's obesity on the biochemical failure rates after various treatment modalities. In this study, we investigated the effect of patient's physical characteristics on prostate shift in external beam radiotherapy (EBRT) and hypothesized that there maybe a correlation between patient physique and tumor shift. Methods and Materials: A retrospective analysis was performed using data for 117 patients who received image-guided radiation therapy (IGRT) for prostate cancer between January 2005 and April 2007. A total of 1,465 CT scans were analyzed. The standard deviations (SDs) of prostate shifts formore » all patients, along with patient weight, body mass index (BMI), and subcutaneous adipose-tissue thickness (SAT), were determined. Spearman rank correlation analysis was performed. Results: Of the 117 patients, 26.5% were considered normal weight, 48.7% were overweight, 17.9% were mildly obese, and 6.9% were moderately to severely obese. Notably 1.3%, 1.5%, 2.0%, and 21.2% of the respective shifts were greater than 10 mm in the left-right (LR) direction for the four patient groups, whereas in the anterior-posterior direction the shifts are 18.2%, 12.6%, 6.7%, and 21.0%, respectively. Strong correlations were observed between SAT, BMI, patient weight, and SDs of daily shifts in the LR direction (p < 0.01). Conclusions: The strong correlation between obesity and shift indicates that without image-guided radiation therapy, the target volume (prostate with or without seminal vesicles) may not receive the intended dose for patients who are moderate to severely obese. This may explain the higher recurrence rate with conventional external beam radiation therapy.« less
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