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Study on joint de-noising method of ECG signals with improved CEEMDAN-wavelet thresholding and singular spectrum analysis

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JOURNAL OF INSTRUMENTATION 2025年第1期20卷

作者： Ge, Liang Ma, Yuhong Xiao, Xiaoting Cheng, Jixiang Li, Zhidan Qin, Wang Southwest Petr Univ Sch Mech & Elect Engn Chengdu 610500 Peoples R China Southwest Petr Univ Sch Elect Engn & Informat Chengdu 610500 Peoples R China

The electrocardiogram (ECG) signal is often contaminated by various noises during acquisition and transmission, and the denoising effect directly affects the diagnosis of heart diseases. To improve the denoising effect, this paper proposes an improved Complete Ensemble Empirical Mode Decomposition (CEEMDAN)-wavelet thresholding and singular spectrum analysis (SSA) denoising method. First, the noise-dominated high-frequency intrinsic mode function (IMF) identified using CEEMDAN;second, it is denoised to reduce high-frequency noise by the improved wavelet thresholding technique;and then, SSA is used to remove baseline wander (BW);finally, to verify the effectiveness of this denoising method, the root mean square error (RMSE) and signal-to-noise ratio (SNR) are used as the evaluation criteria for the denoising effect and the standard MIT-BIH ECG noise database signals are used for verification. The validation results show that compared the existing ECG denoising methods, the denoising method improves the SNR by 39% 55% reduces the RMSE by 18% 42%. The method can be used as an effective tool for ECG signal denoising and provide a better basis for diagnosis in computerized automated medical systems.

关键词： Data processing methods medical-image reconstruction methods and algorithms, computer-aided diagnosis Bioinstrumentation

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Picosecond timing performances of the FERS time unit

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JOURNAL OF INSTRUMENTATION 2025年第1期20卷

作者： Giordano, F. Colombini, L. Doroud, K. Maggio, C. Mati, A. Ninci, D. Picchi, A. Tintori, C. Venturini, Y. Williams, C. Williams, T. CAEN Spa Via Vetraia 11 Viareggio LU Italy Picotech SAS 90 Rue Henri Fabre St Genis Pouilly France

Next-generation high-energy physics experiments will employ high-granularity detectors with thousands of readout channels, necessitating the use of low-power, compact ASICs. The CAEN FrontEnd Readout System (FERS) 5200 integrates these ASICs within small, synchronizable, and distributable systems featuring both Front and Back Ends. The A5203 FERS module incorporates the recently released CERN picoTDC ASIC, enabling high-resolution timing measurements for Time of Arrival (ToA) and Time over Threshold (ToT). In this work, we analyze the performance of the A5203 unit, which has a 3.125 ps least significant bit (LSB), delivering ToA measurements with an RMS resolution of approximately 7 ps for signals of fixed amplitude, and approximately 20 ps RMS for input signals with variable amplitude over a 50 dB dynamic range over a single board. The amplitude-dependent walk effect is corrected using ToT, which, in addition to walk correction, is also utilised for signal amplitude reconstruction and background reduction. The A5203 has been successfully applied across various experimental and industrial contexts. In the concluding section of this paper, we will discuss its application within the ProVision project: a PET scanner specialised in imaging aggressive prostate cancer at an early-stage.

关键词： Front-end electronics for detector readout Modular electronics medical-image reconstruction methods and algorithms, computer-aided diagnosis

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Preliminary study on a chest digital tomosynthesis: development and evaluation

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JOURNAL OF INSTRUMENTATION 2015年第10期10卷 P10035-P10035页

作者： Lee, Y. Lee, S. Eulji Univ Dept Radiol Sci Songnam Gyeonggi Do South Korea Konyang Univ Dept Radiol Sci Daejeon South Korea

Chest digital tomosynthesis (chest DTS) has been recently introduced to overcome the limitations for high patient dose of conventional X-ray radiography and of a cone-beam computed tomography (CBCT) in studies of overlap of anatomical structures. In the present study, we constructed chest DTS system with amorphous-silicon (a-Si) digital flat-panel detector with pixel pitch of 143 x 143 mu m(2) based upon filtered backprojection (FBP) reconstruction methods We performed both experiments and systematic simulations using our chest DTS system. The image performances were evaluated by means of root-mean-square error (RMSE) and signal difference-to-noise ratio (SDNR) with respect to scan angles such as +/- 5 degrees, +/- 10 degrees, +/- 15 degrees, and +/- 20 degrees. We also performed experiments using our chest DTS system. According to the results, the image performances obtained from chest DTS are improved by using our wide scan angle approach The chest DTS slices showed an improvement in the depth resolution with increasing scan angle. It was found that the optimized filter with a Hanning window to limit the high-frequency components improves image performance because of noise reduction. The chest DTS slices showed an improvement in the depth resolution with increasing scan angle. Both simulation and experimental results showed the same tendency when image performances quantitatively compared. Based on our results, we successfully obtained chest DTS reconstruction images by using a FBP method and promising to application to field of medical imaging.

