Physical and Engineering Sciences in Medicine最新文献

{"title":"Frontal EEG correlation based human emotion identification and classification.","authors":"S V Thiruselvam, M Ramasubba Reddy","doi":"10.1007/s13246-024-01495-w","DOIUrl":"https://doi.org/10.1007/s13246-024-01495-w","url":null,"abstract":"<p><p>Humans express their feelings and intentions of their actions or communication through emotions. Recent advancements in technology involve machines in human communication in day-to-day life. Thus, understanding of human emotions by machines will be very helpful in assisting the user in a far better way. Various physiological and non-physiological signals can be used to make the machines to recognize the emotion of a person. The identification of emotional content in the signals is crucial to understand emotion and the machines act with emotional intelligence at appropriate times, thus providing a better human machine interaction with emotion identification system and mental health monitoring for psychiatric patients. This work includes the creation of an emotion EEG dataset, the development of an algorithm for identifying the emotion elicitation segments in the EEG signal, and the classification of emotions from EEG signals. The EEG signals are divided into 3s segments, and the segments with emotional content are selected based on the decrease in correlation between the frontal electrodes. The selected segments are validated with the facial expressions of the subjects in the appropriate time segments of the face video. EEGNet is used to classify the emotion from the EEG signal. The classification accuracy with the selected emotional EEG segments is higher compared to the accuracy using all the EEG segments. In subject-specific classification, an average accuracy of 80.87% is obtained from the network trained with selected EEG segments, and 70.5% is obtained from training with all EEG segments. In subject-independent classification, the accuracy of classification is 67% and 63.8% with and without segment selection, respectively. The proposed method of selection of EEG segments is validated using the DEAP dataset, and classification accuracies and F1-scores of subject dependent and subject-independent methods are presented.</p>","PeriodicalId":48490,"journal":{"name":"Physical and Engineering Sciences in Medicine","volume":" ","pages":""},"PeriodicalIF":2.4,"publicationDate":"2024-11-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142630446","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}

{"title":"Publisher Correction to: Sensitivity improvement of a deuterium-deuterium neutron generator based in vivo neutron activation analysis (IVNAA) system.","authors":"Song Yue, Sana Tabbassum, Elizabeth Helen Jaye, Cheryl A M Anderson, Linda H Nie","doi":"10.1007/s13246-024-01497-8","DOIUrl":"https://doi.org/10.1007/s13246-024-01497-8","url":null,"abstract":"","PeriodicalId":48490,"journal":{"name":"Physical and Engineering Sciences in Medicine","volume":" ","pages":""},"PeriodicalIF":2.4,"publicationDate":"2024-11-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142630467","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}

{"title":"CT scatter spectra transmission data of 80, 100, 120 and 140 kVp primary beams for various shielding materials.","authors":"S M Edwards","doi":"10.1007/s13246-024-01494-x","DOIUrl":"https://doi.org/10.1007/s13246-024-01494-x","url":null,"abstract":"<p><p>The shielding of computed tomography (CT) suites has commonly relied on the assumption that the primary beam has the same beam quality and thus penetrability as the scattered radiation. This report expands on a preliminary work that showed scattered radiation from patients having an overall reduced beam quality, with published transmission data for 120 kVp and 140 kVp through lead. Beam quality data of patient scatter spectra for 80 kVp and 100 kVp are uniquely provided herein using the same methodology, expanding the diagnostic energy range. The mean energy of scatter radiation spectra across this 80-140 kVp diagnostic range was found to have a reduction of 13.4-17.9% compared to a primary beam with a defined 9.8 mm Al added filtration. A DOSXYZnrc Monte Carlo program using the EGSnrc photon and electron transport code was subsequently used to simulate the transmission of scattered spectra of all 80, 100, 120 and 140 kVp beams through various commonly used shielding materials, including lead, concrete, steel, plate glass and gypsum wallboard. Transmission data and Archer fitting coefficients for this scattered radiation were calculated and show a reduction in transmission over the range of practical shielding thicknesses for these materials. Transmission through lead was significantly reduced in comparison to the National Council of Radiological Protection (NCRP) and British Institute of Radiology (BIR) methodologies using primary beam spectra, with transmissions reduced between 40.4 and 63.9% for 120 kVp and between 38.1 and 42% for 140 kVp beams over a 0.44-2.64 mm thickness range. The use of CT scatter spectra and their resultant transmission data is recommended for optimal shielding design.</p>","PeriodicalId":48490,"journal":{"name":"Physical and Engineering Sciences in Medicine","volume":" ","pages":""},"PeriodicalIF":2.4,"publicationDate":"2024-11-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142630519","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}

