scholarly journals Performance of PROPELLER FSE T2WI in Reducing Metal Artifacts for Patients with Various Material Porcelain Fused To Metal Crown: A Preliminary Study

2022 ◽  
Author(s):  
Wenjin Li ◽  
Jing Shi ◽  
Wenjin Bian ◽  
Jianting Li ◽  
Xiaoqing Chen ◽  
...  
Keyword(s):  
Image Quality ◽  
Signal To Noise Ratio ◽  
Spin Echo ◽  
Pure Titanium ◽  
Fast Spin Echo ◽  
Cobalt Chromium ◽  
Signal To Noise ◽  
Metal Artifacts ◽  
Pd Alloy ◽  
Noise Ratio

Abstract This study aimed to compare MRI quality between common fast spin echo T2 weighted imaging (FSE T2WI) with periodically rotated overlapping parallel lines with enhanced reconstruction (PROPELLER) FSE T2WI for patients with various porcelain fused to metal (PFM) crown and analyze the value of PROPELLER technique in reducing metal artifacts. Common FSE T2WI and PROPELLER FSE T2WI sequences for axial imaging of head were applied in participants with different PFM crowns: cobalt-chromium (Co-Cr) alloy, pure titanium (Ti), gold-palladium (Au-Pd) alloy. Two radiologists evaluated overall image quality of section in PFM using a 5-point scale qualitatively and measured the maximum artifact area and artifact signal-to-noise ratio (SNR) quantitatively. The metal crown with the least artifacts and the optimum image quality shown in common FSE T2WI and PROPELLER FSE T2WI were in Au–Pd alloy, Ti, and Co–Cr alloy order. PROPELLER FSE T2WI was superior to common FSE T2WI in improving image quality and reducing artifact area for Co-Cr alloy (17.0±0.2% smaller artifact area, p＜0.001) and Ti (11.6± 0.7 % smaller artifact area, p=0.005), but had similar performance compared to FSE T2WI for Au-Pd alloy. For all PFMs, PROPELLER FSE T2WI significantly reduced the signal-to-noise ratio (SNR) of artifact (393.57±89.75 VS. 214.05±70.45, p < 0.001) when compared to common FSE T2WI.Therefore, the different PFM crown generate varying degrees of metal artifacts in MRI, and the PROPELLER can effectively reduce metal artifacts especially in the PFM crown of Co-Cr alloy.

scholarly journals Analisis Variasi Time Repetition (TR) terhadap Signal to Noise Ratio dan Contrast to Noise Ratio pada Pemeriksaan MRI Cervical T2 Weighted Fast Spin Echo (FSE) Potongan Sagital

2016 ◽  
Vol 2 (1) ◽  
pp. 119-123
Author(s):  
Rini Indrati ◽  
Heriansyah Heriansyah ◽  
Wakhrudin Wakhrudin
Keyword(s):  
Signal To Noise Ratio ◽  
Spin Echo ◽  
Fast Spin Echo ◽  
Mean Deviation ◽  
P Value ◽  
Signal To Noise ◽  
Mri Examination ◽  
Spin Echo Sequence ◽  
Noise Ratio ◽  
Fast Spin

Background: Time Repetition (TR) is one parameter that can affect the value of Signal to Noise Ratio (SNR) and Contrast to Noise Ratio (CNR). The purpose of this research is to know the effect of variation of TR value on SNR and CNR on cervical MRI examination with Sagital T2 Weighted Fast Spin Echo sequence and to know the most optimal TR value from the variation of TR value to SNR and CNR on cervical MRI examination with Sagital T2 Weighted Fast Spin Echo.Methods: The type of this study was experimental study. The study was conducted using MRI 1.5 Tesla at Kasih Ibu Denpasar Hospital. Data were 40 MRI cervical images of sagital Fast Spin Echo from 10 volunteers with four variations of TR (2500 ms, 3000 ms, 3500 ms, and 4000 ms). The SNR and CNR values are measured by identifying the Region of Interest (ROI) in the corpus, discus, cerebro spinal fluid (CSF), and medula spinalis regions to obtain the average signals and compared with the mean deviation of the background. Data was analyzed by regression test to know the influence and by Anova test.Results: The result of the research showed that there was the influence of TR value to SNR and CNR of MRI Cervical Sagital T2 FSE. There was a strong correlation between the variation of TR values with SNR and CNR Cervical with p-value 0.05, the optimal TR value obtained in Cervical Sagital T2 FSE anatomical image on MRI 1,5 Tesla modality was 3500 ms.Conclusion: Time Repetition affected the signal to noise ratio and contrast to noise ratio. TR 3500 ms produced the most optimal cervical MRI image quality.