关键词： Detector design and construction technologies and materials medical-image reconstruction methods and algorithms, computer-aided diagnosis X-ray radiography and digital radiography (DR)

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A deep convolutional neural network for simultaneous denoising and deblurring in computed tomography

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JOURNAL OF INSTRUMENTATION 2020年第12期15卷

作者： Yim, D. Kim, B. Lee, S. Konyang Univ Dept Med Sci 158 Gwanjeodong Ro Daejeon South Korea Konyang Univ Dept Radiol Sci 158 Gwanjeodong Ro Daejeon South Korea

Computed tomography (CT) has been commonly used for providing medical images. However, CT scans have a potential risk of side-effect due to high radiation dose. In order to overcome this limitation, low-dose CT imaging techniques have been developed by using novel scanners, reconstruction algorithms and adjusted scanning protocols. In spite of these strategies, the conventional low-dose CT imaging techniques are hard to compromise between radiation dose and image quality, leading to noise, blur and artifacts in CT images. These drawbacks of the conventional techniques degrade diagnostic accuracy. In this study, we proposed a deep convolutional neural network (CNN)-based low-dose CT imaging technique for simultaneously reducing noise and blur at once. The proposed method, called denoising and deblurring CNN (DnDbCNN), consisted of two networks, and each network was separately trained for reducing noise and blur in CT images. For combining the trained networks, a convolutional layer was added between the two trained networks, and the combined network was re-trained to update the weights of each layer. Denoising convolutional neural network (DnCNN) and super-resolution convolutional neural network (SRCNN) were also implemented for comparison. We evaluated the performance of the DnDbCNN in terms of mean-square error (MSE), peak signal-to-noise ratio (PSNR), structural similarity index measure (SSIM), coefficient-of-variation (COV) and modulation transfer function (MTF). The results showed that the DnDbCNN improved the noise property, spatial resolution and quantitative accuracy of CT images, and the performance of the DnDbCNN was superior to the conventional methods. As a result, the DnDbCNN can simultaneously reduce noise and blur by combining two networks through three training steps. Therefore, the DnDbCNN has a potential for improving CT image quality with low radiation dose and enables precise diagnosis.

关键词： computerized Tomography (CT) and Computed Radiography (CR) medical-image reconstruction methods and algorithms, computer-aided diagnosis

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Synthesising two-dimensional mammographic images using compressed sensing-reconstructed digital breast tomosynthesis images

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JOURNAL OF INSTRUMENTATION 2024年第8期19卷 P08012页

作者： Han, Seohee Yang, Hyesun Xu, Wenting Seo, Changwoo Cho, Hyosung Cha, Bo Kyung Yonsei Univ Dept Radiat Convergence Engn Wonju South Korea Korea Electrotechnol Res Inst Precis Med Device Res Ctr Ansan South Korea

This study presents a method synthesizing a two-dimensional (2D) mammographic image of reasonable quality directly from a 3D digital breast tomosynthesis (DBT) image, reconstructed using an advanced compressed sensing (CS)-based algorithm. This approach aims to reduce the radiation dose required for complementary imaging technologies of digital mammography (DM) and DBT, eliminating the need for additional DM examinations. The method involves three main steps: projection data acquisition from a DBT system, CS-based DBT reconstruction, and synthesis of a 2D mammographic image from the reconstructed DBT image. To verify the efficacy of the proposed method, we conducted both a simulation and an experiment on a numerical breast and commercially available BR3D phantoms, respectively, prior to practical implementation in real-world DBT systems. Our simulation and experimental results indicated that the CS-based algorithm yielded markedly improved DBT reconstruction quality, preserving superior image homogeneity, better edge contour and sharpening, and fewer image artifacts. The measured contrast-to-noise ratio and structural similarity values of the CS-reconstructed DBT images were 10.31 and 0.78, respectively, which were approximately 2.2 and 3.1 times larger, respectively, than those of the filtered-backprojectionreconstructed DBT images in the simulation. The quality of the synthetic mammographic images using the CS-reconstructed DBT images was similar to that of conventional mammographic images obtained using a full dose, indicating the efficacy of the proposed method. Consequently, we successfully reconstructed DBT images of substantially high quality using the CS-based algorithm and synthesised 2D mammographic images of reasonable quality, potentially reducing the radiation dose to patients in the complementary imaging technologies of DM and DBT.