{"title":"Improvement of plan quality in whole-breast radiation following BCS using feasibility DVH by less-experienced planners.","authors":"Yun Zhang, Yuling Huang, Mingming Luo, Xingxing Yuan, Xiaoping Wang, Changfei Gong","doi":"10.1007/s13246-024-01493-y","DOIUrl":"https://doi.org/10.1007/s13246-024-01493-y","url":null,"abstract":"<p><p>Variability in plan quality of radiotherapy is commonly attributed to the planner's skill rather than technological parameters. While experienced planners can set reasonable parameters before optimization, less experienced planners face challenges. This study aimed to assess the quality of volumetric-modulated arc therapy (VMAT) in patients with left-sided breast cancer following breast-conserving surgery. Twenty-eight patients requiring whole-breast irradiation were randomly selected for inclusion. Each patient underwent two VMAT treatment plans: one optimized by an experienced planner (VMAT-EXP group) and the other designed by a less experienced planner using feasibility dose-volume histogram (FDVH) parameters from PlanIQ (VMAT-FDVH group). Both plans aimed to deliver a prescription dose of 50 Gy in 25 fractions to the planning target volume (PTV). Dosimetry parameters for the PTV and organs at risk (OARs) were compared between the two groups. Both the VMAT-EXP and VMAT-FDVH groups met the clinical plan goals for PTV and OARs. VMAT-FDVH demonstrated a PTV coverage and homogeneity comparable to those of VMAT-EXP. Compared to VMAT-EXP plans, VMAT-FDVH plans resulted in a significant reduction in the mean ipsilateral lung dose, with an average decrease of 0.9 Gy (8.5 Gy vs. 7.6 Gy, P < 0.001). The V5Gy and V20Gy of the ipsilateral lung were also reduced by 3.2% and 1.8%, respectively. Minor differences were observed in the heart, contralateral lung, breast, and liver. Personalized objectives derived from the feasibility DVH tool facilitated the generation of acceptable VMAT plans. Less experienced planners achieved lower doses to the ipsilateral lung while maintaining adequate target coverage and homogeneity. These findings suggest the potential for the effective use of VMAT in in patients with left-sided breast cancer following breast-conserving surgery, especially when guided by feasibility DVH parameters.</p>","PeriodicalId":48490,"journal":{"name":"Physical and Engineering Sciences in Medicine","volume":" ","pages":""},"PeriodicalIF":2.4,"publicationDate":"2024-11-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142606834","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}

