scholarly journals A novel method to assess the spatiotemporal image quality in fluoroscopy

2021 ◽  
Author(s):  
Pascal Monnin ◽  
Anaïs Viry ◽  
Jérôme Damet ◽  
Marie Nowak ◽  
Veronika Vitzthum ◽  
...  
Keyword(s):  
Image Processing ◽  
Image Quality ◽  
Temporal Resolution ◽  
Temporal Frequency ◽  
Image Plane ◽  
Dynamic Imaging ◽  
Rectilinear Motion ◽  
Multiple Parameters ◽  
Frame System

Abstract Objectives. The planar formulation of the noise equivalent quanta (NEQ) and detective quantum efficiency (DQE) used to assess the image quality of projection images does not deal with the influence of temporal resolution on signal blurring and image noise. These metrics require correction factors based on temporal resolution when used for dynamic imaging systems such as fluoroscopy. Additionally, the standard NEQ and detector DQE are determined on pre-processed images in scatter-free conditions for effective energies produced by additional aluminium or copper filters that are not representative of clinical fluoroscopic procedures. In this work, we developed a method to measure “frame NEQ” and “frame system DQE” which include the temporal frequency bandwidth and consider the anti-scatter grid, the detector and the image processing procedures for beam qualities with scatter fractions representative of clinical use. Approach. We used a solid water phantom to simulate a patient and a thin copper disc to measure the spatial resolution. The copper disc, set in uniform rectilinear motion in the image plane, assessed the temporal resolution. These new metrics were tested on two fluoroscopy systems, a C-arm and a floor-mounted cardiology, for multiple parameters: phantom thicknesses from 5 to 20 cm, frame rates from 3 to 30 fps, spatial and temporal image processing of different weights. Main results. The frame NEQ correctly described the image quality for different scatter conditions, temporal resolutions and image processing techniques. The frame system DQE varied between 0.38 and 0.65 within the different beam and scatter conditions, and correctly mitigated the influence of spatial and temporal image processing. Significance. This study introduces and validates an unbiased formulation of in-plane NEQ and system DQE to assess the spatiotemporal image quality of fluoroscopy systems.

scholarly journals Implementasi Metode Super Resolusi Untuk Meningkatkan Kualitas Citra Hasil Screenshot

2020 ◽  
Vol 7 (3) ◽  
pp. 432
Author(s):  
Windi Astuti
Keyword(s):  
Image Processing ◽  
Image Quality ◽  
Median Filter ◽  
Super Resolution ◽  
Linear Interpolation ◽  
Resolution Method ◽  
Image Zooming ◽  
Image Enlargement ◽  
Three Stages

Various types of image processing that can be done by computers, such as improving image quality is one of the fields that is quite popular until now. Improving the quality of an image is necessary so that someone can observe the image clearly and in detail without any disturbance. An image can experience major disturbances or errors in an image such as the image of the screenshot is used as a sample. The results of the image from the screenshot have the smallest sharpness and smoothness of the image, so to get a better image is usually done enlargement of the image. After the screenshot results are obtained then, the next process is cropping the image and the image looks like there are disturbances such as visible blur and cracked. To get an enlarged image (Zooming image) by adding new pixels or points. This is done by the super resolution method, super resolution has three stages of completion, first Registration, Interpolation, and Reconstruction. For magnification done by linear interpolation and reconstruction using a median filter for image refinement. This method is expected to be able to solve the problem of improving image quality in image enlargement applications. This study discusses that the process carried out to implement image enlargement based on the super resolution method is then built by using R2013a matlab as an editor to edit programs

Study on Image Processing of Wheel Valve Hole Based on Machine Vision

2011 ◽  
Vol 63-64 ◽  
pp. 541-546 ◽  
Author(s):  
Chang Chun Li ◽  
Shi Feng Wang ◽  
Jing Yu ◽  
Hua Guan Liu
Keyword(s):  
Image Processing ◽  
Image Quality ◽  
Machine Vision ◽  
Edge Detection ◽  
Basic Principle ◽  
Image Acquisition ◽  
Wheel Speed ◽  
Hole Edge

This paper discusses the basic principle for automatic searching the wheel valve hole based on machine vision. Image acquisition and image processing have been done, and we analyzed the factors that impact the image quality of wheel valve hole. This paper argues that many parameters such as the wheel speed, painting color, the distance between the camera and the valve hole, edge detection operator, and they will affect the quality of the image acquisition and image processing of valve hole.