关键词： Data processing methods medical-image reconstruction methods and algorithms, computer-aided diagnosis X-ray mammography and scinto- and MRI-mammography

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A 3D reconstruction solution to ultrasound Joule heat density tomography based on acousto-electric effect: a simulation study

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JOURNAL OF INSTRUMENTATION 2014年第10期9卷 P10004-P10004页

作者： Yang, Renhuan Song, Aiguo Li, Xiao Dong Lu, Yang Yan, Ruqiang Xu, Baoguo Li, Xu Jinan Univ Coll Informat & Technol Guangzhou 510632 Guangdong Peoples R China Southeast Univ Sch Instrument Sci & Engn Nanjing 210096 Jiangsu Peoples R China Johns Hopkins Univ Dept Radiol & Radiol Sci Baltimore MD 21205 USA

A 3D reconstruction solution to ultrasound Joule heat density tomography based on acousto-electric effect by deconvolution is proposed for noninvasive imaging of biological tissue. Compared with ultrasound current source density imaging, ultrasound Joule heat density tomography doesn't require any priori knowledge of conductivity distribution and lead fields, so it can gain better imaging result, more adaptive to environment and with wider application scope. For a general 3D volume conductor with broadly distributed current density field, in the AE equation the ultrasound pressure can't simply be separated from the 3D integration, so it is not a common modulation and basebanding (heterodyning) method is no longer suitable to separate Joule heat density from the AE signals. In the proposed method the measurement signal is viewed as the output of Joule heat density convolving with ultrasound wave. As a result, the internal 3D Joule heat density can be reconstructed by means of Wiener deconvolution. A series of computer simulations set for breast cancer imaging applications, with consideration of ultrasound beam diameter, noise level, conductivity contrast, position dependency and size of simulated tumors, have been conducted to evaluate the feasibility and performance of the proposed reconstruction method. The computer simulation results demonstrate that high spatial resolution 3D ultrasound Joule heat density imaging is feasible using the proposed method, and it has potential applications to breast cancer detection and imaging of other organs.

关键词： image reconstruction in medical imaging medical-image reconstruction methods and algorithms, computer-aided diagnosis Multi-modality systems medical-image reconstruction methods and algorithms, computer-aided software

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A comparative study of crystal geometry, material, and reconstruction algorithms on MicroPET scanner performance

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JOURNAL OF INSTRUMENTATION 2024年第8期19卷 P08028页

作者： Sadremomtaz, Alireza Taherparvar, Payvand Saber, Mohaddeseh Univ Guilan Fac Sci Dept Phys Namjoo AvePostal Code ***POB Rasht 416351914 Guilan Iran

Small-animal PET, also known as microPET, has been developed to enhance image quality by improving spatial resolution and sensitivity due to its smaller ring and crystal size. However, the reduction of crystal size and the presence of gaps between cuboidal crystals could reduce sensitivity. MicroPET with tapered arrays has been developed to simultaneously improve sensitivity and spatial resolution. This study compared the performance of 14 x 14 and 28 x 28 array microPETs using LSO and CZT crystal materials. The impact of crystal design and reconstruction algorithms on image quality and performance parameters was investigated, using GATE Monte Carlo simulation toolkit. The findings showed that sensitivity increased with crystal thickness, particularly in LSO. The 14 x 14 arrays consistently exhibited higher sensitivity, while the 28 x 28 arrays had superior spatial resolution. NECR values increased with crystal thickness, with LSO outperforming CZT. Scatter and random fractions were low. Different reconstruction algorithms had negligible effects on FWHM and CNR but influenced SNR, with the COSEM algorithm achieving significantly reduced noise. The small size of crystals and tapered arrays contributed to improved sensitivity and spatial resolution. However, there was a trade-off between sensitivity and spatial resolution. LSO crystals showed better performance, but the choice between array sizes depended on specific imaging requirements. This study provides insights into optimizing microPET design for enhanced imaging capabilities.

关键词： Gamma camera, SPECT, PET PET/CT, coronary CT angiography (CTA) medical-image reconstruction methods and algorithms, computer-aided diagnosis Models and simulations

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Preliminary performance evaluation of adjustable-FOV full-body PET

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JOURNAL OF INSTRUMENTATION 2020年第6期15卷

作者： Ozsahin, I. Near East Univ Fac Engn Dept Biomed Engn Mersin 10 TRNC TR-99138 Nicosia Turkey Near East Univ DESAM Inst Mersin 10 TRNC TR-99138 Nicosia Turkey

Recent developments in molecular imaging have led to increases in the performance and area of utilization of positron emission tomography (PET) systems. There are several ways that PET system sensitivity can be increased including changing the scanner's geometry. I recently proposed a novel PET design with adjustable field of view (FOV) to improve the system sensitivity up to 40 times higher than the conventional systems, depending on the size of the transaxial FOV. This study aims to evaluate the spatial resolution characteristics of the proposed design. Geant4-based Architecture for Medicine Oriented Simulations (GAMOS) toolkit was used to simulate the system. The proposed PET geometry was designed to cover and scan the full-body of the patient in one bed position. The spatial resolution tests were conducted using a point like source placed at different locations throughout the FOV when the transaxial FOV of the scanner was changed from 70 cm to 30 cm. The results showed that the spatial resolution slightly degrades when the FOV is reduced.

