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

Abstract

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.

Evaluation of Deformable Image Registration for Three-Dimensional Temporal Subtraction of Chest Computed Tomography Images

“…Currently, temporal subtraction is mainly used to detect a new nodule or nodule growth [ 23 ]. Itai et al [ 5 ] developed a voxel-matching technique for substantial reduction of subtraction artifacts in temporal subtraction images from thoracic MDCT. This registration method involved global image matching (2D CC), 3D local elastic matching, and 3D nonlinear image warping (3D voxel matching).…”

“…The applications of the information obtained from three-dimensional (3D) images have been rapidly increasing in the fields of diagnostics and surgical or radiotherapy planning. With the emergence of serial low-dose multidetector CT (MDCT) imaging for lung examination [ 2 ], the 3D temporal subtraction technique for chest CT has become a necessity for aiding in the diagnosis of conditions [ 3 – 5 ]. Temporal subtraction of serial volumes has the potential to efficiently identify areas with temporal changes, such as the lung, through approaches, such as visualization of tumor growth or shrinkage on subtraction images [ 6 , 7 ].…”

CT temporal subtraction: techniques and clinical applications

“…Non-rigid image registration methods have been proposed to reduce further subtraction artifacts on TS images (27)(28)(29)). Hereby we provide example of some of registration methods for reducing the subtraction artifacts due to normal structures, including blood vessels, in order to get precise subtraction of a pair of CT images.…”

A Novel MRA-Based Framework for Segmenting the Cerebrovascular System and Correlating Cerebral Vascular Changes to Mean Arterial Pressure

“…Voxel Matching: A voxel is an array of volume elements that constitute a notional 3D space. A 3D affine registration is used to handle the pose, orientation, and the data spacing changes and other scanning parameter changes between day 0 and day 700 [25]. In this step, the determined Euclidian radii are converted into diameter values.…”