scholarly journals Analisis Pengaruh Perubahan Number Scan Average Terhadap Signal to Noise Ratio Pada Citra MRI Brain Sekuen T2 Fast Spin Echo (FSE)

2019 ◽  
Vol 21 (1) ◽  
pp. 1
Author(s):  
Rakhmat Kurniawan ◽  
Puji Hartoyo ◽  
Ni Larasati Kartika Sari
Keyword(s):  
Signal To Noise Ratio ◽  
Spin Echo ◽  
Median Filter ◽  
Fast Spin Echo ◽  
Signal To Noise ◽  
Mri Brain ◽  
Noise Ratio ◽  
Fast Spin

<div style="’text-align: justify;">Telah dilakukan penelitian tentang pengaruh perubahan nilai parameter Number Scan Average (NSA) terhadap kualitas citra MRI yang direpresentasikan oleh nilai Signal to Noise Ratio (SNR). Penelitian dilakukan menggunakan citra otak potongan aksial menggunakan sekuen T2 Fast Spin Echo. Variasi nilai NSA yang digunakan adalah 2, 4 dan 6. Nilai SNR dihitung memanfaatkan algoritma median filter pada software Matlab 2013a. SNR diperoleh dengan membandingkan nilai piksel rata-rata dari citra setelah diberi median filter dengan nilai piksel rata-rata dari selisih citra sebelum dan sesudah diberi median filter. Nilai SNR pada NSA 2,4 dan 6 masing-masing sebesar 81,3411, 85,8796, dan 87,2757. Hal tersebut menunjukkan bahwa semakin besar nilai NSA, semakin besar pula nilai SNR yang diperoleh. Kenaikan NSA dari 2 ke 4, meningkatkan NSA sebesar 5,6%, dan perubahan NSA dari 4 ke 6, meningkatkan SNR sebanyak 1,6%. Namun, kenaikan nilai NSA juga menambah waktu scanning. Kenaikan NSA dari 2 ke 4, dan 4 ke 6, menambah waktu scanning rata-rata sebesar 2 menit.</div>

Image Quality Enhancing by Efficient Histogram Equalization

2014 ◽  
Vol 2 (2) ◽  
pp. 47-58
Author(s):  
Ismail Sh. Baqer
Keyword(s):  
Image Quality ◽  
Contrast Enhancement ◽  
Mean Squared Error ◽  
Signal To Noise Ratio ◽  
Histogram Equalization ◽  
Gray Level ◽  
Signal To Noise ◽  
Squared Error ◽  
Noise Ratio

A two Level Image Quality enhancement is proposed in this paper. In the first level, Dualistic Sub-Image Histogram Equalization DSIHE method decomposes the original image into two sub-images based on median of original images. The second level deals with spikes shaped noise that may appear in the image after processing. We presents three methods of image enhancement GHE, LHE and proposed DSIHE that improve the visual quality of images. A comparative calculations is being carried out on above mentioned techniques to examine objective and subjective image quality parameters e.g. Peak Signal-to-Noise Ratio PSNR values, entropy H and mean squared error MSE to measure the quality of gray scale enhanced images. For handling gray-level images, convenient Histogram Equalization methods e.g. GHE and LHE tend to change the mean brightness of an image to middle level of the gray-level range limiting their appropriateness for contrast enhancement in consumer electronics such as TV monitors. The DSIHE methods seem to overcome this disadvantage as they tend to preserve both, the brightness and contrast enhancement. Experimental results show that the proposed technique gives better results in terms of Discrete Entropy, Signal to Noise ratio and Mean Squared Error values than the Global and Local histogram-based equalization methods

Model-based reconstruction algorithm in the detection of acute trauma-related lesions in brain CT examinations

2021 ◽  
pp. 197140092110087
Author(s):  
Andrea De Vito ◽  
Cesare Maino ◽  
Sophie Lombardi ◽  
Maria Ragusi ◽  
Cammillo Talei Franzesi ◽  
...  
Keyword(s):  
Image Quality ◽  
Iterative Reconstruction ◽  
Signal To Noise Ratio ◽  
Reconstruction Algorithm ◽  
Signal To Noise ◽  
Subjective Image Quality ◽  
Model Based ◽  
Hybrid Iterative Reconstruction ◽  
Noise Ratio ◽  
Enhanced Computed Tomography

