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ABSTRACT: Recent advances in computing hardware have enabled the application of physically based simulation techniques to various research fields for improved accuracy. In this paper, we present a novel physically based non-rigid registration method using smoothed particle hydrodynamics (SPH) for hepatic metastasis volume-preserving registration between follow-up liver CT images. Our method models the liver and hepatic metastasis as a set of particles carrying their own physical properties. Based on the fact that the hepatic metastasis is stiffer than other normal cells in the liver parenchyma, the candidate regions of hepatic metastasis are modeled with particles of higher stiffness compared to the liver parenchyma. Particles placed in the liver and candidate regions of hepatic metastasis in the source image are transformed along a gradient vector flow (GVF)-based force field calculated in the target image. In this transformation, the particles are physically interacted and deformed by a novel deformable particle method which is proposed to preserve the hepatic metastasis to the best. In experimental results using 10 clinical datasets, our method matches the liver effectively between follow-up CT images as well as preserves the volume of hepatic metastasis almost completely, enabling the accurate assessment of the volume change of the hepatic metastasis. These results demonstrated a potential of the proposed method that it can deliver a substantial aid in measuring the size change of index lesion (i.e., hepatic metastasis) after the chemotheraphy of metastasis patients in radiation oncology.
IEEE transactions on bio-medical engineering 04/2013; · 2.15 Impact Factor
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ABSTRACT: In lung cancer screening, benign and malignant nodules can be classified through nodule growth assessment by the registration and, then, subtraction between follow-up computed tomography scans. During the registration, the volume of nodule regions in the floating image should be preserved, whereas the volume of other regions in the floating image should be aligned to that in the reference image. However, ground glass opacity (GGO) nodules are very elusive to automatically segment due to their inhomogeneous interior. In other words, it is difficult to automatically define the volume-preserving regions of GGO nodules. In this paper, we propose an accurate and fast nonrigid registration method. It applies the volume-preserving constraint to candidate regions of GGO nodules, which are automatically detected by gray-level cooccurrence matrix (GLCM) texture analysis. Considering that GGO nodules can be characterized by their inner inhomogeneity and high intensity, we identify the candidate regions of GGO nodules based on the homogeneity values calculated by the GLCM and the intensity values. Furthermore, we accelerate our nonrigid registration by using Compute Unified Device Architecture (CUDA). In the nonrigid registration process, the computationally expensive procedures of the floating-image transformation and the cost-function calculation are accelerated by using CUDA. The experimental results demonstrated that our method almost perfectly preserves the volume of GGO nodules in the floating image as well as effectively aligns the lung between the reference and floating images. Regarding the computational performance, our CUDA-based method delivers about 20× faster registration than the conventional method. Our method can be successfully applied to a GGO nodule follow-up study and can be extended to the volume-preserving registration and subtraction of specific diseases in other organs (e.g., liver cancer).
IEEE Transactions on Biomedical Engineering 11/2011; · 2.28 Impact Factor
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ABSTRACT: This study aimed to introduce heat map, a graphical data presentation method widely used in gene expression experiments, to the presentation and interpretation of image fidelity assessment data of compressed computed tomography (CT) images.
The authors used actual assessment data that consisted of five radiologists' responses to 720 computed tomography images compressed using both Joint Photographic Experts Group 2000 (JPEG2000) 2D and JPEG2000 3D compressions. They additionally created data of two artificial radiologists, which were generated by partly modifying the data from two human radiologists.
For each compression, the entire data set, including the variations among radiologists and among images, could be compacted into a small color-coded grid matrix of the heat map. A difference heat map depicted the advantage of 3D compression over 2D compression. Dendrograms showing hierarchical agglomerative clustering results were added to the heat maps to illustrate the similarities in the data patterns among radiologists and among images. The dendrograms were used to identify two artificial radiologists as outliers, whose data were created by partly modifying the responses of two human radiologists.
The heat map can illustrate a quick visual extract of the overall data as well as the entirety of large complex data in a compact space while visualizing the variations among observers and among images. The heat map with the dendrograms can be used to identify outliers or to classify observers and images based on the degree of similarity in the response patterns.
Medical Physics 08/2011; 38(8):4667-71. · 2.83 Impact Factor
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ABSTRACT: This study aimed to comparatively evaluate three different image comparison methods: alternate display without an intervening blank image (AWOB), alternate display with an intervening blank image (AWB), and side-by-side display (SSD), in terms of the perceptual sensitivity to image differences between Joint Photographic Experts Group 2000 (JPEG2000) compressed body CT images and their originals.
