Physical and Engineering Sciences in Medicine最新文献

筛选
英文 中文
An Australasian survey on the use of ChatGPT and other large language models in medical physics. 一项关于在医学物理学中使用ChatGPT和其他大型语言模型的澳大利亚调查。
IF 2 4区 医学
Physical and Engineering Sciences in Medicine Pub Date : 2025-09-01 Epub Date: 2025-05-20 DOI: 10.1007/s13246-025-01571-9
Stanley A Norris, Tomas Kron, Maeve Masterson, Mohamed K Badawy
{"title":"An Australasian survey on the use of ChatGPT and other large language models in medical physics.","authors":"Stanley A Norris, Tomas Kron, Maeve Masterson, Mohamed K Badawy","doi":"10.1007/s13246-025-01571-9","DOIUrl":"10.1007/s13246-025-01571-9","url":null,"abstract":"<p><p>This study surveyed medical physicists in Australia and New Zealand on their use of large language models (LLMs), particularly ChatGPT. There is currently no literature on the application of ChatGPT and other LLMs by medical physicists. This survey targeted a mixed group of professionals, including clinical medical physicists, registrars, students, and other specialised roles. It reveals that many respondents integrate LLM platforms into their work for a broad range of tasks. Most participants reported efficiency gains, although fewer perceived improvements in the overall quality of their work. Despite these benefits, substantial concerns remain regarding data security, patient confidentiality, and the lack of established guidelines or professional training for using these tools in a clinical context. Further, the potential for sudden changes in accessibility and pricing, which could disproportionately impact developing countries and under-resourced departments, implies that other vulnerabilities may exist. These findings suggest the need for the medical physics community to come together and debate the careful balance between exploiting LLM platforms and developing clear best practices that implement robust risk management strategies.</p>","PeriodicalId":48490,"journal":{"name":"Physical and Engineering Sciences in Medicine","volume":" ","pages":"1145-1153"},"PeriodicalIF":2.0,"publicationDate":"2025-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144112191","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Automated multiclass segmentation of liver vessel structures in CT images using deep learning approaches: a liver surgery pre-planning tool. 使用深度学习方法的CT图像中肝脏血管结构的自动多类分割:肝脏手术预计划工具。
IF 2 4区 医学
Physical and Engineering Sciences in Medicine Pub Date : 2025-09-01 Epub Date: 2025-07-14 DOI: 10.1007/s13246-025-01581-7
Sahar Sarkar, Mahdiyeh Rahmani, Parastoo Farnia, Alireza Ahmadian, Nasser Mozayani
{"title":"Automated multiclass segmentation of liver vessel structures in CT images using deep learning approaches: a liver surgery pre-planning tool.","authors":"Sahar Sarkar, Mahdiyeh Rahmani, Parastoo Farnia, Alireza Ahmadian, Nasser Mozayani","doi":"10.1007/s13246-025-01581-7","DOIUrl":"10.1007/s13246-025-01581-7","url":null,"abstract":"<p><p>Accurate liver vessel segmentation is essential for effective liver surgery pre-planning, and reducing surgical risks since it enables the precise localization and extensive assessment of complex vessel structures. Manual liver vessel segmentation is a time-intensive process reliant on operator expertise and skill. The complex, tree-like architecture of hepatic and portal veins, which are interwoven and anatomically variable, further complicates this challenge. This study addresses these challenges by proposing the UNETR (U-Net Transformers) architecture for the multi-class segmentation of portal and hepatic veins in liver CT images. UNETR leverages a transformer-based encoder to effectively capture long-range dependencies, overcoming the limitations of convolutional neural networks (CNNs) in handling complex anatomical structures. The proposed method was evaluated on contrast-enhanced CT images from the IRCAD as well as a locally dataset developed from a hospital. On the local dataset, the UNETR model achieved Dice coefficients of 49.71% for portal veins, 69.39% for hepatic veins, and 76.74% for overall vessel