Background and purpose To evaluate the added value of a model-based reconstruction algorithm in the assessment of acute traumatic brain lesions in emergency non-enhanced computed tomography, in comparison with a standard hybrid iterative reconstruction approach. Materials and methods We retrospectively evaluated a total of 350 patients who underwent a 256-row non-enhanced computed tomography scan at the emergency department for brain trauma. Images were reconstructed both with hybrid and model-based iterative algorithm. Two radiologists, blinded to clinical data, recorded the presence, nature, number, and location of acute findings. Subjective image quality was performed using a 4-point scale. Objective image quality was determined by computing the signal-to-noise ratio and contrast-to-noise ratio. The agreement between the two readers was evaluated using k-statistics. Results A subjective image quality analysis using model-based iterative reconstruction gave a higher detection rate of acute trauma-related lesions in comparison to hybrid iterative reconstruction (extradural haematomas 116 vs. 68, subdural haemorrhages 162 vs. 98, subarachnoid haemorrhages 118 vs. 78, parenchymal haemorrhages 94 vs. 64, contusive lesions 36 vs. 28, diffuse axonal injuries 75 vs. 31; all P<0.001). Inter-observer agreement was moderate to excellent in evaluating all injuries (extradural haematomas k=0.79, subdural haemorrhages k=0.82, subarachnoid haemorrhages k=0.91, parenchymal haemorrhages k=0.98, contusive lesions k=0.88, diffuse axonal injuries k=0.70). Quantitatively, the mean standard deviation of the thalamus on model-based iterative reconstruction images was lower in comparison to hybrid iterative one (2.12 ± 0.92 vsa 3.52 ± 1.10; P=0.030) while the contrast-to-noise ratio and signal-to-noise ratio were significantly higher (contrast-to-noise ratio 3.06 ± 0.55 vs. 1.55 ± 0.68, signal-to-noise ratio 14.51 ± 1.78 vs. 8.62 ± 1.88; P<0.0001). Median subjective image quality values for model-based iterative reconstruction were significantly higher ( P=0.003). Conclusion Model-based iterative reconstruction, offering a higher image quality at a thinner slice, allowed the identification of a higher number of acute traumatic lesions than hybrid iterative reconstruction, with a significant reduction of noise.

Retinal Digital Image Quality Improvement as A Diabetes Retinopatic Disease Detection Effort

2020 ◽  
Vol 4 (2) ◽  
pp. 53-60
Author(s):  
Latifah Listyalina ◽  
Yudianingsih Yudianingsih ◽  
Dhimas Arief Dharmawan
Keyword(s):  
Image Processing ◽  
Diabetic Retinopathy ◽  
Image Quality ◽  
Digital Image ◽  
Signal To Noise Ratio ◽  
Histogram Equalization ◽  
Vital Role ◽  
Retinal Images ◽  
Signal To Noise ◽  
Noise Ratio

Image processing is a technical term useful for modifying images in various ways. In medicine, image processing has a vital role. One example of images in the medical world, namely retinal images, can be obtained from a fundus camera. The retina image is useful in the detection of diabetic retinopathy. In general, direct observation of diabetic retinopathy is conducted by a doctor on the retinal image. The weakness of this method is the slow handling of the disease. For this reason, a computer system is required to help doctors detect diabetes retinopathy quickly and accurately. This system involves a series of digital image processing techniques that can process retinal images into good quality images. In this research, a method to improve the quality of retinal images was designed by comparing the methods for adjusting histogram equalization, contrast stretching, and increasing brightness. The performance of the three methods was evaluated using Mean Square Error (MSE), Peak Signal to Noise Ratio (PSNR), and Signal to Noise Ratio (SNR). Low MSE values and high PSNR and SNR values indicated that the image had good quality. The results of the study revealed that the image was the best to use, as evidenced by the lowest MSE values and the highest SNR and PSNR values compared to other techniques. It indicated that adaptive histogram equalization techniques could improve image quality while maintaining its information.