scholarly journals THE APPLICATION OF USING GEL PAD AS A MEDIUM FOR ULTRASOUND SHOULDER

2020 ◽  
Vol 4 (2) ◽  
pp. 66
Author(s):  
Lelly Agustina Sisparwati ◽  
Rosy Setiawati ◽  
Berliana Devianti Putri
Keyword(s):  
Image Processing ◽  
Image Quality ◽  
Short Axis ◽  
Conductive Medium ◽  
Questionnaire Assessment ◽  
Axis Position ◽  
Ultrasound Investigation ◽  
Radiology Image ◽  
Shoulder Examination

Background: A conductive medium on ultrasound is a medium that is used to obtain sound wave transmission by minimizing air between the transducer and the skin. This study used materials that are easily found such as gel wax and paraffin for making the gel pad. A good oil and mineral based wax gel are used as a basic ingredient for ultrasound gel making. Gel pad can be used to minimize the structure of unauthorized organs. One of which is the shoulder. Objective: This study aims to determine the quality of the image in the use of standard gel, and the use of gel pad as a medium for ultrasound shoulder. Method: Gel pad is made by mixing gel wax and paraffin ingredients. This gel is used to obtain images from ultrasound investigation. The study used 16 samples with a total of 64 images obtained in which 32 images using standard gel and gel pad in the long axis position and 32 images using standard gel and gel pad in the short axis position. The analysis of image results is done using matlab image processing to assess SNR. The image quality obtained from the results of the questionnaire was assessed by a specialist in radiology. Image quality processing based on SNR was tested using independent T test. Meanwhile, the results of image quality from the questionnaire assessment were tested using Wilcoxon. Result: As many as 64 objects were obtained using standard gel. The gel pad showed that there were significant differences in the results of image quality based on SNR values. In the results of the questionnaire assessment, there are several anatomic organs that have no significant differences. Conclusion: The use of standard gel was still higher compared to the use of gel pad. The gel pad is able to become a standard gel alternative on ultrasound shoulder examination.

scholarly journals Computational Efficient Method for Denoising of Salt and Pepper Noise for Image Enhancement

2020 ◽  
Vol 8 (6) ◽  
pp. 538-543
Keyword(s):  
Image Processing ◽  
Image Quality ◽  
Median Filter ◽  
Noise Removal ◽  
Input Image ◽  
Filter Method ◽  
Pixel Intensity ◽  
Feature Information ◽  
Salt And Pepper

Digital Image processing is basically a computer-algorithm which is used to enhance the quality of image to understand the feature of image and exact the meaningful features information from image. Image processing has wider range of algorithms to be applied to the input image and can escape the difficulty as the signal distortion and add noise in input image at the time of processing of images. Noises affect the image visualization and degraded the image quality, sometimes chaotic variation in value of pixel intensity, lighting effect or because of poor contrast, image can’t be used directly because many time interest feature information not received as output that’s one reason image processing is significant for removal of noise from images, so noise removal is becomes trending field in image processing. Median filter method is one of most popular method to eradicate the effect of noise from image and it enhances the image quality to take meaningful feature easily from image. In this paper removing of noise using median filter to enhance the image quality is discussed, also the importance and applications of enhancement technique are covered. Parameter PSNR and MSE is also used to analysis the image quality along with the visualization of image. Simulation results show that Median filter gives good outcome for salt & pepper noise as compare to other filtering method. MATLAB software is used as simulation tool.

scholarly journals Challenges in Curating 2D Multimedia Data in the Application of Machine Learning in Biodiversity Image Analysis

2021 ◽  
Vol 5 ◽  
Author(s):  
Yasin Bakış ◽  
Xiaojun Wang ◽  
Hank Bart
Keyword(s):  
Neural Network ◽  
Machine Learning ◽  
Image Processing ◽  
Image Analysis ◽  
Image Quality ◽  
Multimedia Data ◽  
Computational Techniques ◽  
Search Results ◽  
Quality Issues