segmentation, while reaching Dice coefficients of 62.54% for vessel segmentation on the IRCAD dataset. These results highlight the method's effectiveness in identifying complex vessel structures across diverse datasets. These findings underscore the critical role of advanced architectures and precise annotations in improving segmentation accuracy. This work provides a foundation for future advancements in automated liver surgery pre-planning, with the potential to enhance clinical outcomes significantly. The implementation code is available on GitHub: https://github.com/saharsarkar/Multiclass-Vessel-Segmentation .</p>","PeriodicalId":48490,"journal":{"name":"Physical and Engineering Sciences in Medicine","volume":" ","pages":"1463-1472"},"PeriodicalIF":2.0,"publicationDate":"2025-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144627479","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
A novel inverse treatment planning training method for inexperienced treatment planners. 一种针对无经验治疗计划者的逆向治疗计划训练方法。
IF 2 4区 医学
Physical and Engineering Sciences in Medicine Pub Date : 2025-09-01 Epub Date: 2025-06-23 DOI: 10.1007/s13246-025-01547-9
Shadab Momin, Kirk Luca, Yang Lei, Chih-Wei Chang, Huiqiao Xie, Tiffany Kei, Jacob Adams, Tanisha Davis, Xiaofeng Yang, Ashesh Jani, Justin Roper, Jiahan Zhang
{"title":"A novel inverse treatment planning training method for inexperienced treatment planners.","authors":"Shadab Momin, Kirk Luca, Yang Lei, Chih-Wei Chang, Huiqiao Xie, Tiffany Kei, Jacob Adams, Tanisha Davis, Xiaofeng Yang, Ashesh Jani, Justin Roper, Jiahan Zhang","doi":"10.1007/s13246-025-01547-9","DOIUrl":"10.1007/s13246-025-01547-9","url":null,"abstract":"<p><p>Knowledge-based treatment planning (KBP) has been traditionally employed to improve consistency and efficiency in radiation treatment planning. This work introduces a unique use of the KBP model to build site-specific treatment planning modules to provide inexperienced treatment planners with planning intuitions and enhanced learning experience. Our experimental design divided seven planners into two main categories: (a) three planners with more than 6 months of experience and (b) four planners with less than a month of experience. Prior to going through the training module, each planner optimized a treatment plan until they were satisfied with the plan quality on two validation cases. These two plans effectively recorded their baseline planning performance. This was followed by the initiation of treatment planning training on three different training cases. The training process required each planner to first reach their best plan quality, which was then evaluated by the training module. The training module generates a spatial representation of areas of improvement in the form of structures with instructions regarding the current dose value and its ideal dose value. Each planner then focused on incorporating the suggestions made by the training module (i.e., iteration 1, 2…). After training, each planner transferred their knowledge from training to re-optimize the two validation cases. The performance of each planner was evaluated based on the improvements in plan quality before and after the training via clinically relevant dose-volume metrics. The results of this heuristic approach show plan quality improvements after the training for less experienced planners. For instance, the mean dose to bladder, rectum, and penile bulb was reduced by 3.0 Gy, 4.0 Gy, and 2.5 Gy, respectively. An average reduction of 4.6% and 8.2% was achieved for bladder V<sub>40Gy</sub> and rectum V<sub>45Gy</sub>. The quality of treatment plans improved as planners accounted for suggestions made by the training module. As anticipated, the treatment plan quality of more experienced planners was comparable before and after the training. Overall results of this work demonstrate the feasibility of training inexperienced planners with the help of the training module implemented in Eclipse treatment planning system.</p>","PeriodicalId":48490,"journal":{"name":"Physical and Engineering Sciences in Medicine","volume":" ","pages":"965-970"},"PeriodicalIF":2.0,"publicationDate":"2025-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144477404","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Early detection and staging of retinitis pigmentosa using multifocal electroretinogram parameters and machine learning algorithms. 使用多焦点视网膜电图参数和机器学习算法进行视网膜色素变性的早期检测和分期。
