scholarly journals Application of generalized method of least modules in problems of processing and analysing images

2020 ◽  
Vol 2020 (2) ◽  
pp. 45-55
Author(s):  
Vladimir Anatolevich Surin ◽  
Alexander Nikolaevich Tyrsin
Keyword(s):  
Medical Diagnostics ◽  
Nonlinear Filter ◽  
Nonlinear Filtration ◽  
Original Image ◽  
Acceptable Result ◽  
X Ray ◽  
Clustering Problem ◽  
Smoothing Filter ◽  
Brightness Difference ◽  
Nonlinear Smoothing

The article describes the use of nonlinear smoothing filter for image processing and analysis. Description of the model of the smoothing filter based on the generalized method of the least absolute values is given. The filter constructed on the basis of the offered model efficiently reduces the noise on brightness difference. Along with noise reduction in the contrast images, this method can be used for the solving problems of machine vision, medical diagnostics, etc. It has been found that nonlinear filtration on the basis of the generalized method of the least modules allows to solve such problems as clarification of the boundaries of contrast objects and segmentation of the image. There has been shown the possibility of recovering the boundaries of the images in which the contrast borders were blurry. X-ray image of an animal hand with defocusing was used as an example. After filtering, the contrast boundary was restored to the place where it was originally located. When processing a fluorography image, the filter removed various artifacts from the image and increased the contrast. Removal of artifacts along with the recoveries of the boundaries of contrast objects improves the overall “readability” of the fluorography image and also allows seeing earlier not distinguishable details on the image. Examples of the filter application in the clustering problem using the k-means algorithm are given. Due to the lack of this algorithm, applying it directly to the image does not give an acceptable result. However, after processing the original image with a nonlinear filter, the application of the k-means algorithm yields the desired result.

Performance Evaluation of Convolutional Neural Network Using Synthetic Medical Data Augmentation Generated by GAN

2021 ◽  
Author(s):  
Ramesh Adhikari ◽  
Suresh Pokharel
Keyword(s):  
Neural Network ◽  
Neural Networks ◽  
Convolutional Neural Network ◽  
Data Augmentation ◽  
Medical Diagnostics ◽  
Generative Adversarial Networks ◽  
Generalization Capability ◽  
X Ray ◽  
Original Dataset ◽  
Unseen Data

Data augmentation is widely used in image processing and pattern recognition problems in order to increase the richness in diversity of available data. It is commonly used to improve the classification accuracy of images when the available datasets are limited. Deep learning approaches have demonstrated an immense breakthrough in medical diagnostics over the last decade. A significant amount of datasets are needed for the effective training of deep neural networks. The appropriate use of data augmentation techniques prevents the model from over-fitting and thus increases the generalization capability of the network while testing afterward on unseen data. However, it remains a huge challenge to obtain such a large dataset from rare diseases in the medical field. This study presents the synthetic data augmentation technique using Generative Adversarial Networks to evaluate the generalization capability of neural networks using existing data more effectively. In this research, the convolutional neural network (CNN) model is used to classify the X-ray images of the human chest in both normal and pneumonia conditions; then, the synthetic images of the X-ray from the available dataset are generated by using the deep convolutional generative adversarial network (DCGAN) model. Finally, the CNN model is trained again with the original dataset and augmented data generated using the DCGAN model. The classification performance of the CNN model is improved by 3.2% when the augmented data were used along with the originally available dataset.

scholarly journals A nonlinear edge –preserving smoothing filter for edge detection on color and gray satellite images

2019 ◽  
Vol 13 (26) ◽  
pp. 29-37
Author(s):  
Suhad A. Hamdan
Keyword(s):  
Edge Detection ◽  
Gaussian Noise ◽  
Satellite Images ◽  
Cross Correlation ◽  
Nonlinear Filter ◽  
Edge Preserving ◽  
Pass Filter ◽  
Low Pass Filter ◽  
Smoothing Filter ◽  
Low Pass

A nonlinear filter for smoothing color and gray imagescorrupted by Gaussian noise is presented in this paper. The proposedfilter designed to reduce the noise in the R,G, and B bands of thecolor images and preserving the edges. This filter applied in order toprepare images for further processing such as edge detection andimage segmentation.The results of computer simulations show that the proposedfilter gave satisfactory results when compared with the results ofconventional filters such as Gaussian low pass filter and median filterby using Cross Correlation Coefficient (ccc) criteria.

scholarly journals Recovering Past Reflections: X-Ray Fluorescence Imaging of Electrocleaned 19th Century Daguerreotypes

Heritage ◽  
2019 ◽  
Vol 2 (1) ◽  
pp. 568-586
Author(s):  
Madalena S. Kozachuk ◽  
Tsun-Kong Sham ◽  
Ronald R. Martin ◽  
Andrew J. Nelson ◽  
Ian Coulthard ◽  
...  
Keyword(s):  
Fluorescence Imaging ◽  
19Th Century ◽  
Particle Density ◽  
Electrochemical Process ◽  
X Rays ◽  
Original Image ◽  
X Ray ◽  
Restoration Method ◽  
Physical And Chemical ◽  
X Ray Absorption

