Edge Detection Techniques for Quantifying Spatial Imaging System Performance and Image Quality

Multi-modality imaging provides coregistered PET-CT and SPECT-CT images; however such multi-modality workflows usually consist of sequential scans from the individual imaging components for each modality. This typical workflow may result in long scan times limiting throughput of the imaging system. Conversely, acquiring multi-modality data simultaneously may improve correlation and registration of images, improve temporal alignment of the acquired data, increase imaging throughput, and benefit the scanned subject by minimizing time under anesthetic. In this work, we demonstrate the feasibility and procedure for modifying a commercially available preclinical SPECT-CT platform to enable simultaneous SPECT-CT acquisition. We also evaluate the performance of simultaneous SPECT-CT tomographic imaging with this modified system. Performance was accessed using a 57Co source and image quality was evaluated with Tc99m phantoms in a series of simultaneous SPECT-CT scans.

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Imaging System Performance and Visibility as Affected by the Physical Environment

10.21236/ada572748 ◽

2012 ◽

Author(s):

Grace Chang

Keyword(s):

Physical Environment ◽

System Performance ◽

Imaging System

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Modeling and image quality enhancement for dynamic compressive imaging system

Journal of Algorithms & Computational Technology ◽

10.1177/17483026211008098 ◽

2021 ◽

Vol 15 ◽

pp. 174830262110080

Author(s):

Changjun Zha* ◽

Qian Zhang* ◽

Huimin Duan

Keyword(s):

Image Quality ◽

Imaging System ◽

Quality Enhancement ◽

Target Image ◽

Compressive Imaging ◽

Image Quality Enhancement ◽

System A ◽

Single Column ◽

The Impact

Traditional single-pixel imaging systems are aimed mainly at relatively static or slowly changing targets. When there is relative motion between the imaging system and the target, sizable deviations between the measurement values and the real values can occur and result in poor image quality of the reconstructed target. To solve this problem, a novel dynamic compressive imaging system is proposed. In this system, a single-column digital micro-mirror device is used to modulate the target image, and the compressive measurement values are obtained for each column of the image. Based on analysis of the measurement values, a new recovery model of dynamic compressive imaging is given. Differing from traditional reconstruction results, the measurement values of any column of vectors in the target image can be used to reconstruct the vectors of two adjacent columns at the same time. Contingent upon characteristics of the results, a method of image quality enhancement based on an overlapping average algorithm is proposed. Simulation experiments and analysis show that the proposed dynamic compressive imaging can effectively reconstruct the target image; and that when the moving speed of the system changes within a certain range, the system reconstructs a better original image. The system overcomes the impact of dynamically changing speeds, and affords significantly better performance than traditional compressive imaging.

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Performance Evaluation of Dorsal Vein Network of Hand Imaging Using Relative Total Variation-Based Regularization for Smoothing Technique in a Miniaturized Vein Imaging System: A Pilot Study

International Journal of Environmental Research and Public Health ◽

10.3390/ijerph18041548 ◽

2021 ◽

Vol 18 (4) ◽

pp. 1548 ◽

Cited By ~ 1

Author(s):

Kyuseok Kim ◽

Hyun-Woo Jeong ◽

Youngjin Lee

Keyword(s):

Image Quality ◽

Total Variation ◽

Near Infrared ◽

Imaging System ◽

Histogram Equalization ◽

Evaluation Performance ◽

Visual Evaluation ◽

Évaluation Performance ◽

Nir Imaging ◽

Relative Total Variation

Vein puncture is commonly used for blood sampling, and accurately locating the blood vessel is an important challenge in the field of diagnostic tests. Imaging systems based on near-infrared (NIR) light are widely used for accurate human vein puncture. In particular, segmentation of a region of interest using the obtained NIR image is an important field, and research for improving the image quality by removing noise and enhancing the image contrast is being widely conducted. In this paper, we propose an effective model in which the relative total variation (RTV) regularization algorithm and contrast-limited adaptive histogram equalization (CLAHE) are combined, whereby some major edge information can be better preserved. In our previous study, we developed a miniaturized NIR imaging system using light with a wavelength of 720–1100 nm. We evaluated the usefulness of the proposed algorithm by applying it to images acquired by the developed NIR imaging system. Compared with the conventional algorithm, when the proposed method was applied to the NIR image, the visual evaluation performance and quantitative evaluation performance were enhanced. In particular, when the proposed algorithm was applied, the coefficient of variation was improved by a factor of 15.77 compared with the basic image. The main advantages of our algorithm are the high noise reduction efficiency, which is beneficial for reducing the amount of undesirable information, and better contrast. In conclusion, the applicability and usefulness of the algorithm combining the RTV approach and CLAHE for NIR images were demonstrated, and the proposed model can achieve a high image quality.

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Synthetic Aperture Imaging Using High-Frequency Convex Array for Ophthalmic Ultrasound Applications

Sensors ◽

10.3390/s21072275 ◽

2021 ◽

Vol 21 (7) ◽

pp. 2275

Author(s):

Hae Gyun Lim ◽

Hyung Ham Kim ◽

Changhan Yoon

Keyword(s):

Image Quality ◽

Penetration Depth ◽

Spatial Resolution ◽

High Frequency ◽

Imaging System ◽

Ex Vivo ◽

Synthetic Aperture ◽

Single Element ◽

High Frequency Ultrasound ◽

Synthetic Aperture Imaging

High-frequency ultrasound (HFUS) imaging has emerged as an essential tool for pre-clinical studies and clinical applications such as ophthalmic and dermatologic imaging. HFUS imaging systems based on array transducers capable of dynamic receive focusing have considerably improved the image quality in terms of spatial resolution and signal-to-noise ratio (SNR) compared to those by the single-element transducer-based one. However, the array system still suffers from low spatial resolution and SNR in out-of-focus regions, resulting in a blurred image and a limited penetration depth. In this paper, we present synthetic aperture imaging with a virtual source (SA-VS) for an ophthalmic application using a high-frequency convex array transducer. The performances of the SA-VS were evaluated with phantom and ex vivo experiments in comparison with the conventional dynamic receive focusing method. Pre-beamformed radio-frequency (RF) data from phantoms and excised bovine eye were acquired using a custom-built 64-channel imaging system. In the phantom experiments, the SA-VS method showed improved lateral resolution (>10%) and sidelobe level (>4.4 dB) compared to those by the conventional method. The SNR was also improved, resulting in an increased penetration depth: 16 mm and 23 mm for the conventional and SA-VS methods, respectively. Ex vivo images with the SA-VS showed improved image quality at the entire depth and visualized structures that were obscured by noise in conventional imaging.

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