This paper introduced the imaging principle, data acquisition method and image characteristics of PET/CT; Then reviewed several image reconstruction methods widely used in PET/CT at present in detail, such as FBP, ML-EM, 3DRP and so on. Finally, the advantages and disadvantages of these methods were summarized and compared.
Image Interpretation, Computer-Assisted ; methods ; Positron-Emission Tomography ; methods ; Tomography, X-Ray Computed ; methods

Colon cancer is one of the leading causes of cancer-related deaths, while the virtual colonoscopy plays an important role in the early detection of colon cancer. Effective colon segmentation is the basis of virtual colonoscopy. Oral contrast agent can reduce the use of laxatives, but it can to bring some difficulties in the colon segmentation. Because of the partial volume effect, the CT value of air-tagging boundary span a wide range, which are not easily eliminated. We present an effective method of colon segmentation in this paper. Firstly, we used adaptive threshold method to extract air area. Then we segmented tagging region and removed air-tagging boundary by segment region growing method based on statistical information and morphological operation. The experiments showed that the agreement between the results by manual and by orithm segmentation reached 93.4%.
Algorithms ; Colon ; diagnostic imaging ; Colonography, Computed Tomographic ; methods ; Humans ; Pattern Recognition, Automated ; methods ; Radiographic Image Enhancement ; methods ; Radiographic Image Interpretation, Computer-Assisted ; methods

An algebraic image reconstruction from few views using bilateral-filtering iterative method was proposed due to the problem of computed tomography insufficient data in the present study. In each iteration reconstruction, we first used algebraic reconstruction technique (ART) algorithm to reconstruct an image, ensuring the non-negativity of the reconstructed image at the same time, and then performed bilateral-filtering to the above-mentioned image. In order to improve reconstructed image quality and accelerate the convergence speed, we developed a modified bilateral-filtering method. Shepp-Logan simulation experiments and real CT projection data reconstructions showed the feasibility of the algorithm. The results showed that, compared with the traditional methods of filtered back projection (FBP), ART and GF-ART,the proposed method has a higher signal-to-noise ratio, and maintains more effectively the image edge information.
Algorithms ; Artifacts ; Humans ; Image Processing, Computer-Assisted ; methods ; Radiographic Image Interpretation, Computer-Assisted ; methods ; Tomography, X-Ray Computed ; methods

To reconstruct a tooth model from CT slices, we need to define the accurate contour of each tooth from CT slices. In this paper, we propose a semi-automatic method for drawing the contours of teeth in dental CT images. First of all, we select the reference slice from CT slices and carry out tooth segmentation interactively based on shape characteristic of each tooth. The dental CT images have the following distinct characteristic: in two neighboring CT slices, the size, location and intensity of corresponding tooth is very similar, so we can project the bounding box of the tooth whose contour has been drawn onto the next slice as the operation region of corresponding tooth. And then we perform segmentation operation tooth by tooth in the operation region based on the region growing algorithm using the information passed from the previous slice. With the reference slice as the starting slice, we carry out tooth segmentation slice by slice like this way automatically. The test result shows that the proposed method can detect the contours of teeth quickly and reliably with only little user intervention and it has practical value.
Humans ; Image Processing, Computer-Assisted ; methods ; Radiographic Image Interpretation, Computer-Assisted ; methods ; Tomography, X-Ray Computed ; methods ; Tooth ; diagnostic imaging

The present paper introduces the components and operating principle of Sensation 16 CT date measuring system (DMS), analyzes the fixed position of modules and channels in array detector modules (ADM), the Checkup table, Tuneup table and IRS table in ICS Syngo Service. The author also puts forward a solution of manual handling of defective channels.
Artifacts ; Radiographic Image Interpretation, Computer-Assisted ; methods ; Software ; Tomography, Spiral Computed ; instrumentation

A CT 3-D image is reconstructed based on a lot of 2-D slice images. A new 3-D image reconstruction method, presented in this paper, is to use the helical scan continuity, sufficient condition of image reconstruction and the raw data from a few helical scan cycles to reconstruct,by a direct interpolation algorithm, 2-D images and then 3-D images.
Algorithms ; Humans ; Image Processing, Computer-Assisted ; methods ; Imaging, Three-Dimensional ; methods ; Radiographic Image Enhancement ; methods ; Radiographic Image Interpretation, Computer-Assisted ; methods ; Reproducibility of Results ; Tomography, Spiral Computed ; methods

OBJECTIVEWe present an alternative approach for precise reconstruction of the images from helical cone-beam projections combining Hilbert filter and Ramp filter.