The first commercially viable photographic image, the daguerreotype, captured imagesfor a span of approximately 20 years (1839–1860). Deterioration now disfigures many of thesevaluable images. One proposed restoration method is an electrochemical process. However, itssafety and effectiveness are still under debate within the conservation community as the effects ofthis treatment, and its physical and chemical impact on the daguerreotype image, have not yet beenanalyzed in depth. This study used synchrotron-based micro-X-ray fluorescence to map theelemental distribution pre- and post-electrocleaning on 19th century daguerreotypes using both softand hard incident X-rays. X-ray absorption spectroscopy was used to probe local chemistry beforeand after cleaning. Two different electro-treatment methods were compared: the original methodproposed by Barger and a second put forward by Wei. When used correctly, both processessignificantly reduced the S and Cl surface contamination without dulling the surface. However,both electrochemical methods used in this study resulted in a loss of Hg and Au from the surface.In all cases, the Hg distribution tracks with image particle density allowing the retrieval of fullportraits from entirely corroded daguerreotypes, suggesting that Hg concentration may be a usefulproxy for the original image.

Aqueous Ferrofluid of Citric Acid Coated Magnetite Particles

2003 ◽  
Vol 789 ◽  
Author(s):  
A. Goodarzi ◽  
Y. Sahoo ◽  
M. T. Swihart ◽  
P. N. Prasad
Keyword(s):  
Citric Acid ◽  
Photoelectron Spectroscopy ◽  
Quantum Interference ◽  
Fluorescent Dyes ◽  
Aqueous Suspension ◽  
Medical Diagnostics ◽  
X Ray Diffraction ◽  
X Ray ◽  
Transmission Electron ◽  
Magnetite Particles

ABSTRACTMagnetic nanoparticles have found application in medical diagnostics such as magnetic resonance imaging and therapies such as cancer treatment. In these applications, it is imperative to have a biocompatible solvent such as water at optimum pH for possible bio-ingestion. In the present work, a synthetic methodology has been developed to get a well-dispersed and homogeneous aqueous suspension of Fe3O4 nanoparticles in the size range of 8–10 nm. The surface functionalization of the particles is provided by citric acid. The particles have been characterized using transmission electron microscopy, magnetization measurements with a superconducting quantum interference device, FTIR spectroscopy (for surfactant binding sites), thermogravimetric studies (for strength of surfactant binding), and x-ray photoelectron spectroscopy and x-ray diffraction (for composition and phase information). The carboxylate functionality on the surface provides an avenue for further surface modification with fluorescent dyes, hormone linkers etc for possible cell-binding, bioimaging, tracking, and targeting.

scholarly journals Deep Learning and Artificial Intelligence for the Determination of the Cervical Vertebra Maturation Degree from Lateral Radiography

Entropy ◽  
2019 ◽  
Vol 21 (12) ◽  
pp. 1222 ◽  
Author(s):  
Masrour Makaremi ◽  
Camille Lacaule ◽  
Ali Mohammad-Djafari
Keyword(s):  
Artificial Intelligence ◽  
Deep Learning ◽  
Cervical Vertebra ◽  
Medical Diagnostics ◽  
Great Success ◽  
X Ray ◽  
Treatment Timing ◽  
Proposed Model ◽  
The Right

Deep Learning (DL) and Artificial Intelligence (AI) tools have shown great success in different areas of medical diagnostics. In this paper, we show another success in orthodontics. In orthodontics, the right treatment timing of many actions and operations is crucial because many environmental and genetic conditions may modify jaw growth. The stage of growth is related to the Cervical Vertebra Maturation (CVM) degree. Thus, determining the CVM to determine the suitable timing of the treatment is important. In orthodontics, lateral X-ray radiography is used to determine it. Many classical methods need knowledge and time to look and identify some features. Nowadays, ML and AI tools are used for many medical and biological diagnostic imaging. This paper reports on the development of a Deep Learning (DL) Convolutional Neural Network (CNN) method to determine (directly from images) the degree of maturation of CVM classified in six degrees. The results show the performances of the proposed method in different contexts with different number of images for training, evaluation and testing and different pre-processing of these images. The proposed model and method are validated by cross validation. The implemented software is almost ready for use by orthodontists.