关键词： Gamma camera, SPECT, PET PET/CT, coronary CT angiography (CTA) medical-image reconstruction methods and algorithms, computer-aided diagnosis medical-image reconstruction methods and algorithms, computer-aided software

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MARS-MD: rejection based image domain material decomposition

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JOURNAL OF INSTRUMENTATION 2018年第5期13卷 P05020-P05020页

作者： Bateman, C. J. Knight, D. Brandwacht, B. Mc Mahon, J. Healy, J. Panta, R. Aamir, R. Rajendran, K. Moghiseh, M. Ramyar, M. Rundle, D. Bennett, J. de Ruiter, N. Smithies, D. Bell, S. T. Doesburg, R. Chernoglazov, A. Mandalika, V. B. H. Walsh, M. Shamshad, M. Anjomrouz, M. Atharifard, A. Broeke, L. Vanden Bheesette, S. Kirkbride, T. Anderson, N. G. Gieseg, S. P. Woodfield, T. Renaud, P. F. Butler, A. P. H. Butler, P. H. MARS Bioimaging Ltd 29a Clyde Rd Christchurch New Zealand Univ Otago Dept Radiol 2 Riccarton Ave Christchurch 8140 New Zealand Univ Canterbury Dept Phys & Astron POB 69 133 Christchurch 7640 New Zealand Lincoln Agritech Ltd Private Bag 4800 Christchurch 8140 New Zealand Univ Canterbury Dept Biol Private Bag 4800 Christchurch 8140 New Zealand HIT Lab NZ John Britten BldgCnr Creyke & Engn Rd Christchurch New Zealand Univ Twente Drienerlolaan 5 NL-7522 NB Enschede Netherlands CERN European Org Nucl Res CH-1211 Geneva Switzerland Univ Canterbury Dept Math & Stat Private Bag 4800 Christchurch 8140 New Zealand Ara Inst Canterbury Dept Nursing Midwifery & Allied Hlth POB 540 Christchurch 8140 New Zealand

This paper outlines image domain material decomposition algorithms that have been routinely used in MARS spectral CT systems. These algorithms (known collectively as MARSMD) are based on a pragmatic heuristic for solving the under-determined problem where there are more materials than energy bins. This heuristic contains three parts: (1) splitting the problem into a number of possible sub-problems, each containing fewer materials;(2) solving each sub-problem;and (3) applying rejection criteria to eliminate all but one sub-problem's solution. An advantage of this process is that different constraints can be applied to each sub-problem if necessary. In addition, the result of this process is that solutions will be sparse in the material domain, which reduces crossover of signal between material images. Two algorithms based on this process are presented: the Segmentation variant, which uses segmented material classes to define each subproblem;and the Angular Rejection variant, which defines the rejection criteria using the angle between reconstructed attenuation vectors.

关键词： computerized Tomography (CT) and Computed Radiography (CR) Data processing methods medical-image reconstruction methods and algorithms, computer-aided diagnosis

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MAIR-Net: a sparse-view CT reconstruction network based on a combination of mixed attention and iterative optimization learning

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JOURNAL OF INSTRUMENTATION 2024年第8期19卷 P08029页

作者： Guo, Tong Liu, Yi Zhang, Pengcheng Liu, Yu Gui, Zhiguo North Univ China Sch Informat & Commun Engn Taiyuan Peoples R China

Sparse-view computed tomography (CT) is one of the main means to reduce radiation risk. When the projection data is highly undersampled, the reconstructed CT image may suffer from serious stripe artifacts and structural information loss. In this paper, we propose a sparse-view CT reconstruction network architecture combining mixed attention (MA) and an iterative reconstruction strategy, called MAIR-Net. Firstly, the approach expands the proximal gradient descent into the neural network and uses an initial value enhancement module between the gradient descent module and the proximal mapping module. The aim is to enhance the flow of detailed information between different layers, fully retain image details, and improve the network convergence speed. Secondly, the mixed attention module (MAM) is introduced into the reconstruction process as a regularization term. It adaptively fuses local and non-local features of the image, which are used to reduce the over-smoothing of the reconstructed image and fully retain the details of the reconstructed image, respectively. Experimental results showed that the proposed method can better retain the details of the reconstructed image and improve the quality of the reconstructed image while inhibiting the sparse angle artifacts of the CT reconstructed image.

关键词： computerized Tomography (CT) and Computed Radiography (CR) image reconstruction in medical imaging medical-image reconstruction methods and algorithms, computer-aided diagnosis

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