A total of 50 body CT images obtained with five different scan protocols (5-mm-thick abdomen, 0.67-mm-thick abdomen, 5-mm-thick lung, 0.67-mm-thick lung, and 5-mm-thick low-dose lung) were compressed to one of five compression ratios (reversible, 6:1, 8:1, 10:1, and 15:1) using JPEG2000 algorithm. The fidelity of the compressed images was visually assessed on a four-grade scale independently by five radiologists using each of the three image comparison methods of AWOB, AWB, and SSD. The fidelity grading results for the 40 irreversibly compressed images were compared between the three image comparison methods using the Friedman tests with post hoc Tukey tests. The number of image pairs with no perceptible difference was compared using the exact tests for paired proportions. The time required for the fidelity assessment for all of the 50 compressed images was also compared using the Friedman tests with post hoc Tukey tests.
For the 40 irreversibly compressed images, the fidelity grade was significantly lower for AWOB than for AWB or SSD (p < 0.01 for all readers); however, there was no significant difference between AWB and SSD (p-value range, 0.06-0.92). The percentage of image pairs with no perceptible difference tended to be smaller for AWOB than for AWB (p < 0.01 for all readers) or SSD (p < 0.01 for readers 1-3, p = 0.04 for reader 4, and p = 0.23 for reader 5). However, there was no significant difference between AWB and SSD (p-value range, 0.12- >0.99). For all of the 50 compressed images, the fidelity grading time significantly increased in the order of AWOB, SSD, and AWB.
In assessing the image fidelity of JPEG2000 compressed body CT images, AWOB yields lower fidelity grade and requires less fidelity grading time than AWB or SSD, indicating that AWOB is most sensitive to image differences among of them.
Medical Physics 02/2011; 38(2):836-44. · 2.83 Impact Factor
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ABSTRACT: This study aimed to assess the advantage of the Joint Photographic Experts Group 2000 (JPEG2000) 3D (part 2) over JPEG2000 in compressing abdomen computed tomography (CT) image data sets of different section thicknesses (STs).
Twenty CT scans were reconstructed with six STs (0.67, 1, 2, 3, 4, and 5 mm) and were then compressed to seven compression ratios (CRs) (reversible, 6:1, 8:1, 10:1, 12:1, 14:1, and 16:1) using JPEG2000 and JPEG2000 3D algorithms. Computing (encoding and decoding) times were measured. The image fidelity of the compressed images was quantitatively measured with two computerized image fidelity metrics, peak signal-to-noise ratio (PSNR) and multiscale structural similarity (MS-SSIM). For 120 selected case-relevant images (20 patients x one image per patient x 6 STs), five radiologists independently compared original and compressed images and assessed the fidelity of the compressed images on a four-grade scale. Wilcoxon signed-rank tests and Friedman tests with post hoc Dunn tests were used for the comparisons between the two compressions and among the six STs, respectively
For each combination of the ST and irreversible CR, JPEG2000 3D showed higher image fidelity than JPEG2000 in terms of PSNR (p < 0.0001), MS-SSIM (p < 0.0001), and five radiologists' grading (p-values ranged from <0.0001 to 0.003). At each CR, the advantage of JPEG2000 3D in image fidelity, measured as the differences in the two computerized image fidelity metrics (PSNR and MS-SSIM), significantly increased as the ST increased from 0.67 to 2 mm, and then slowly decreased as the ST increased from 2 to 5 mm. Similar trends were observed in visual analyses of 120 selected images by five radiologists. At each CR, the 3D-to-2D encoding-time ratio significantly decreased (p < 0.001) as the ST increased from 0.67 to 2 mm, and then slowly increased (p < 0.001) as the ST increased from 2 to 5 mm. The 3D-to-2D decoding-time ratio at each CR did not show a notable biphasic trend across the ST.
In compressing abdomen CT image data sets of different STs, the advantage of JPEG2000 3D over JPEG2000 increases as the ST increases from 0.67 to 2 mm, and then slowly decreases as the ST increases from 2 to 5 mm. The practical advantage of JPEG2000 3D is limited for a submillimeter ST due to its greater computing time with only a marginal improvement in image fidelity.
Medical Physics 08/2010; 37(8):4238-48. · 2.83 Impact Factor