Preliminary study of improved median filter using adaptively mask size in light microscopic image

Microscopy ◽  
2020 ◽  
Vol 69 (1) ◽  
pp. 31-36
Author(s):  
Ji-Youn Kim ◽  
Youngjin Lee
Keyword(s):  
Image Quality ◽  
Coefficient Of Variation ◽  
Signal To Noise Ratio ◽  
Median Filter ◽  
Microscopic Image ◽  
Signal To Noise ◽  
Mask Size ◽  
Preliminary Study ◽  
Noise Ratio ◽  
Image Details

Abstract This study aimed to develop and evaluate an improved median filter (IMF) with an adaptive mask size for light microscope (LM) images. We acquired images of the mouse first molar using a LM at 100× magnification. The images obtained using our proposed IMF were compared with those from a conventional median filter. Several parameters such as the contrast-to-noise ratio, coefficient of variation, no-reference assessments and peak signal-to-noise ratio were employed to evaluate the image quality quantitatively. The results demonstrated that the proposed IMF could effectively de-noise the LM images and preserve the image details, achieving a better performance than the conventional median filter.

scholarly journals Image multiplexing using residue number system coding over MIMO-OFDM communication system

2019 ◽  
Vol 9 (6) ◽  
pp. 4815
Author(s):  
Mohamed Ibrahim Youssif ◽  
Amr ElSayed Emam ◽  
Mohamed Abd ElGhany
Keyword(s):  
Image Quality ◽  
Communication System ◽  
Signal To Noise Ratio ◽  
Image Transmission ◽  
Number System ◽  
Residue Number System ◽  
Signal To Noise ◽  
Residue Number ◽  
Mimo Ofdm ◽  
Noise Ratio

<p>Image transmission over Orthogonal Frequency-Division Multiplexing (OFDM) communication system is prone to distortion and noise due to the encountered High-Peak-to-Average-Power-Ratio (PAPR) generated from the OFDM block. This paper studies the utilization of Residue Number System (RNS) as a coding scheme for digital image transmission over Multiple-Input-Multiple-Output (MIMO) – OFDM transceiver communication system. The use of the independent parallel feature of RNS, as well as the reduced signal amplitude to convert the input signal to parallel smaller residue signals, enable to reduce the signal PAPR, decreasing the signal distortion and the Bit Error Rate (BER). Consequently, improving the received Signal-to-Noise Ratio (SNR) and enhancing the received image quality. The performance analyzed though BER, and PAPR. Moreover, image quality measurement is achieved through evaluating the Mean Squared Error (MSE), Peak Signal to Noise Ratio (PSNR), and the correlation values between the initial and retrieved images. Simulation results had shown the performance of transmission/reception model with and without RNS coding implementation.</p><p> </p>

The Influence of Alteration of kVp and mAs towards the Image Quality of Acrylic Using CBCT

2019 ◽  
Vol 829 ◽  
pp. 252-257
Author(s):  
Azhari ◽  
Yohanes Hutasoit ◽  
Freddy Haryanto
Keyword(s):  
Image Quality ◽  
Signal To Noise Ratio ◽  
Region Of Interest ◽  
Signal To Noise ◽  
Bite Block ◽  
Significant Difference ◽  
Noise Ratio ◽  
Post Hoc ◽  
Radiograph Image

CBCT is a modernized technology in producing radiograph image on dentistry. The image quality excellence is very important for clinicians to interpret the image, so the result of diagnosis produced becoming more accurate, appropriate, thus minimizing the working time. This research was aimed to assess the image quality using the blank acrylic phantom polymethylmethacrylate (PMMA) (C­5H8O2)n in the density of 1.185 g/cm3 for evaluating the homogeneity and uniformity of the image produced. Acrylic phantom was supported with a tripod and laid down on the chin rest of the CBCT device, then the phantom was fixed, and the edge of the phantom was touched by the bite block. Furthermore, the exposure of the X-ray was executed toward the acrylic phantom with various kVp and mAs, from 80 until 90, with the range of 5 kV and the variation of mA was 3, 5, and 7 mA respectively. The time exposure was kept constant for 25 seconds. The samples were taken from CBCT acrylic images, then as much as 5 ROIs (Region of Interest) was chosen to be analyzed. The ROIs determination was analyzed by using the ImageJ® software for recognizing the influence of kVp and mAs towards the image uniformity, noise and SNR. The lowest kVp and mAs had the result of uniformity value, homogeneity and signal to noise ratio of 11.22; 40.35; and 5.96 respectively. Meanwhile, the highest kVp and mAs had uniformity value, homogeneity and signal to noise ratio of 16.96; 26.20; and 5.95 respectively. There were significant differences between the image uniformity and homogeneity on the lowest kVp and mAs compared to the highest kVp and mAs, as analyzed with the ANOVA statistics analysis continued with the t-student post-hoc test with α = 0.05. However, there was no significant difference in SNR as analyzed with the ANOVA statistic analysis. The usage of the higher kVp and mAs caused the improvement of the image homogeneity and uniformity compared to the lower kVp and mAs.

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