IF 2 4区 医学
Physical and Engineering Sciences in Medicine Pub Date : 2025-09-01 Epub Date: 2025-06-16 DOI: 10.1007/s13246-025-01577-3
Bayram Karaman, Ayse Öner, Aysegül Güven
{"title":"Early detection and staging of retinitis pigmentosa using multifocal electroretinogram parameters and machine learning algorithms.","authors":"Bayram Karaman, Ayse Öner, Aysegül Güven","doi":"10.1007/s13246-025-01577-3","DOIUrl":"10.1007/s13246-025-01577-3","url":null,"abstract":"<p><p>Retinitis pigmentosa is an inherited retinal disease caused by damage to photoreceptor cells. Diagnosis and staging of this disease are crucial for early intervention and effective treatment planning. In this study, the amplitude and latency features of N1, P1, and N2 waves obtained from multifocal electroretinogram responses over five rings were used with binary and multiclass classification methods using four different machine learning algorithms to distinguish retinitis pigmentosa patients from healthy individuals and to evaluate the stages of the disease. Binary classifications were performed for six different groups, and the Naive Bayes (NB) algorithm performed the best on all evaluation metrics, achieving 99% accuracy in distinguishing healthy individuals from each disease stage. Furthermore, multiclass classification was applied in two different steps. In the first step, the Naive Bayes model achieved 82% accuracy in four-class classification, including healthy individuals. Considering the near-perfect separability of healthy individuals, in the second step, a three-class classification including only disease stages was performed, and the model achieved 76% accuracy. These results indicate that the proposed approach provides objective and accurate staging for retinitis pigmentosa and can serve as a valuable decision support system to assist ophthalmologists in clinical practice.</p>","PeriodicalId":48490,"journal":{"name":"Physical and Engineering Sciences in Medicine","volume":" ","pages":"1185-1205"},"PeriodicalIF":2.0,"publicationDate":"2025-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144303355","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
The predictive power of hemodynamic data on postoperative neurocognitive impairment: a logistic regression and random forest approach. 血流动力学数据对术后神经认知功能障碍的预测能力:逻辑回归和随机森林方法。
IF 2 4区 医学
Physical and Engineering Sciences in Medicine Pub Date : 2025-09-01 Epub Date: 2025-06-25 DOI: 10.1007/s13246-025-01585-3
Faruk Sanberk Kiziltas, Ozhan Ozkan, Fatih Toptan, Zuhal Dogan, Kadir Gokmen, Esra Gundogdu Eryilmaz, Ibrahim Kara, Ali Fuat Erdem
{"title":"The predictive power of hemodynamic data on postoperative neurocognitive impairment: a logistic regression and random forest approach.","authors":"Faruk Sanberk Kiziltas, Ozhan Ozkan, Fatih Toptan, Zuhal Dogan, Kadir Gokmen, Esra Gundogdu Eryilmaz, Ibrahim Kara, Ali Fuat Erdem","doi":"10.1007/s13246-025-01585-3","DOIUrl":"10.1007/s13246-025-01585-3","url":null,"abstract":"","PeriodicalId":48490,"journal":{"name":"Physical and Engineering Sciences in Medicine","volume":" ","pages":"1299-1310"},"PeriodicalIF":2.0,"publicationDate":"2025-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144486642","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
DGEAHorNet: high-order spatial interaction network with dual cross global efficient attention for medical image segmentation. 基于双交叉全局高效关注的高阶空间交互网络,用于医学图像分割。
IF 2 4区 医学
Physical and Engineering Sciences in Medicine Pub Date : 2025-09-01 Epub Date: 2025-07-24 DOI: 10.1007/s13246-025-01583-5
Haixin Peng, Xinjun An, Xue Chen, Zhenxiang Chen
