scholarly journals Optimization dose and image quality enhancement of ct scan with back projection filters on the use of automatic exposure control

2021 ◽  
Vol 1943 (1) ◽  
pp. 012048
Author(s):  
L Fitriana ◽  
K Adi ◽  
J Ardiyanto
Keyword(s):  
Image Quality ◽  
Ct Scan ◽  
Quality Enhancement ◽  
Exposure Control ◽  
Automatic Exposure Control ◽  
Back Projection ◽  
Image Quality Enhancement

scholarly journals Automatic Exposure Control And Fixed mA Technique To Radiation Dose And Image Quality On Non Contrast Urology CT Scan

2021 ◽  
Vol 16 (1) ◽  
pp. 8
Author(s):  
Sariyanto Ginanjar Kartasasmita ◽  
Mayarani Mayarani ◽  
Novan Hendra Hariyanto
Keyword(s):  
Computed Tomography ◽  
Image Quality ◽  
Radiation Dose ◽  
Ct Scan ◽  
Exposure Control ◽  
Automatic Exposure Control

Penelitian ini bertujuan untuk membandingkan nilai dosis radiasi dan kualitas gambar pada pemeriksaan CT Scanurologi non kontras dengan perbedaan teknik Automatic Exposure Control(AEC) dan teknik fixed mA. Desain penelitian ini adalah kuantitatif analitik. Penelitian ini dilakukan di Instalasi Radiologi RS Swasta di Jakarta Utara pada bulan Agustus – Oktober 2019. Jumlah sampel dari penelitian ini adalah 40 orang dengan empat perbedaan perlakuan dan masing-masing perlakuan berjumlah 10 pasien yang dipilih berdasarkan kriteria inklusi dan eksklusi. Metode pengumpulan data yang digunakan berupa observasi dan dokumentasi. Instrumen penelitian yang digunakan yaitu lembar kerja untuk mencatat data selama penelitian berlangsung dan komputer AdvantageWorkstation Computed Tomography ( AWCT) untuk mengukur nilai atau kualitas citra gambar CT Scan.Pengolahan dan analisis hasil data menggunakan program komputasi. Hasil dari penelitian penggunaan teknik Automatic Exposure Control(AEC) dapat memberikan dosis radiasi yang optimal dengan kualitas gambar CT Scan yang lebih baik dibandingkan dengan teknik fixed mA. Meskipun teknik fixed mA100 dapat memberikan nilai dosis radiasi yang lebih kecil dibandingkan teknik AEC tetapi menghasilkan kualitas gambar yang kurang baik

scholarly journals ANALYSIS OF THE EFFECT OF CARE DOSE 4D SOFTWARE USE ON IMAGE QUALITY AND RADIATION DOSE ON THE CT SCAN ABDOMEN

2020 ◽  
Vol 5 (1) ◽  
pp. 31-40
Author(s):  
Ni Larasati Kartika Sari ◽  
Merry Suzana ◽  
Muzilman Muslim ◽  
Dewi Muliyati
Keyword(s):  
Image Quality ◽  
Radiation Dose ◽  
Power Spectrum ◽  
Ct Scan ◽  
Noise Power ◽  
Exposure Control ◽  
Automatic Exposure Control ◽  
Ct Number ◽  
Still Image ◽  
Reduced Dose

The CT Scan is the most significant contributor to radiation dose on radiological examination, although the frequency of the examination is far below other modalities. In order to control this radiation dose, manufactures of CT Scan have equipped their units with built-in software called Automatic Exposure Control (AEC). This study aims to analyze the effect of AEC software, CARE Dose 4D, on image quality, and CTDIvol. Objects used in this study were three water phantoms, each with a diameter of 165 mm, 230 mm, and 305 mm. The image quality-analyzed was CT Number and noise. Measurement of image quality was carried out following Bapeten's provisions. Noise Power Spectrum (NPS) graphics were also used to further observes noise texture. The CT Number accuracy, CT Number, and noise uniformity obtained with and without CARE Dose 4D, on the three phantoms were still within Bapeten's threshold. This indicates that the use of CARE Dose 4D can still image a homogeneous object accurately. The results of the NPS curve showed that the two modes, in three phantoms, were having the same noise texture. The NPS curves also showed that the use of CARE Dose 4D produces higher noise than the non-CARE Dose 4D mode. Meanwhile, there were significant differences from the CTDIvol obtained from the two modes. The use of CARE Dose 4D software reduced dose of up to 54.34%. From this, the use of CARE Dose 4D software can reduce the radiation dose while maintaining image quality.

Interactive Image Quality Enhancement Support System by Tone Curve Correction Based on Human KANSEI

2009 ◽  
Vol 129 (6) ◽  
pp. 593-600 ◽  
Author(s):  
Yuichiro Tokuda ◽  
Gosuke Ohashi ◽  
Masato Tsukada ◽  
Reiichi Kobayashi ◽  
Yoshifumi Shimodaira
Keyword(s):  
Image Quality ◽  
Support System ◽  
Quality Enhancement ◽  
Curve Correction ◽  
Image Quality Enhancement

Deep Learning Approaches for Whiteboard Image Quality Enhancement

2019 ◽  
Vol 2019 (1) ◽  
pp. 360-368
Author(s):  
Mekides Assefa Abebe ◽  
Jon Yngve Hardeberg
Keyword(s):  
Deep Learning ◽  
Image Quality ◽  
Image Data ◽  
Quality Enhancement ◽  
Network Architectures ◽  
Learning Approaches ◽  
Data Set ◽  
Image Quality Enhancement ◽  
Processing Techniques ◽  
White Balancing

Different whiteboard image degradations highly reduce the legibility of pen-stroke content as well as the overall quality of the images. Consequently, different researchers addressed the problem through different image enhancement techniques. Most of the state-of-the-art approaches applied common image processing techniques such as background foreground segmentation, text extraction, contrast and color enhancements and white balancing. However, such types of conventional enhancement methods are incapable of recovering severely degraded pen-stroke contents and produce artifacts in the presence of complex pen-stroke illustrations. In order to surmount such problems, the authors have proposed a deep learning based solution. They have contributed a new whiteboard image data set and adopted two deep convolutional neural network architectures for whiteboard image quality enhancement applications. Their different evaluations of the trained models demonstrated their superior performances over the conventional methods.

scholarly journals Modeling and image quality enhancement for dynamic compressive imaging system

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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