Over 1 billion biodiversity collection specimens ranging from fungi to fish to fossils are housed in more than 1,600 natural history collections across the United States. The digitization of these specimens has risen significantly within the last few decades and this is only likely to increase, as the use of digitized data gains more importance every day. Numerous experiments with automated image analysis have proven the practicality and usefulness of digitized biodiversity images by computational techniques such as neural networks and image processing. However, most of the computational techniques to analyze images of biodiversity collection specimens require a good curation of this data. One of the challenges in curating multimedia data of biodiversity collection specimens is the quality of the multimedia objects—in our case, two dimensional images. To tackle the image quality problem, multimedia needs to be captured in a specific format and presented with appropriate descriptors. In this study we present an analysis of two image repositories each consisting of 2D images of fish specimens from several institutions—the Integrated Digitized Biocollections (iDigBio) and the Great Lakes Invasives Network (GLIN). Approximately 70 thousand images have been processed from the GLIN repository and 450 thousand images have been processed from the iDigBio repository and their suitability assessed for use in neural network-based species identification and trait extraction applications. Our findings showed that images that came from the GLIN dataset were more successful for image processing and machine learning purposes. Almost 40% of the species have been represented with less than 10 images while only 20% have more than 100 images per species. We identified and captured 20 metadata descriptors that define quality and usability of the image. According to the captured metadata information, 70% of the GLIN dataset images were found to be useful for further analysis according to the overall image quality score. Quality issues with the remaining images included: curved specimens, non-fish objects in the images such as tags, labels and rocks that obstructed the view of the specimen; color, focus and brightness issues; folded or overlapping parts as well as missing parts. We used both the web interface and the API (Application Programming Interface) for downloading images from iDigBio. We searched for all fish genera, families and classes in three different searches with the images-only option selected. Then we combined all of the search results and removed duplicates. Our search on the iDigBio database for fish taxa returned approximately 450 thousand records with images. We narrowed this down to 90 thousand fish images aided by the multimedia metadata with the downloaded search results, excluding some non-fish images, fossil samples, X-ray and CT (computed tomography) scans and several others. Only 44% of these 90 thousand images were found to be suitable for further analysis. In this study, we discovered some of the limitations of biodiversity image datasets and built an infrastructure for assessing the quality of biodiversity images for neural network analysis. Our experience with the fish images gathered from two different image repositories has enabled describing image quality metadata features. With the help of these metadata descriptors, one can simply create a dataset for a desired image quality for the purpose of analysis. Likewise, the availability of the metadata descriptors will help advance our understanding of quality issues, while helping data technicians, curators and the other digitization staff be more aware of multimedia.

scholarly journals The object detection system of balinese script on traditional Balinese manuscript with findcontours method

2021 ◽  
Vol 11 (3) ◽  
pp. 177-184
Author(s):  
Putra Manuaba ◽  
◽  
Komang Ayu Triana Indah ◽  
Keyword(s):  
Image Processing ◽  
Image Quality ◽  
Edge Detection ◽  
Object Detection ◽  
Detection System ◽  
Main Issue ◽  
Age Factor

Lontar is a traditional Balinese manuscript with a Balinese script in it. Balinese traditional manuscripts can be more than 100 years old. The age factor of the Balinese manuscript has an impact on the Balinese script in it. Balinese script that has been written more than 10 years tends to be darker. This makes Balinese script not visible well, and this affects the image quality of the manuscript. This thing becomes the main issue in this research, Balinese script detection on Balinese manuscript images. the first of all is image processing using edge detection, canny and Sobel becomes the main algorithm of this process. After image processing, the Balinese manuscript will be processed with the findcontour method to detect an object that contains in it. The final process of this detection system is to separate detected objects into three main groups namely noise object, Balinese script object, and hole object. Application (Balinese script object detection system) is more accurate in detecting Balinese script objects in Balinese script under 1 year (new script), it tends to be more likely to find noise/dirt. This is because the writing of the lontar using a pencil first before using the knife media. This adds to the noise or dirt detected by the application The findcontour method can detect Balinese script objects with a detection result of 30% - 70% Balinese script objects.

Effective temporal resolution and image quality of volume scanning in 320-row detector CT

2019 ◽  
Vol 42 (2) ◽  
pp. 503-510 ◽  
Author(s):  
Atsushi Urikura ◽  
Takanori Hara ◽  
Tsukasa Yoshida ◽  
Eiji Nishimaru ◽  
Takashi Hoshino ◽  
...  
Keyword(s):  
Image Quality ◽  
Temporal Resolution
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