Effects from x-ray intensity instability on CT image characteristics

The purpose of this study was to compare the signal intensity (SI) and image characteristics of 1st-pass (FP) CT imaging vs. MR FP in an animal model of resting myocardial blood flow (MBF). Pigs (n=5) were scanned at rest using FP MRI perfusion imaging. Gd-DTPA was injected IV at 5cc/sec at 0.04mmol/kg. FP MR was acquired at 3T with 3 axial slices 3mm thick per R-R interval during bolus injection using a saturation recovery gradient echo sequence. ECG gated FP CT was performed immediately thereafter on a 64-slice scanner in axial mode with 10 2.5mm thick slices during bolus injection (5cc/sec) of 40% dilution of iopamidol 370. MBF was measured at rest using fluorescent microspheres between studies. SI was measured for baseline and peak myocardial enhancement phases. Contrast enhancement (CE)= (peak-baseline) SI/baseline SI X 100. Rest MBF was 0.60±0.15 ml/min/g. Temporal resolution was similar by technique but more slices were imaged by CT per R-R interval (10 vs 3) and spatial resolution was superior for FP CT. Image characteristics are shown in the table . Baseline (top) and peak enhancement (bottom) images for FP CT and MRI are shown in the figure . Results were similar when undiluted contrast was used for each modality. Despite similar absolute change in SI, CE during FP CT is markedly reduced compared to FP MR due to a more than 20-fold higher baseline SI of the myocardium.

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A Robust Line Filter for Automatic X-Ray/CT Image Segmentation

Applied Mechanics and Materials ◽

10.4028/www.scientific.net/amm.721.783 ◽

2014 ◽

Vol 721 ◽

pp. 783-787

Author(s):

Shao Hu Peng ◽

Hyun Do Nam ◽

Yan Fen Gan ◽

Xiao Hu

Keyword(s):

Multiscale Analysis ◽

Automatic Segmentation ◽

Local Variation ◽

Recognition System ◽

Ct Images ◽

Gray Level ◽

Ct Image ◽

Image Pyramid ◽

Level Variation ◽

X Ray

Automatic segmentation of the line-like regions plays a very important role in the automatic recognition system, such as automatic cracks recognition in X-ray images, automatic vessels segmentation in CT images. In order to automatically segment line-like regions in the X-ray/CT images, this paper presents a robust line filter based on the local gray level variation and multiscale analysis. The proposed line filter makes usage of the local gray level and its local variation to enhance line-like regions in the X-ray/CT image, which can well overcome the problems of the image noises and non-uniform intensity of the images. For detecting various sizes of line-like regions, an image pyramid is constructed based on different neighboring distances, which enables the proposed filter to analyze different sizes of regions independently. Experimental results showed that the proposed line filter can well segment various sizes of line-like regions in the X-ray/CT images, which are with image noises and non-uniform intensity problems.

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