{"title":"DGEAHorNet: high-order spatial interaction network with dual cross global efficient attention for medical image segmentation.","authors":"Haixin Peng, Xinjun An, Xue Chen, Zhenxiang Chen","doi":"10.1007/s13246-025-01583-5","DOIUrl":"10.1007/s13246-025-01583-5","url":null,"abstract":"<p><p>Medical image segmentation is a complex and challenging task, which aims to accurately segment various structures or abnormal regions in medical images. However, obtaining accurate segmentation results is difficult because of the great uncertainty in the shape, location, and scale of the target region. To address these challenges, we propose a higher-order spatial interaction framework with dual cross global efficient attention (DGEAHorNet), which employs a neural network architecture based on recursive gate convolution to adequately extract multi-scale contextual information from images. Specifically, a Dual Cross-Attentions (DCA) is added to the skip connection that can effectively blend multi-stage encoder features and narrow the semantic gap. In the bottleneck stage, global channel spatial attention module (GCSAM) is used to extract image global information. To obtain better feature representation, we feed the output from the GCSAM into the multi-branch dense layer (SENetV2) for excitation. Furthermore, we adopt Depthwise Over-parameterized Convolutional Layer (DO-Conv) in order to replace the common convolutional layer in the input and output part of our network, then add Efficient Attention (EA) to diminish computational complexity and enhance our model's performance. For evaluating the effectiveness of our proposed DGEAHorNet, we conduct comprehensive experiments on four publicly-available datasets, and achieving 0.9320, 0.9337, 0.9312 and 0.7799 in Dice similarity coefficient on ISIC2018, ISIC2017, CVC-ClinicDB and HRF respectively. Our results show that DGEAHorNet has better performance compared with advanced methods. The code is publicly available at https://github.com/penghaixin/mymodel .</p>","PeriodicalId":48490,"journal":{"name":"Physical and Engineering Sciences in Medicine","volume":" ","pages":"1265-1280"},"PeriodicalIF":2.0,"publicationDate":"2025-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144709488","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Optimum design of a biodegradable implant for femoral shaft fracture fixation using finite element method. 生物可降解股骨干骨折内固定物的有限元优化设计。
IF 2 4区 医学
Physical and Engineering Sciences in Medicine Pub Date : 2025-09-01 Epub Date: 2025-06-18 DOI: 10.1007/s13246-025-01562-w
Sina Taghipour, Farid Vakili-Tahami, Akbar Allahverdizadeh
{"title":"Optimum design of a biodegradable implant for femoral shaft fracture fixation using finite element method.","authors":"Sina Taghipour, Farid Vakili-Tahami, Akbar Allahverdizadeh","doi":"10.1007/s13246-025-01562-w","DOIUrl":"10.1007/s13246-025-01562-w","url":null,"abstract":"<p><p>Recent developments in biodegradable implant technology have expanded its use in several medical fields, such as orthopedics, cardiology, dentistry, and tissue engineering. Degradable bone-fixing implants, consisting of plates and screws, provide the advantage of completely degrading after efficaciously supporting the broken bone and can accelerate healing through nutrient release while maintaining mechanical stability. Magnesium alloys are considered promising options for bone implants owing to their natural degradability, biocompatibility, and potential to reduce long-term complications, but challenges such as rapid corrosion rate and lower mechanical strength compared to non-biodegradable materials may reduce structural strength before the broken bone completely heals. This article mainly concentrates on the design of a biodegradable implant plate for a femoral shaft fracture in the walking cycle, considering the plate's dimension, number of screws, biodegradation rate, and sufficient mechanical stability. Using the results of the numerical analyses, the safe zone of the implant plate design is determined based on the implant plate stress and the total displacement of the femur bone. Then, the appropriate number of screws and optimum topology of the plate are determined. The outcomes indicate that lengthening the implant plate significantly reduces stress and bone displacement. Reducing screw numbers increases stress and displacement, so fewer screws can be used for strong bones, while weaker bones require more screws for support, and topology optimization helps maintain satisfactory outcomes with minimal material use. This research lays the foundation for future studies that simultaneously consider implant material degradation and bone fracture healing.