A 3D space–time motion evaluation for image registration in digital subtraction angiography

Taleb, Nasreddine; Bentoutou, Y.; Déforges, Olivier; Taleb, M.

doi:10.1016/s0895-6111(00)00054-9

Cited by 16 publications

(13 citation statements)

References 22 publications

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“…In the case of the second region (containing strong object edges), such a peak is not guaranteed to exist. In most cases, the intensity associated with all pixels belonging to image edges varies slowly in time from one level to another [3]. These two observations imply that the MPs can be extracted from the contrast images in the sequence by isolating the opacified vessels.…”

Section: A Movement Points Extraction From the Contrast Imagementioning

confidence: 95%

“…Pixels having gradient magnitude values less than are considered pixels belonging to homogeneous background and their gray values are put to 0 while those having gradient magnitude values greater than are considered pixels belonging to regions where edges are present and their gray values are put to 255. The second step consists of selecting moving pixels belonging to moving edges by exploiting the 3-D space-time motion detection algorithm [3].…”

Section: A Movement Points Extraction From the Contrast Imagementioning

confidence: 99%

“…Recently, a new, fully automatic motion correction technique was developed, which is capable of aligning pairs of images within few seconds [3]. This technique involves the extraction of the opacified vessels from the background anatomy by an a priori knowledge of the probable variation of arterial iodine concentration with time following an intravenous injection of contrast material.…”

Section: A Movement Points Extraction From the Contrast Imagementioning

confidence: 99%

“…However, patient motion is often more complex. Thus, there is a need for automated techniques that require little or no operator supervision [3]- [5].…”

Section: Introductionmentioning

confidence: 99%

“…The purpose of this paper is to demonstrate that using the three-dimensional (3-D) space-time motion-detection algorithm [3] for movement point (MP) selection and using the combined invariants-based similarity measure for MP displacement computation [4] enhance the accuracy of control points extraction and thus the effectiveness of the registration.…”

Section: Introductionmentioning

confidence: 99%

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Automatic extraction of control points for digital subtraction angiography image enhancement

Bentoutou

Taleb

2005

IEEE Trans. Nucl. Sci.

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In this paper, a new automatic control point selection and matching technique for digital subtraction angiography image enhancement is proposed. The characteristic of this approach is that it uses features that are based on image moments and are invariant to symmetric blur, translation, and rotation to establish correspondences between matched regions from two X-ray images. The automatic extraction of control points is based on an edge detection approach and on local similarity detection by means of template matching according to a combined invariantsbased similarity measure. A new strategy was developed in which a 3-D space-time motion detection algorithm was used for selecting movement points (MPs) belonging to moving structures. The proposed technique has been successfully applied to register several clinical data sets including coronary applications. The experimental results demonstrate the efficiency and accuracy of the algorithm which have outperformed manual registration in terms of root mean square error at the MPs. In addition, the results of the proposed registration algorithm, using the combined invariants-based similarity measure are compared to those of the same proposed algorithm but using the energy of the histogram of differences (EHD) measure. These results clearly indicate that the combined invariants-based measure may be better suited for subpixel registration as it produces more accurate results than EHD.

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Section: A Movement Points Extraction From the Contrast Imagementioning

confidence: 95%

Section: A Movement Points Extraction From the Contrast Imagementioning

confidence: 99%

Section: A Movement Points Extraction From the Contrast Imagementioning

confidence: 99%

“…However, patient motion is often more complex. Thus, there is a need for automated techniques that require little or no operator supervision [3]- [5].…”

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Automatic extraction of control points for digital subtraction angiography image enhancement

Bentoutou

Taleb

2005

IEEE Trans. Nucl. Sci.

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A stretching transform‐based automatic nonrigid registration system for cerebrovascular digital subtraction angiography images

Liu

Dong

et al. 2013

Int J Imaging Syst Tech

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In the cerebrovascular digital subtraction angiography (DSA), patient motion is the primary cause of image quality degradation. In this article, we describe a nonrigid image registration system for motion artifact reduction in DSA which is fully automatic, effective, and computationally very efficient. In this system, the mask image is partitioned to generate the appropriate control points. The energy of histogram of differences method is adopted as similarity measurement, and the Powell algorithm is utilized for acceleration. A forward stretching transformation is used to complete the motion estimation, and an inverse stretching transformation is used to generate the target image by pixel mapping strategy. The method of this system is effective to maintain the topological relationships of the gray value before and after the image deformation. Preliminary experiments on the cerebrovascular DSA images illustrate the applicability of the system. After the deformation, the mask image remains clear and accurate contours, and the quality of the subtraction image after the registration is favorable.

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The Application of ICA to the X-Ray Digital Subtraction Angiography

Tang

Wang

Chen

Advances in Neural Networks – ISNN 2007

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A 3D space–time motion evaluation for image registration in digital subtraction angiography

Cited by 16 publications

References 22 publications

Automatic extraction of control points for digital subtraction angiography image enhancement

Automatic extraction of control points for digital subtraction angiography image enhancement

A stretching transform‐based automatic nonrigid registration system for cerebrovascular digital subtraction angiography images

The Application of ICA to the X-Ray Digital Subtraction Angiography

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