Iterative image warping technique for temporal subtraction of sequential chest radiographs to detect interval change

Ishida, Takayuki; Katsuragawa, Shigehiko; Nakamura, Katsumi; MacMahon, Heber; Doi, Kunio

doi:10.1118/1.598627

Cited by 108 publications

(47 citation statements)

References 9 publications

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“…The registered image is subtracted and if the registration is successful, areas with interval change appear as either dark or bright on a gray background. The original technique has been improved and evaluated using subjective ratings by radiologists of the quality of the subtraction image [110,113] and the results of the method have been compared with manual registration [131]. An observer study [56] with a small number of selected cases showed an increase in detection accuracy of interval change when both the normal image and the subtraction image were presented to the radiologist.…”

Section: Subtraction Techniquesmentioning

confidence: 99%

Computer aided diagnosis in chest radiography

Mouton¹,

Douglas

2003

Academic Radiology

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Section: Subtraction Techniquesmentioning

confidence: 99%

Computer aided diagnosis in chest radiography

Mouton¹,

Douglas

2003

Academic Radiology

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“…An imagewarping technique such as that described in the "Appendix" is first applied to the current and the previous image, as shown in Figure 1a,b, respectively, in order to obtain shift vectors 5 which represent the extent of deformation (or warping) of the previous image relative to the current image. Based on these shift vectors on the current image, the previous image can be warped to produce a temporal subtraction image.…”

Section: -D Nonlinear Image Warping By Use Of 3-d Voxel Matching Andmentioning

confidence: 99%

“…Many warping techniques for two-dimensional (2-D) images in chest radiography have been developed in the field of computer-aided diagnosis. 1,[3][4][5][6][7] In the temporal subtraction obtained with multipledetector computed tomography (MDCT) volume images that is used in thoracic examinations, it is necessary to employ a more complex threedimensional (3-D) registration and warping of lung regions between the current and previous images.…”

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confidence: 99%

Development of a Voxel-Matching Technique for Substantial Reduction of Subtraction Artifacts in Temporal Subtraction Images Obtained from Thoracic MDCT

et al. 2008

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A temporal subtraction image, which is obtained by subtraction of a previous image from a current one, can be used for enhancing interval changes (such as formation of new lesions and changes in existing abnormalities) on medical images by removing most of the normal structures. However, subtraction artifacts are commonly included in temporal subtraction images obtained from thoracic computed tomography and thus tend to reduce its effectiveness in the detection of pulmonary nodules. In this study, we developed a new method for substantially removing the artifacts on temporal subtraction images of lungs obtained from multiple-detector computed tomography (MDCT) by using a voxel-matching technique. Our new method was examined on 20 clinical cases with MDCT images. With this technique, the voxel value in a warped (or nonwarped) previous image is replaced by a voxel value within a kernel, such as a small cube centered at a given location, which would be closest (identical or nearly equal) to the voxel value in the corresponding location in the current image. With the voxel-matching technique, the correspondence not only between the structures but also between the voxel values in the current and the previous images is determined. To evaluate the usefulness of the voxel-matching technique for removal of subtraction artifacts, the magnitude of artifacts remaining in the temporal subtraction images was examined by use of the full width at half maximum and the sum of a histogram of voxel values, which may indicate the average contrast and the total amount, respectively, of subtraction artifacts. With our new method, subtraction artifacts due to normal structures such as blood vessels were substantially removed on temporal subtraction images. This computerized method can enhance lung nodules on chest MDCT images without disturbing misregistration artifacts.

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“…Ishida et al added to this method an initial global matching found through cross correlation of two radiographs at low resolution 8 and later extended the algorithm to include iterative steps. 9 Armato et al employed the same algorithm in the subtraction of temporally sequential DE soft-tissue images. 10 Other applications involve registering ventilation-perfusion images with digital chest radiography using contour detection and anatomical landmarks.…”

Section: Introductionmentioning

confidence: 99%

Multiscale deformable registration for dual‐energy x‐ray imaging

et al. 2009

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Dual-energy ͑DE͒ imaging of the chest improves the conspicuity of subtle lung nodules through the removal of overlying anatomical noise. Recent work has shown double-shot DE imaging ͑i.e., successive acquisition of low-and high-energy projections͒ to provide detective quantum efficiency, spectral separation ͑and therefore contrast͒, and radiation dose superior to single-shot DE imaging configurations ͑e.g., with a CR cassette͒. However, the temporal separation between highenergy ͑HE͒ and low-energy ͑LE͒ image acquisition can result in motion artifacts in the DE images, reducing image quality and diminishing diagnostic performance. This has motivated the development of a deformable registration technique that aligns the HE image onto the LE image before DE decomposition. The algorithm reported here operates in multiple passes at progressively smaller scales and increasing resolution. The first pass addresses large-scale motion by means of mutual information optimization, while successive passes ͑2-4͒ correct misregistration at finer scales by means of normalized cross correlation. Evaluation of registration performance in 129 patients imaged using an experimental DE imaging prototype demonstrated a statistically significant improvement in image alignment. Specific to the cardiac region, the registration algorithm was found to outperform a simple cardiac-gating system designed to trigger both HE and LE exposures during diastole. Modulation transfer function ͑MTF͒ analysis reveals additional advantages in DE image quality in terms of noise reduction and edge enhancement. This algorithm could offer an important tool in enhancing DE image quality and potentially improving diagnostic performance.

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Iterative image warping technique for temporal subtraction of sequential chest radiographs to detect interval change

Cited by 108 publications

References 9 publications

Computer aided diagnosis in chest radiography

Computer aided diagnosis in chest radiography

Development of a Voxel-Matching Technique for Substantial Reduction of Subtraction Artifacts in Temporal Subtraction Images Obtained from Thoracic MDCT

Multiscale deformable registration for dual‐energy x‐ray imaging

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