{"title":"<ArticleTitle xmlns:ns0=\"http://www.w3.org/1998/Math/MathML\">Re-evaluation of <ns0:math><ns0:mmultiscripts><ns0:mrow /> <ns0:mrow /> <ns0:mn>18</ns0:mn></ns0:mmultiscripts> </ns0:math> F-FDG absorbed and effective dose in adult and pediatric phantoms using DoseCalcs Monte Carlo platform: a validation study.","authors":"Tarik El Ghalbzouri, Tarek El Bardouni, Jaafar El Bakkali, Otman El Hajjaji, Hicham Satti, Assia Arectout, Maryam Hadouachi, Randa Yerru","doi":"10.1007/s13246-024-01492-z","DOIUrl":"https://doi.org/10.1007/s13246-024-01492-z","url":null,"abstract":"<p><p>Positron emission tomography (PET) using <math><mmultiscripts><mrow></mrow> <mrow></mrow> <mn>18</mn></mmultiscripts> </math> F-FDG is a well-known modality for the diagnosis of various diseases in patients of different ages, sexes, and states of health, which implies that internal radiation dosimetry is highly desired for different phantom anatomies. In this study, we validate \"DoseCalcs,\" a new Monte Carlo platform that combines personalized internal dosimetry calculations with Monte Carlo simulations. To achieve that, we used the specific absorbed fraction (SAF) calculated by DoseCalcs and those from ICRP publication 133 to estimate the absorbed dose per injected activity (AD/IA) and effective dose per injected activity (ED/IA) for <math><mmultiscripts><mrow></mrow> <mrow></mrow> <mn>18</mn></mmultiscripts> </math> F-FDG. The investigation focused on various voxelized phantoms representing different age groups, including adult male and female, and pediatric phantoms of various ages, from newborn to 15 years old. Using the DoseCalcs Monte Carlo platform, we have simulated the emission of <math><mmultiscripts><mrow></mrow> <mrow></mrow> <mn>18</mn></mmultiscripts> </math> F-FDG positrons based on the energy spectrum provided in ICRP publication 107. The results demonstrated the impact of anatomical differences and different organ/tissue compositions on radiation absorption, with significant variations in the AD/IA across different phantoms. Interestingly, organs/tissues near the emission source showed higher AD/IA, highlighting the anatomical dependence on the phantom. When our results were compared to established reference data, especially from ICRP128, most organs/tissues had good agreement. Still, some cases have shown differences. This shows how important it is to use accurate radionuclide data and biokinetic modeling in internal dosimetry calculations. Furthermore, we compared AD/IA and ED/IA values calculated in newborns by DoseCalcs with those derived from alternative codes, MCNP and EGSnrc. While the results generally exhibited consistency, subtle variations underscored the influence of biokinetics modeling choices and computational methodologies. Overall, this research contributes valuable insights into the precision of internal dosimetry calculations using \"DoseCalcs-Gui\" by providing one platform for Monte Carlo simulation and personalized internal dosimetry in nuclear medicine. The DoseCalcs platform is free for research and available for download at www.github.com/TarikEl/DoseCalcs-Gui .</p>","PeriodicalId":48490,"journal":{"name":"Physical and Engineering Sciences in Medicine","volume":" ","pages":""},"PeriodicalIF":2.4,"publicationDate":"2024-11-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142584449","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}

{"title":"Improving deep learning U-Net++ by discrete wavelet and attention gate mechanisms for effective pathological lung segmentation in chest X-ray imaging.","authors":"Faiçal Alaoui Abdalaoui Slimani, M'hamed Bentourkia","doi":"10.1007/s13246-024-01489-8","DOIUrl":"https://doi.org/10.1007/s13246-024-01489-8","url":null,"abstract":"<p><p>Since its introduction in 2015, the U-Net architecture used in Deep Learning has played a crucial role in medical imaging. Recognized for its ability to accurately discriminate small structures, the U-Net has received more than 2600 citations in academic literature, which motivated continuous enhancements to its architecture. In hospitals, chest radiography is the primary diagnostic method for pulmonary disorders, however, accurate lung segmentation in chest X-ray images remains a challenging task, primarily due to the significant variations in lung shapes and the presence of intense opacities caused by various diseases. This article introduces a new approach for the segmentation of lung X-ray images. Traditional max-pooling operations, commonly employed in conventional U-Net++ models, were replaced with the discrete wavelet transform (DWT), offering a more accurate down-sampling technique that potentially captures detailed features of lung structures. Additionally, we used attention gate (AG) mechanisms that enable the model to focus on specific regions in the input image, which improves the accuracy of the segmentation process. When compared with current techniques like Atrous Convolutions, Improved FCN, Improved SegNet, U-Net, and U-Net++, our method (U-Net++-DWT) showed remarkable efficacy, particularly on the Japanese Society of Radiological Technology dataset, achieving an accuracy of 99.1%, specificity of 98.9%, sensitivity of 97.8%, Dice Coefficient of 97.2%, and Jaccard Index of 96.3%. Its performance on the Montgomery County dataset further demonstrated its consistent effectiveness. Moreover, when applied to additional datasets of Chest X-ray Masks and Labels and COVID-19, our method maintained high performance levels, achieving up to 99.3% accuracy, thereby underscoring its adaptability and potential for broad applications in medical imaging diagnostics.</p>","PeriodicalId":48490,"journal":{"name":"Physical and Engineering Sciences in Medicine","volume":" ","pages":""},"PeriodicalIF":2.4,"publicationDate":"2024-11-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142569956","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}