METHODSBased on the Katsevich algorithm framework, the proposed algorithm combined the FDK-type algorithms and Katsevich algorithm for their respective advantages, to completely avoid the direct derivatives with respect to the coordinates on the detector plane.

RESULTSThe experimental results validated the accuracy of the new algorithm, and this approach significantly improved the resolution of the reconstructed images with much reduced artifacts.

CONCLUSIONThe proposed reconstruction formula based on hybrid Hilbert-Ramp filter is an important development of Katsevich reconstruction formula, and the different forms of the Ramp filters can be designed to realize frequency modulation according to the actual clinical application.

Algorithms ; Humans ; Image Processing, Computer-Assisted ; methods ; Radiographic Image Enhancement ; methods ; Radiographic Image Interpretation, Computer-Assisted ; methods ; Spiral Cone-Beam Computed Tomography ; methods

Objective To explore the feasibility of reducing radiation dose of CT colonography (CTC) while preserving image quality using the third-generation dual-source CT at 70 kV tube voltage with advanced modeled iterative reconstruction (ADMIRE). Methods This prospective study consecutively included 53 patients. All patients underwent CTC at 120 kV in supine position with filtered back projection reconstruction and at 70 kV in prone position with ADMIRE with the same scan range. Radiation dose and image quality were compared between these two protocols. Results CT dose index volume,dose-length product,and effective dose of 70 kV were (1.47±0.23)mGy,(68.85±13.82)mGy·cm,and (1.03±0.21)mSv,respectively,which were significantly lower than 120 kV mode [(2.96±0.61)mGy (t=25.356,P=0.000),(136.97±32.77)mGy·cm (t=22.246,P=0.000),and (2.05±0.49)mSv (t=22.293,P=0.000)]. Signal to noise ratio of 70 kV with ADMIRE was 3.60±0.58,which was obviously higher than that of 120 kV as 2.34±0.47 (t=-18.036,P=0.000). Noise of 70 kV with ADMIRE was (11.81±1.93)HU,which was obviously lower than that of 120 kV as (14.39±2.57)HU (t=7.856,P=0.000). The κ value of two radiologists' overall subjective image score was 0.843 (P=0.000). For 2D images,the noise score of 70 kV with ADMIRE was significantly lower (Z=325.000,P=0.000) and the overall image quality was significantly higher (Z=78.000,P=0.001) compared with 120 kV;however,the sharpness had no significant difference. All scores ranged from 4 to 5. For 3D virtual endoscopy,the overall image quality of 70 kV with ADMIRE and 120 kV was not significantly different (Z=4.000,P=0.059),and all scores ranged from 4 to 5. Conclusion CTC at 70 kV tube voltage combined with ADMIRE can remarkably reduce the radiation dose while maintaining imaging quality than 120 kV at third-generation dual-source CT.
Colon ; diagnostic imaging ; Colonography, Computed Tomographic ; methods ; Humans ; Prone Position ; Prospective Studies ; Radiation Dosage ; Radiographic Image Interpretation, Computer-Assisted ; Radionuclide Imaging ; Signal-To-Noise Ratio

