DWT-Based Segmentation Method for Coronary Arteries

Hsu, Chih‐Yu; Hung, Pei-Kai; Lin, Muh-Shi; Huang, Chih-Hsin; Chen, Chung-Ming; Wang, Tzung‐Dau; Lee, Wei-Jei

doi:10.1007/s10916-014-0055-8

Cited by 9 publications

(1 citation statement)

References 19 publications

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“…Various methods have been applied for medical image segmentation, most notably thresholding [1], region-growing [2,3], graph based [4], level set based [5], snake [6], clustering [7][8][9][10], and statistical methods. Clustering is the most popular method in medical image segmentation for its simplicity and efficiency, with expectation-maximization, K-mean, Fuzzy C-Means, and neural network algorithms being the typical methods.…”

Section: Introductionmentioning

confidence: 99%

Brain MR Image Segmentation with Spatial Constrained K-mean Algorithm and Dual-Tree Complex Wavelet Transform

Zhang

Jiang²,

Wang

et al. 2014

J Med Syst

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In brain MR images, the noise and low-contrast significantly deteriorate the segmentation results. In this paper, we propose an automatic unsupervised segmentation method integrating dual-tree complex wavelet transform (DT-CWT) with K-mean algorithm for brain MR image. Firstly, a multi-dimensional feature vector is constructed based on the intensity, the low-frequency subband of DT-CWT and spatial position information. Then, a spatial constrained K-mean algorithm is presented as the segmentation system. The proposed method is validated by extensive experiments using both simulated and real T1-weighted MR images, and compared with the state-of-the-art algorithms.

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Section: Introductionmentioning

confidence: 99%

Brain MR Image Segmentation with Spatial Constrained K-mean Algorithm and Dual-Tree Complex Wavelet Transform

Zhang

Jiang²,

Wang

et al. 2014

J Med Syst

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Processing of CT Lung Images as a Part of Radiomics

Зотин

Hamad

Simonov

et al. 2020

Intelligent Decision Technologies

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Analysis of Enlarged Images Using Time-of-Flight Magnetic Resonance Angiography, Computed Tomography, and Conventional Angiography

et al. 2014

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This study aimed to assess the accuracy of time-of-flight magnetic resonance angiography, computed tomography, and conventional angiography in depicting the actual length of the blood vessels. Three-dimensional time-of-flight magnetic resonance angiography and computed tomography angiography were performed using a flow phantom model that was 2.11 mm in diameter and had a total area of 0.26 cm(2). After this, volume rendering technique and the maximum intensity projection method as well as two-dimensional digital subtraction angiography and three-dimensional rotational angiography based on conventional angiography were conducted. For three-dimensional time-of-flight magnetic resonance angiography, 8 channel sensitivity encoding (SENSE) head coil for the 3.0 Tesla equipment was used. Fluid was added to the normal saline solution at various rates, such as 11.4, 20.0, 31.4, 40.0, 51.5, 60.0, 71.5, 80.1, 91.5, and 100.1 cm/s using an automatic contrast media injector. Each image was thoroughly examined. After reconstructing the image using the maximum intensity projection method, the length of the conduit in the center of the coronal plane was measured 30 times. After performing computed tomography angiography with the 64-channel CT scanner and 16-channel CT scanner, the images were sent to TeraRecon. Then, the length of the conduit in the center of the coronal plane of each image was measured 30 times after reconstructing the images using volume rendering and maximum intensity projection techniques. For conventional angiography, three-dimensional rotational angiography and two-dimensional digital subtraction angiography were used. Images obtained by three-dimensional rotational angiography were reconstructed and enhanced by 33, 50, and 100 % in the 128 Matrix and the 256 Matrix, respectively on the Xtra Vision workstation. The maximum intensity projection was used for the reconstruction, and the length of the conduit was measured 30 times in the center of the coronal plane of each image. Measurements using the two-dimensional digital subtraction angiography were obtained 30 times in the center of the image. As a result, the lumen length measured by three-dimensional enhanced flow MR angiography images was a minimum of 2.51 ± 0.12 mm when the fluid velocity was 40 cm/s. The images obtained by computed tomography angiography were larger than the actual images obtained by using the test equipment and the reconstruction method. Among the reconstruction methods of three-dimensional rotational angiography, the lumen length in the image reconstructed by 100 % in the 256 matrix was the smallest; 2.76 ± 0.009 mm. In the 128 matrix, as the scope of reconstruction was widened, the length of the vessel was increased by 0.710 units. In the 256 matrix, as the scope of reconstruction was widened, the length of the vessel was decreased by 0.972 units. In two-dimensional digital subtraction angiography, the lumen length in the image was 2.22 ± 0.095 mm. Although this image was magnified similar to the image reconstructed by 100 % in ...

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DWT-Based Segmentation Method for Coronary Arteries

Cited by 9 publications

References 19 publications

Brain MR Image Segmentation with Spatial Constrained K-mean Algorithm and Dual-Tree Complex Wavelet Transform

Brain MR Image Segmentation with Spatial Constrained K-mean Algorithm and Dual-Tree Complex Wavelet Transform

Processing of CT Lung Images as a Part of Radiomics

Analysis of Enlarged Images Using Time-of-Flight Magnetic Resonance Angiography, Computed Tomography, and Conventional Angiography

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