scholarly journals Methods for Improving Image Quality for Contour and Textures Analysis Using New Wavelet Methods

2021 ◽  
Vol 11 (9) ◽  
pp. 3895
Author(s):  
Catalin Dumitrescu ◽  
Maria Simona Raboaca ◽  
Raluca Andreea Felseghi
Keyword(s):  
Image Quality ◽  
Real Time ◽  
Wiener Filter ◽  
Digital Processing ◽  
Reconstructed Image ◽  
Human Observer ◽  
The Difference ◽  
Assisted Diagnosis ◽  
Wavelet Methods ◽  
Noise Reduction Algorithm

The fidelity of an image subjected to digital processing, such as a contour/texture highlighting process or a noise reduction algorithm, can be evaluated based on two types of criteria: objective and subjective, sometimes the two types of criteria being considered together. Subjective criteria are the best tool for evaluating an image when the image obtained at the end of the processing is interpreted by man. The objective criteria are based on the difference, pixel by pixel, between the original and the reconstructed image and ensure a good approximation of the image quality perceived by a human observer. There is also the possibility that in evaluating the fidelity of a remade (reconstructed) image, the pixel-by-pixel differences will be weighted according to the sensitivity of the human visual system. The problem of improving medical images is particularly important in assisted diagnosis, with the aim of providing physicians with information as useful as possible in diagnosing diseases. Given that this information must be available in real time, we proposed a solution for reconstructing the contours in the images that uses a modified Wiener filter in the wavelet domain and a nonlinear cellular network and that is useful both to improve the contrast of its contours and to eliminate noise. In addition to the need to improve imaging, medical applications also need these applications to run in real time, and this need has been the basis for the design of the method described below, based on the modified Wiener filter and nonlinear cellular networks.

Development of High-Definition Image Processing System for a FE-SEM

1996 ◽  
Vol 54 ◽  
pp. 458-459
Author(s):  
M. Yamada ◽  
T. Yoshihara ◽  
H. Arima ◽  
Y. Nimura ◽  
T. Kobayashi ◽  
...  
Keyword(s):  
Image Processing ◽  
Image Quality ◽  
Real Time ◽  
Processing System ◽  
Digital Processing ◽  
High Definition ◽  
Sem Images ◽  
Pixel Resolution ◽  
Generator System ◽  
Image Processing System

This paper presents the development of a new, fully digital image processing system for a field emission SEM (FE-SEM) which can eliminate fluctuations in the emission current. The system can display, in real time, images with 1280 × 1024 pixels on a viewing CRT, allowing direct observation of high definition SEM images on the FE-SEM.In the past, even though image was acquired and recorded (photographed) with the resolution higher than 1,000 x 1,000 pixels, it was generally observed on the viewing CRT at the resolution of only about 500 x 500 pixels for real-time observation. This created a difference in image quality between the two CRT's. Using a CRT of the same pixel resolution for observation as on the recording CRT, the difference in image quality can be minimised, provided that the characteristics (speed and resolution) of the image processing and scan generator system are improved and optimised for digital processing.

scholarly journals A “Smart” Biosensor-Enabled Intravascular Catheter and Platform for Dynamic Delivery of Propofol to “Close the Loop” for Total Intravenous Anesthesia

2021 ◽  
Vol 186 (Supplement_1) ◽  
pp. 370-377
Author(s):  
Edward Chaum ◽  
Ernő Lindner
Keyword(s):  
Real Time ◽  
Drug Distribution ◽  
Population Based ◽  
Pharmacokinetic Data ◽  
Drug Infusion ◽  
Blood Concentrations ◽  
The Usa ◽  
The Difference ◽  
Automated Delivery

ABSTRACT Background Target-controlled infusion anesthesia is used worldwide to provide user-defined, stable, blood concentrations of propofol for sedation and anesthesia. The drug infusion is controlled by a microprocessor that uses population-based pharmacokinetic data and patient biometrics to estimate the required infusion rate to replace losses from the blood compartment due to drug distribution and metabolism. The objective of the research was to develop and validate a method to detect and quantify propofol levels in the blood, to improve the safety of propofol use, and to demonstrate a pathway for regulatory approval for its use in the USA. Methods We conceptualized and prototyped a novel “smart” biosensor-enabled intravenous catheter capable of quantifying propofol at physiologic levels in the blood, in real time. The clinical embodiment of the platform is comprised of a “smart” biosensor-enabled catheter prototype, a signal generation/detection readout display, and a driving electronics software. The biosensor was validated in vitro using a variety of electrochemical methods in both static and flow systems with biofluids, including blood. Results We present data demonstrating the experimental detection and quantification of propofol at sub-micromolar concentrations using this biosensor and method. Detection of the drug is rapid and stable with negligible biofouling due to the sensor coating. It shows a linear correlation with mass spectroscopy methods. An intuitive graphical user interface was developed to: (1) detect and quantify the propofol sensor signal, (2) determine the difference between targeted and actual propofol concentration, (3) communicate the variance in real time, and (4) use the output of the controller to drive drug delivery from an in-line syringe pump. The automated delivery and maintenance of propofol levels was demonstrated in a modeled benchtop “patient” applying the known pharmacokinetics of the drug using published algorithms. Conclusions We present a proof-of-concept and in vitro validation of accurate electrochemical quantification of propofol directly from the blood and the design and prototyping of a “smart,” indwelling, biosensor-enabled catheter and demonstrate feedback hardware and software architecture permitting accurate measurement of propofol in blood in real time. The controller platform is shown to permit autonomous, “closed-loop” delivery of the drug and maintenance of user-defined propofol levels in a dynamic flow model.