To explore the value of the third generation dual-source computed tomography (CT) convolution kernel in display of pulmonary ground-glass nodule (GGN) in transverse image reconstruction.
 Methods: A total of 52 lung adenocarcinoma patients with lung CT data were selected from February 2018 to January 2019 for this study. The pulmonary CT data were reconstructed by convolutional nucleus B157, Br54, and Br49. The signal-to-noise ratio (SNR), the contrast-to-noise ratio (CNR), and the standard deviation (SD) of the image at the GGN were used as the objective evaluation standard of image quality. Subjective image quality was scored by 2 radiologists from 3 aspects (overall image quality, noise, and lesion outline).
 Results: Objective image quality evaluation, SNR and CNR of reconstructed convolution kernel Br49 (SNR: 11.36±5.39, CNR: 7.19±4.29), Br54 (SNR: 8.30±3.35, CNR: 5.09±2.86) are greater than those of Bl57 (SNR: 4.18±2.10, CNR: 3.25±1.78; all P<0.01). SD of reconstructed convolution kernel Br49 (61.80±20.17) and Br54 (80.45±20.31) is smaller than that of Bl57 (137.92±31.11, both P<0.01). In the subjective image quality evaluation, the overall image quality score 5.0(4.5, 5.0) of Br54 was higher than that of all other images [Br49: 3.0(3.0, 4.0), Bl57: 3.0(3.0, 3.5); both P<0.05]. The Br54 image showed that the lesion contour ability score 5.0(4.0, 5.0) was higher than all other images [Br49: 4.0(4.0, 5.0), Bl57: 3.0(3.0, 3.0); both P<0.05]; Br49 image noise score 3.0(3.0, 3.0) is the lowest one [Br54 4.0(4.0, 4.0), Bl57 5.0(5.0, 5.0); both P<0.05].
 Conclusion: The reasonable selection of CT convolution kernel plays an important role in the subjective and objective image quality of GGN. It is suggested that Br54 should be used as the reconstruction of convolutional kernel in pulmonary ground glass nodules, which is helpful for doctors to find and diagnose GGN.
Algorithms ; Humans ; Radiation Dosage ; Radiographic Image Interpretation, Computer-Assisted ; Signal-To-Noise Ratio ; Tomography, X-Ray Computed

Objective To quantitatively compare and determine the best pancreatic tumor contrast to noise ratio (CNR) in different dual-energy derived datasets. Methods In this retrospective, single center study, 16 patients (9 male, 7 female, average age 59.4±13.2 years) with pathologically diagnosed pancreatic cancer were enrolled. All patients received an abdominal scan using a dual source CT scanner 7 to 31 days before biopsy or surgery. After injection of iodine contrast agent, arterial and pancreatic parenchyma phase were scanned consequently, using a dual-energy scan mode (100 kVp/230 mAs and Sn 140 kVp/178 mAs) in the pancreatic parenchyma phase. A series of derived dual-energy datasets were evaluated including non-liner blending (non-linear blending width 0-500 HU; blending center -500 to 500 HU), mono-energetic (40-190 keV), 100 kVp and 140 kVp. On each datasets, mean CT values of the pancreatic parenchyma and tumor, as well as standard deviation CT values of subcutaneous fat and psoas muscle were measured. Regions of interest of cutaneous fat and major psoas muscle of 100 kVp and 140 kVp images were calculated. Best CNR of subcutaneous fat (CNRF) and CNR of the major psoas muscle (CNRM) of non-liner blending and mono-energetic datasets were calculated with the optimal mono-energetic keV setting and the optimal blending center/width setting for the best CNR. One Way ANOVA test was used for comparison of best CNR between different dual-energy derived datasets. Results The best CNRF (4.48±1.29) was obtained from the non-liner blending datasets at blending center -16.6±103.9 HU and blending width 12.3±10.6 HU. The best CNRF (3.28±0.97) was obtained from the mono-energetic datasets at 73.3±4.3 keV. CNRF in the 100 kVp and 140 kVp were 3.02±0.91 and 1.56±0.56 respectively. Using fat as the noise background, all of these images series showed significant differences (P<0.01) except best CNRF of mono-energetic image sets vs. CNRF of 100 kVp image (P=0.460). Similar results were found using muscle as the noise background (mono-energetic image vs. 100 kVp image: P=0.246; mono-energetic image vs. non-liner blending image: P=0.044; others: P<0.01). Conclusion Compared with mono-energetic datasets and low kVp datasets, non-linear blending image at automatically chosen blending width/window provides better tumor to the pancreas CNR, which might be beneficial for better detection of pancreatic tumors.
Adenocarcinoma ; Humans ; Noise ; Radiographic Image Interpretation, Computer-Assisted ; Retrospective Studies ; Tomography, X-Ray Computed