A new X-ray computed tomography system for laboratory mouse imaging

Paulus, Michael J.; Sari‐Sarraf, Hamed; Gleason, Shaun S.; Bobrek, M.; Hicks, J.S.; Johnson, Dabney K.; Behel, J.K.; Thompson, L.H.; Allen, W.C.

doi:10.1109/23.775579

Cited by 92 publications

(40 citation statements)

References 17 publications

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“…Next, the rats were euthanized by a 20 mEq intravenous injection of KCI solution. Heparinized saline (5000 units=100 cm 3 ) and a vasodilator (Lidocaine, 1 mg=kg) were used to ush the vascular system, followed by infusion of microÿl (a silicon polymer containing lead chromate) at 100 mm Hg pressure using a Harvard pump. As soon as the microÿl entered both venaecava and pulmonary artery, the pulmonary artery and aorta were clamped and the infusion was stopped.…”

Section: Specimen Preparationmentioning

confidence: 99%

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Multi-generational analysis and visualization of the vascular tree in 3D micro-CT images

Wan

Ritman

Higgins

2002

Computers in Biology and Medicine

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Micro-CT scanners can generate large high-resolution three-dimensional (3D) digital images of small-animal organs, such as rat hearts. Such images enable studies of basic physiologic questions on coronary branching geometry and uid transport. Performing such an analysis requires three steps: (1) extract the arterial tree from the image; (2) compute quantitative geometric data from the extracted tree; and (3) perform a numerical analysis of the computed data. Because a typical coronary arterial tree consists of hundreds of branches and many generations, it is impractical to perform such an integrated study manually. An automatic method exists for performing step (1), extracting the tree, but little e ort has been made on the other two steps. We propose an environment for performing a complete study. Quantitative measures for arterial-lumen cross-sectional area, inter-branch segment length, branch surface area and others at the generation, inter-branch, and intra-branch levels are computed. A human user can then work with the quantitative data in an interactive visualization system. The system provides various forms of viewing and permits interactive tree editing for "on the y" correction of the quantitative data. We illustrate the methodology for 3D micro-CT rat heart images. ?

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Section: Specimen Preparationmentioning

confidence: 99%

“…Modern micro-CT scanners can produce very large three-dimensional (3D) digital images of vascular trees [1][2][3][4]. A typical tree consists of hundreds of branches and many generations.…”

Section: Introductionmentioning

confidence: 99%

Multi-generational analysis and visualization of the vascular tree in 3D micro-CT images

Wan

Ritman

Higgins

2002

Computers in Biology and Medicine

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“…Tissue contrast in the head and brain could be improved if a lower setting were permitted. CT scanners specifically designed for small-animal imaging and operating at lower tube voltages [3] exhibit appreciably higher tissue contrast and could, therefore, potentially yield improved image registration compared to that observed in this work. The MR image contrast might also be improved with a similar effect on registration accuracy.…”

Section: Discussionmentioning

confidence: 76%

PET, CT, and MR image registration of the rat brain and skull

Vaquero

Desco

Pascau

et al. 2001

IEEE Trans. Nucl. Sci.

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Abstract-Spatially registered positron emission tomography (PET), computed tomography (CT), and magnetic resonance (MR) images of the same small animal offer potential advantages over PET alone: CT images should allow accurate, nearly noise-free correction of the PET image data for attenuation; the CT or MR images should permit more certain identification of structures evident in the PET images; and CT images provide a priori anatomical information that may be of use with resolution-improving image-reconstruction algorithms that model the PET imaging process. However, image registration algorithms effective in human studies have not been characterized in the small-animal setting. Accordingly, we evaluated the ability of the automated image registration (AIR) and mutual information (MI) algorithms to register PET images of the rat skull and brain to CT or MR images of the same animal. External fiducial marks visible in all three modalities were used to estimate residual errors after registration. The AIR algorithm registered PET bone-to-CT bone images with a maximum error of less than 1.0 mm. The registration errors for PET brain-to-CT brain images, however, were greater, and considerable user intervention was required prior to registration. The AIR algorithm either failed or required excessive user intervention to register PET and MR brain images. In contrast, the MI algorithm yielded smaller registration errors in all scenarios with little user intervention. The MI algorithm thus appears to be a more robust method for registering PET, CT, and MR images of the rat head.Index Terms-Image reconstruction, positron emission tomography (PET), small animal imaging.

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“…For these reasons, investigators have developed high resolution imaging systems specifically designed for small animal imaging. 111,112,[118][119][120] These include microCT systems 118,[121][122][123] that incorporate a low power X-ray tube and a phosphor-coupled CCD camera or similar two-dimensional x-ray imaging detector to achieve spatial resolutions as high as 25 microns or better. Similarly, high-resolution images can be obtained using microPET scanners 111,119 having high-resolution detectors operated in coincidence to obtain spatial resolutions in the range of 1 to 2 mm, whereas SPECT imaging of mice [124][125][126][127][128][129] can be performed using pinhole collimation to obtain spatial resolutions better than 1 millimetre.…”

Section: Small-animal Imaging Systemsmentioning

confidence: 99%