scholarly journals A Modified KNN Algorithm for High-Performance Computing on FPGA of Real-Time m-QAM Demodulators

Electronics ◽  
2021 ◽  
Vol 10 (5) ◽  
pp. 627
Author(s):  
David Marquez-Viloria ◽  
Luis Castano-Londono ◽  
Neil Guerrero-Gonzalez
Keyword(s):  
Real Time ◽  
High Performance ◽  
Interference Mitigation ◽  
Parallel Implementation ◽  
Computational Time ◽  
Successful Implementation ◽  
Interchannel Interference ◽  
The Difference ◽  
High Level ◽  
Performance Computing

A methodology for scalable and concurrent real-time implementation of highly recurrent algorithms is presented and experimentally validated using the AWS-FPGA. This paper presents a parallel implementation of a KNN algorithm focused on the m-QAM demodulators using high-level synthesis for fast prototyping, parameterization, and scalability of the design. The proposed design shows the successful implementation of the KNN algorithm for interchannel interference mitigation in a 3 × 16 Gbaud 16-QAM Nyquist WDM system. Additionally, we present a modified version of the KNN algorithm in which comparisons among data symbols are reduced by identifying the closest neighbor using the rule of the 8-connected clusters used for image processing. Real-time implementation of the modified KNN on a Xilinx Virtex UltraScale+ VU9P AWS-FPGA board was compared with the results obtained in previous work using the same data from the same experimental setup but offline DSP using Matlab. The results show that the difference is negligible below FEC limit. Additionally, the modified KNN shows a reduction of operations from 43 percent to 75 percent, depending on the symbol’s position in the constellation, achieving a reduction 47.25% reduction in total computational time for 100 K input symbols processed on 20 parallel cores compared to the KNN algorithm.

scholarly journals Feasibility of Total Variation Noise Reduction Algorithm According to Various MR-Based PET Images in a Simultaneous PET/MR System: A Phantom Study

Diagnostics ◽  
2021 ◽  
Vol 11 (2) ◽  
pp. 319
Author(s):  
Chan-Rok Park ◽  
Seong-Hyeon Kang ◽  
Young-Jin Lee
Keyword(s):  
Image Quality ◽  
Noise Reduction ◽  
Total Variation ◽  
Parallel Imaging ◽  
Pulse Sequence ◽  
Reduction Algorithm ◽  
Median Filters ◽  
Reduction Techniques ◽  
Imaging Results ◽  
Noise Reduction Algorithm

Recently, the total variation (TV) algorithm has been used for noise reduction distribution in degraded nuclear medicine images. To acquire positron emission tomography (PET) to correct the attenuation region in the PET/magnetic resonance (MR) system, the MR Dixon pulse sequence, which is based on controlled aliasing in parallel imaging, results from higher acceleration (CAIPI; MR-ACDixon-CAIPI) and generalized autocalibrating partially parallel acquisition (GRAPPA; MR-ACDixon-GRAPPA) algorithms are used. Therefore, this study aimed to evaluate the image performance of the TV noise reduction algorithm for PET/MR images using the Jaszczak phantom by injecting 18F radioisotopes with PET/MR, which is called mMR (Siemens, Germany), compared with conventional noise-reduction techniques such as Wiener and median filters. The contrast-to-noise (CNR) and coefficient of variation (COV) were used for quantitative analysis. Based on the results, PET images with the TV algorithm were improved by approximately 7.6% for CNR and decreased by approximately 20.0% for COV compared with conventional noise-reduction techniques. In particular, the image quality for the MR-ACDixon-CAIPI PET image was better than that of the MR-ACDixon-GRAPPA PET image. In conclusion, the TV noise-reduction algorithm is efficient for improving the PET image quality in PET/MR systems.

A Unitary-UCA-Root-MUSIC Algorithm Based on MSWF

2014 ◽  
Vol 610 ◽  
pp. 339-344
Author(s):  
Qiang Guo ◽  
Yun Fei An
Keyword(s):  
Computer Simulation ◽  
Computational Complexity ◽  
Real Time ◽  
Unitary Transformation ◽  
Wiener Filter ◽  
Doa Estimation ◽  
Signal Subspace ◽  
Music Algorithm ◽  
Multi Stage ◽  
Simulation Results

A UCA-Root-MUSIC algorithm for direction-of-arrival (DOA) estimation is proposed in this paper which is based on UCA-RB-MUSIC [1]. The method utilizes not only a unitary transformation matrix different from UCA-RB-MUSIC but also the multi-stage Wiener filter (MSWF) to estimate the signal subspace and the number of sources, so that the new method has lower computational complexity and is more conducive to the real-time implementation. The computer simulation results demonstrate the improvement with the proposed method.

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