{"title":"Sensitivity improvement of a deuterium-deuterium neutron generator based in vivo neutron activation analysis (IVNAA) system.","authors":"Song Yue, Sana Tabbassum, Elizabeth Helen Jaye, Cheryl A M Anderson, Linda H Nie","doi":"10.1007/s13246-024-01487-w","DOIUrl":"10.1007/s13246-024-01487-w","url":null,"abstract":"<p><p>Our lab has been developing a deuterium-deuterium (DD) neutron generator-based neutron activation analysis (NAA) system to quantify metals and elements in the human body in vivo. The system has been used to quantify metals such as manganese, aluminum, sodium in bones of a living human. The technology provides a useful way to assess metal exposure and to estimate elemental deposition, storage and biokinetics. It has great potential to be applied in the occupational and environmental health fields to study the association of metal exposure and various health outcomes, as well as in the nutrition field to study the intake of essential elements and human health. However, the relatively low sensitivity of the system has greatly limited its applications. Neutron moderation plays an important role in designing an IVNAA facility, as it affects thermal neutron flux in irradiation cave and radiation exposure to the human subject. This study aims to develop a novel thermal neutron enhancement method to improve the sensitivity of the in vivo neutron activation analysis (IVNAA) system for elemental measurement but still maintain radiation dose. Utilizing a compact DD neutron source, we propose a new and practical moderator design that combines high density polyethylene with heavy water to enhance thermal neutrons by reducing thermal neutron absorption. All material dimensions are calculated by PHITS, a general-purpose Monte Carlo simulation program. The improvement of the new design predicted by the Monte Carlo simulation for the quantification of one of the elements, manganese was verified by experimental irradiation of manganese-doped bone equivalent phantoms. For the same radiation dose, a 67.9% thermal neutron flux enhancement is reached. With only 4.2% increase of radiation dose, the simulated thermal neutron flux and activation can be further increased by 84.2%. A 100% thermal neutron enhancement ratio is also achievable with a 20% dose increase. The experimental results clearly show higher manganese activation gamma ray counts for each specific phantom, with a significantly reduced minimum detection limit. Additionally, the photon dose was suppressed. The thermal neutron enhancement method can increase the number of useful neutrons significantly but maintain the radiation dose. This greatly decreased the detection limit of the system for elemental quantification at an acceptable dose, which will broadly expand the application of the technology in research and clinical use. The method can also be applied to other neutron medical applications, including neutron imaging and radiotherapy.</p>","PeriodicalId":48490,"journal":{"name":"Physical and Engineering Sciences in Medicine","volume":" ","pages":""},"PeriodicalIF":2.4,"publicationDate":"2024-10-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142510616","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}

{"title":"Unsupervised generative model for simulating post-operative double eyelid image.","authors":"Renzhong Wu, Shenghui Liao, Peishan Dai, Fuchang Han, Xiaoyan Kui, Xuefei Song","doi":"10.1007/s13246-024-01488-9","DOIUrl":"https://doi.org/10.1007/s13246-024-01488-9","url":null,"abstract":"<p><p>Simulating the outcome of double eyelid surgery is a challenging task. Many existing approaches rely on complex and time-consuming 3D digital models to reconstruct facial features for simulating facial plastic surgery outcomes. Some recent research performed a simple affine transformation approach based on 2D images to simulate double eyelid surgery outcomes. However, these methods have faced challenges, such as generating unnatural simulation outcomes and requiring manual removal of masks from images. To address these issues, we have pioneered the use of an unsupervised generative model to generate post-operative double eyelid images. Firstly, we created a dataset involving pre- and post-operative 2D images of double eyelid surgery. Secondly, we proposed a novel attention-class activation map module, which was embedded in a generative adversarial model to facilitate translating a single eyelid image to a double eyelid image. This innovative module enables the generator to selectively focus on the eyelid region that differentiates between the source and target domain, while enhancing the discriminator's ability to discern differences between real and generated images. Finally, we have adjusted the adversarial consistency loss to guide the generator in preserving essential features from the source image and eliminating any masks when generating the double eyelid image. Experimental results have demonstrated the superiority of our approach over existing state-of-the-art techniques.</p>","PeriodicalId":48490,"journal":{"name":"Physical and Engineering Sciences in Medicine","volume":" ","pages":""},"PeriodicalIF":2.4,"publicationDate":"2024-10-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142478061","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}