</p>","PeriodicalId":48490,"journal":{"name":"Physical and Engineering Sciences in Medicine","volume":" ","pages":"999-1014"},"PeriodicalIF":2.0,"publicationDate":"2025-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144327216","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
A novel time-frequency feature extraction method of EEG signals utilizing fractional synchrosqueezing wavelet transform. 基于分数阶同步压缩小波变换的脑电信号时频特征提取方法。
IF 2 4区 医学
Physical and Engineering Sciences in Medicine Pub Date : 2025-09-01 Epub Date: 2025-06-19 DOI: 10.1007/s13246-025-01580-8
Sheng-Wei Fei, Jia-le Chen, Yi-Bo Hu
{"title":"A novel time-frequency feature extraction method of EEG signals utilizing fractional synchrosqueezing wavelet transform.","authors":"Sheng-Wei Fei, Jia-le Chen, Yi-Bo Hu","doi":"10.1007/s13246-025-01580-8","DOIUrl":"10.1007/s13246-025-01580-8","url":null,"abstract":"<p><p>In order to improve the accuracy of Electroencephalogram (EEG) classification, Fractional Synchrosqueezing Wavelet Transform (FSSWT) is proposed to effectively overcome the contradiction between energy concentration and frequency separation in traditional time-frequency analysis methods. Firstly, the principle of FSSWT is introduced, and the time-frequency transformation equation for FSSWT applied to multi-frequency signals is established. The examples of synthetic signal and EEG signal show that the proposed method can suppress the mode aliasing of MI-EEG significantly while maintaining high resolution characteristics, and the energy concentration and related intermediate indexes perform well. The experimental results show that the proposed FSSWT-EEGDNN-ResNet model achieves an average classification accuracy of 95.17% under the condition of the MI-EEG signals processed by FSSWT of eight subjects, demonstrating the effectiveness of FSSWT in EEG signal feature extraction and classification.</p>","PeriodicalId":48490,"journal":{"name":"Physical and Engineering Sciences in Medicine","volume":" ","pages":"1237-1247"},"PeriodicalIF":2.0,"publicationDate":"2025-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144327215","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
A retrospective comparison of [18F]FDG radiation dose following a transition from conventional to long axial field of view PET/CT. 从常规PET/CT到长轴视场PET/CT过渡后[18F]FDG辐射剂量的回顾性比较
IF 2 4区 医学
Physical and Engineering Sciences in Medicine Pub Date : 2025-09-01 Epub Date: 2025-07-18 DOI: 10.1007/s13246-025-01588-0
Wei-Ting Jacky Chen, William I D Rae, Peter L Kench, Kathy P Willowson, Dale L Bailey, Elizabeth A Bailey, Heidi Fearnside, Eleanor Kelliher, Steven R Meikle
{"title":"A retrospective comparison of [<sup>18</sup>F]FDG radiation dose following a transition from conventional to long axial field of view PET/CT.","authors":"Wei-Ting Jacky Chen, William I D Rae, Peter L Kench, Kathy P Willowson, Dale L Bailey, Elizabeth A Bailey, Heidi Fearnside, Eleanor Kelliher, Steven R Meikle","doi":"10.1007/s13246-025-01588-0","DOIUrl":"10.1007/s13246-025-01588-0","url":null,"abstract":"<p><p>Long axial field of view (LAFOV) PET/CT scanners (> 1 m axial FOV) provide an order of magnitude higher system sensitivity compared with conventional scanners. This creates opportunities for significant radiation dose reductions for patients, without loss of diagnostic image quality or increased scan time. This study aimed to investigate changes in radiation dose received by patients undergoing whole-body [<sup>18</sup>F]FDG PET/CT studies at a metropolitan hospital following the transition from the Siemens Biograph mCT (21.8 