Nanocrystals of Metal Halide Perovskites and Their Analogues as Scintillators for X-ray detection

Nano Futures ◽  
2021 ◽  
Author(s):  
Huiwen Chen ◽  
Yunlong Li ◽  
Bo Zhao ◽  
Jun Ming ◽  
Dongfeng Xue
Keyword(s):  
Homeland Security ◽  
Quantum Confinement ◽  
Room Temperature ◽  
Quantum Confinement Effect ◽  
Medical Diagnostics ◽  
Metal Halide ◽  
Large Area ◽  
X Ray ◽  
Industrial Inspection ◽  
Halide Perovskites

Abstract Scintillators are widely used for X-ray detection in various fields, such as medical diagnostics, industrial inspection and homeland security. Nanocrystals of metal halide perovskites and their analogues showed great advantages as X-ray scintillators due to their cheap manufacturing, fast decay time, and room temperature scintillation from quantum confinement effect. However, there are still many challenges unsolved for further industrialization. Herein, it is necessary to summarize the progress of scintillators based on nanocrystals of metal halide perovskites and their analogues. In first section, the scintillation mechanism and key parameters are outlined. Then, various nanocrystals of metal halide perovskites and their analogues used as scintillators are reviewed. Finally, the challenges and outlook are discussed. It is believed that nanocrystals of metal halide perovskites and their analogues are favorable for large-area and flexible X-ray detectors.

scholarly journals Bi-cross validation of spectral clustering hyperparameters

2020 ◽  
Vol 35 (2) ◽  
pp. 112-116
Author(s):  
Sioan Zohar ◽  
Chun Hong Yoon
Keyword(s):  
Spectral Clustering ◽  
Cross Validation ◽  
Clustering Algorithms ◽  
Scattering Data ◽  
Number Of Clusters ◽  
X Ray ◽  
Clustering Problem ◽  
X Ray Scattering ◽  
Linac Coherent Light Source ◽  
Ray Scattering

One challenge impeding the analysis of terabyte scale X-ray scattering data from the Linac Coherent Light Source (LCLS) is determining the number of clusters required for the execution of traditional clustering algorithms. Here, we demonstrate that the previous work using bi-cross validation to determine the number of singular vectors directly maps to the spectral clustering problem of estimating both the number of clusters and hyperparameter values. Applying this method to LCLS X-ray scattering data enables the identification of dropped shots without manually setting boundaries on detector fluence and provides a path toward identifying rare and anomalous events.

scholarly journals Synthesis and Characterization of a New Nanocomposite Film Based on Polyvinyl Alcohol Polymer and Nitro Blue Tetrazolium Dye as a Low Radiation Dosimeter in Medical Diagnostics Application

Polymers ◽  
2021 ◽  
Vol 13 (11) ◽  
pp. 1815
Author(s):  
Saleh Alashrah ◽  
Yassine El-Ghoul ◽  
Mohammed Ahmed Ali Omer
Keyword(s):  
Polyvinyl Alcohol ◽  
Nanocomposite Film ◽  
Radiation Detection ◽  
Medical Diagnostics ◽  
Linear Increase ◽  
Nitro Blue Tetrazolium ◽  
Diagnostic Radiology ◽  
Nanocomposite Films ◽  
X Ray ◽  
Blue Tetrazolium

Dosimetry is a field of increasing importance in diagnostic radiology. There has been a realization among healthcare professionals that the dose of radiation received by patients via modern medical X-ray examinations could induce acute damage to the skin and eyes. The present study highlights the synthesis of polyvinyl alcohol/nitro blue tetrazolium nanocomposite films (PVA/NBT) for radiation detection depending on chromic, optical, chemical and morphologic changes. First, we synthesized the nanocomposite film-based PVA doped with NBT and the different parameters of the preparation procedure were optimized. Then The films were exposed to different low X-ray doses on the scale of mGy level (0, 2, 4, 10 and 20 mGy). The sensitivity and the performance of the made composite films were evaluated via different characterization methods. Indeed, the response curve based on UV-Vis absorptions revealed a linear increase in absorbance with increased radiation doses (R = 0.998). FTIR analysis showed a clear chemical modification in recorded spectra after irradiation. X-ray diffraction assessment revealed clear structural changes in crystallinity after ionization treatment. SEM analysis showed a clear morphological modification of PVA/NBT films after irradiation. In addition, the prepared PVA/NBT films exhibited excellent pre- and post-irradiation stability in dark and light. Finally, the quantitative colorimetry study confirmed the performance of the prepared films and the different colorimetric coordinates, the total color difference (∆E) and the color strength (K/S) showed a linear increase with increasing X-ray doses. The made nanocomposite PVA/NBT film might offer promising potential for an effective highly sensitive medical dosimeter applied for very low doses in X-ray diagnostic radiology.

Highly Efficient Copper Halide Scintillators for High-Performance and Dynamic X-ray Imaging

Nanoscale ◽  
2021 ◽  
Author(s):  
Quan Zhou ◽  
Jiwei Ren ◽  
Jiawen Xiao ◽  
Lin Lei ◽  
Feiyi Liao ◽  
...  
Keyword(s):  
Homeland Security ◽  
High Performance ◽  
Low Cost ◽  
Light Yield ◽  
Medical Diagnostics ◽  
Dynamic Imaging ◽  
Copper Halide ◽  
X Ray ◽  
X Ray Imaging ◽  
High Light Yield

Progress towards high performance X-ray detection and dynamic imaging applications, including nondestructive inspection, homeland security, and medical diagnostics, requires scintillators with high light yield, reasonable decay time, low cost, and...

Sign in / Sign up

Export Citation Format

Share Document