{"title":"PPG2RespNet: a deep learning model for respirational signal synthesis and monitoring from photoplethysmography (PPG) signal","authors":"Md Nazmul Islam Shuzan, Moajjem Hossain Chowdhury, Saadia Binte Alam, Mamun Bin Ibne Reaz, Muhammad Salman Khan, M. Murugappan, Muhammad E. H. Chowdhury","doi":"10.1007/s13246-024-01482-1","DOIUrl":"https://doi.org/10.1007/s13246-024-01482-1","url":null,"abstract":"<p>Breathing conditions affect a wide range of people, including those with respiratory issues like asthma and sleep apnea. Smartwatches with photoplethysmogram (PPG) sensors can monitor breathing. However, current methods have limitations due to manual parameter tuning and pre-defined features. To address this challenge, we propose the PPG2RespNet deep-learning framework. It draws inspiration from the UNet and UNet + + models. It uses three publicly available PPG datasets (VORTAL, BIDMC, Capnobase) to autonomously and efficiently extract respiratory signals. The datasets contain PPG data from different groups, such as intensive care unit patients, pediatric patients, and healthy subjects. Unlike conventional U-Net architectures, PPG2RespNet introduces layered skip connections, establishing hierarchical and dense connections for robust signal extraction. The bottleneck layer of the model is also modified to enhance the extraction of latent features. To evaluate PPG2RespNet’s performance, we assessed its ability to reconstruct respiratory signals and estimate respiration rates. The model outperformed other models in signal-to-signal synthesis, achieving exceptional Pearson correlation coefficients (PCCs) with ground truth respiratory signals: 0.94 for BIDMC, 0.95 for VORTAL, and 0.96 for Capnobase. With mean absolute errors (MAE) of 0.69, 0.58, and 0.11 for the respective datasets, the model exhibited remarkable precision in estimating respiration rates. We used regression and Bland-Altman plots to analyze the predictions of the model in comparison to the ground truth. PPG2RespNet can thus obtain high-quality respiratory signals non-invasively, making it a valuable tool for calculating respiration rates.</p>","PeriodicalId":48490,"journal":{"name":"Physical and Engineering Sciences in Medicine","volume":"6 1","pages":""},"PeriodicalIF":4.4,"publicationDate":"2024-09-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142252040","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}

{"title":"Effect of mirror system and scanner bed of a flatbed scanner on lateral response artefact in radiochromic film dosimetry","authors":"Tarafder Shameem, Nick Bennie, Martin Butson, David Thwaites","doi":"10.1007/s13246-024-01478-x","DOIUrl":"https://doi.org/10.1007/s13246-024-01478-x","url":null,"abstract":"<p>Radiochromic film, evaluated with flatbed scanners, is used for practical radiotherapy QA dosimetry. Film and scanner component effects contribute to the Lateral Response Artefact (LRA), which is further enhanced by light polarisation from both. This study investigates the scanner bed’s contribution to LRA and also polarisation from the mirrors for widely used EPSON scanners, as part of broader investigations of this dosimetry method aiming to improve processes and uncertainties. Alternative scanner bed materials were compared on a modified EPSON V700 scanner. Polarisation effects were investigated for complete scanners (V700, V800, on- and off-axis, and V850 on-axis), for a removed V700 mirror system, and independently using retail-quality single mirror combinations simulating practical scanner arrangements, but with varying numbers (0–5) and angles. Some tests had no film present, whilst others included films (EBT3) irradiated to 6 MV doses of 0–11.3 Gy. For polarisation analysis, images were captured by a Canon 7D camera with 50 mm focal length lens. Different scanner bed materials showed only small effects, within a few percent, indicating that the normal glass bed is a good choice. Polarisation varied with scanner type (7–11%), increasing at 10 cm lateral off-axis distance by around a further 6%, and also with film dose. The V700 mirror system showed around 2% difference to the complete scanner. Polarization increased with number of mirrors in the single mirror combinations, to 14% for 4 and 5 mirrors, but specific values depend on angles and mirror quality. Novel film measurement methods could reduce LRA effect corrections and associated uncertainties.</p>","PeriodicalId":48490,"journal":{"name":"Physical and Engineering Sciences in Medicine","volume":"26 1","pages":""},"PeriodicalIF":4.4,"publicationDate":"2024-09-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142184071","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}