A new combined prior based reconstruction method for compressed sensing in 3D ultrasound imaging

2015 ◽  
Author(s):  
Muhammad S. Uddin ◽  
Rafiqul Islam ◽  
Murat Tahtali ◽  
Andrew J. Lambert ◽  
Mark R. Pickering
Keyword(s):  
Compressed Sensing ◽  
Ultrasound Imaging ◽  
3D Ultrasound ◽  
Reconstruction Method

GPU-accelerated Kernel Regression Reconstruction for Freehand 3D Ultrasound Imaging

2017 ◽  
Vol 39 (4) ◽  
pp. 240-259 ◽  
Author(s):  
Tiexiang Wen ◽  
Ling Li ◽  
Qingsong Zhu ◽  
Wenjian Qin ◽  
Jia Gu ◽  
...  
Keyword(s):  
Image Quality ◽  
Ultrasound Imaging ◽  
Kernel Regression ◽  
3D Ultrasound ◽  
Speckle Reduction ◽  
Reconstruction Method ◽  
Processing Unit ◽  
Hole Filling ◽  
Volume Reconstruction ◽  
Computational Performance

Volume reconstruction method plays an important role in improving reconstructed volumetric image quality for freehand three-dimensional (3D) ultrasound imaging. By utilizing the capability of programmable graphics processing unit (GPU), we can achieve a real-time incremental volume reconstruction at a speed of 25-50 frames per second (fps). After incremental reconstruction and visualization, hole-filling is performed on GPU to fill remaining empty voxels. However, traditional pixel nearest neighbor–based hole-filling fails to reconstruct volume with high image quality. On the contrary, the kernel regression provides an accurate volume reconstruction method for 3D ultrasound imaging but with the cost of heavy computational complexity. In this paper, a GPU-based fast kernel regression method is proposed for high-quality volume after the incremental reconstruction of freehand ultrasound. The experimental results show that improved image quality for speckle reduction and details preservation can be obtained with the parameter setting of kernel window size of [Formula: see text] and kernel bandwidth of 1.0. The computational performance of the proposed GPU-based method can be over 200 times faster than that on central processing unit (CPU), and the volume with size of 50 million voxels in our experiment can be reconstructed within 10 seconds.

A novel Bayesian-based nonlocal reconstruction method for freehand 3D ultrasound imaging

2015 ◽  
Vol 168 ◽  
pp. 104-118 ◽  
Author(s):  
Tiexiang Wen ◽  
Feng Yang ◽  
Jia Gu ◽  
Lei Wang
Keyword(s):  
Ultrasound Imaging ◽  
3D Ultrasound ◽  
Reconstruction Method ◽  
Freehand 3D Ultrasound

scholarly journals Validation of Scolioscan Air-Portable Radiation-Free Three-Dimensional Ultrasound Imaging Assessment System for Scoliosis

Sensors ◽  
2021 ◽  
Vol 21 (8) ◽  
pp. 2858
Author(s):  
Kelly Ka-Lee Lai ◽  
Timothy Tin-Yan Lee ◽  
Michael Ka-Shing Lee ◽  
Joseph Chi-Ho Hui ◽  
Yong-Ping Zheng
Keyword(s):  
Ultrasound Imaging ◽  
Imaging System ◽  
Outcome Measurement ◽  
Three Dimensional ◽  
3D Ultrasound ◽  
Mean Difference ◽  
Assessment System ◽  
Absolute Difference ◽  
Data Sets ◽  
Low Profile

To diagnose scoliosis, the standing radiograph with Cobb’s method is the gold standard for clinical practice. Recently, three-dimensional (3D) ultrasound imaging, which is radiation-free and inexpensive, has been demonstrated to be reliable for the assessment of scoliosis and validated by several groups. A portable 3D ultrasound system for scoliosis assessment is very much demanded, as it can further extend its potential applications for scoliosis screening, diagnosis, monitoring, treatment outcome measurement, and progress prediction. The aim of this study was to investigate the reliability of a newly developed portable 3D ultrasound imaging system, Scolioscan Air, for scoliosis assessment using coronal images it generated. The system was comprised of a handheld probe and tablet PC linking with a USB cable, and the probe further included a palm-sized ultrasound module together with a low-profile optical spatial sensor. A plastic phantom with three different angle structures built-in was used to evaluate the accuracy of measurement by positioning in 10 different orientations. Then, 19 volunteers with scoliosis (13F and 6M; Age: 13.6 ± 3.2 years) with different severity of scoliosis were assessed. Each subject underwent scanning by a commercially available 3D ultrasound imaging system, Scolioscan, and the portable 3D ultrasound imaging system, with the same posture on the same date. The spinal process angles (SPA) were measured in the coronal images formed by both systems and compared with each other. The angle phantom measurement showed the measured angles well agreed with the designed values, 59.7 ± 2.9 vs. 60 degrees, 40.8 ± 1.9 vs. 40 degrees, and 20.9 ± 2.1 vs. 20 degrees. For the subject tests, results demonstrated that there was a very good agreement between the angles obtained by the two systems, with a strong correlation (R2 = 0.78) for the 29 curves measured. The absolute difference between the two data sets was 2.9 ± 1.8 degrees. In addition, there was a small mean difference of 1.2 degrees, and the differences were symmetrically distributed around the mean difference according to the Bland–Altman test. Scolioscan Air was sufficiently comparable to Scolioscan in scoliosis assessment, overcoming the space limitation of Scolioscan and thus providing wider applications. Further studies involving a larger number of subjects are worthwhile to demonstrate its potential clinical values for the management of scoliosis.

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