cm axial FOV) to the Siemens Biograph Vision Quadra LAFOV PET/CT (106 cm axial FOV). For the mCT and Quadra, 484 and 554 patient studies were reviewed, respectively. The radiation dose from the PET component was derived from the recorded FDG dose, calculated based on ICRP recommendations, and scaled to patient weight. The CT dose was derived from the dose-length product. The median effective dose from the PET component for the mCT and Quadra was 6.2 (IQR 5.5-6.9) and 2.9 (IQR 2.8-3.6) mSv, respectively, and 5.7 (IQR 5.1-6.5) and 2.8 (IQR 2.4-3.4) mSv, respectively, when scaled to patient weight. The median effective dose from the CT component for the mCT and Quadra was 7.7 (IQR 6.2-9.4) and 7.6 (IQR 5.9-9.4) mSv, respectively. The total median effective dose combining PET and CT components for the mCT and Quadra was 13.9 (IQR 12.4-15.7) and 10.5 (IQR 9.4-12.3) mSv, respectively, and 13.5 (IQR 12.4-15.0) and 10.3 (IQR 9.3-11.9) mSv, respectively, when scaled to patient weight. While the effective dose from PET was approximately halved due to reduced injected activity, the CT effective dose remained relatively unchanged and is now the dominant source of radiation dose to the patient for LAFOV PET/CT.</p>","PeriodicalId":48490,"journal":{"name":"Physical and Engineering Sciences in Medicine","volume":" ","pages":"1337-1349"},"PeriodicalIF":2.0,"publicationDate":"2025-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144660767","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Evolutionary optimization-based descendent adaptive filter for noise confiscation in electrocardiogram signals. 基于进化优化的下降自适应滤波在心电图信号中的应用。
IF 2 4区 医学
Physical and Engineering Sciences in Medicine Pub Date : 2025-09-01 DOI: 10.1007/s13246-025-01631-0
Shubham Yadav, Suman Kumar Saha, Rajib Kar, Prabhat Dansena
{"title":"Evolutionary optimization-based descendent adaptive filter for noise confiscation in electrocardiogram signals.","authors":"Shubham Yadav, Suman Kumar Saha, Rajib Kar, Prabhat Dansena","doi":"10.1007/s13246-025-01631-0","DOIUrl":"https://doi.org/10.1007/s13246-025-01631-0","url":null,"abstract":"<p><p>Electrocardiogram (ECG) signals are usually contaminated by numerous artefacts during the recording process, and the quality of physiological information related to the heart is compromised. Due to this, artefact cancellation has become necessary for ECG signals. In this paper, swarm intelligence-based optimally tuned adaptive noise cancellers (ANCs) have been proposed and applied to denoise the ECG signal. The results have been analysed both qualitatively and quantitatively for noise cancellation from ECG signals through the ANCs optimized by using the seagull optimization algorithm (SOA), the Neighbourhood-based lineal population size success history-based adaptive differential evolution (NLSHADE) algorithm and the hyperbolic gravitational search algorithm (HGSA). The performance of the proposed methodology has been validated by using the additive white Gaussian noise at a diverse signal-to-noise ratio (SNR) on two publicly available datasets of ECG signal from the arrhythmia database (ADB) and QT ECG database (QTDB). The reference noise for ANC was considered using the noise stress test database (NSTDB). The performance of SOA-assisted ANC has been tested with the help of the Wilcoxon signed-rank test. The proposed technique-based ANCs supplied an enhanced percentage root mean squared deviation (PRD) value of 3.40E-03, mean squared error (MSE) value of 1.35E-11 and mean SNR improvement of 10.986 dB as compared to the reported state-of-the-art methods along with the benchmark competent algorithms, namely NLSHADE and HGSA.</p>","PeriodicalId":48490,"journal":{"name":"Physical and Engineering Sciences in Medicine","volume":" ","pages":""},"PeriodicalIF":2.0,"publicationDate":"2025-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144974805","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
0
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
相关产品
×
本文献相关产品
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:604180095
Book学术官方微信