Journal of Medical Imaging and Radiation Sciences最新文献

{"title":"Beyond the Machine: A Radiographer's Tale","authors":"Shayne Chau","doi":"10.1016/j.jmir.2024.101771","DOIUrl":"10.1016/j.jmir.2024.101771","url":null,"abstract":"","PeriodicalId":46420,"journal":{"name":"Journal of Medical Imaging and Radiation Sciences","volume":"56 1","pages":"Article 101771"},"PeriodicalIF":1.3,"publicationDate":"2024-10-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142553384","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Innovative Learning Activities to Prepare Radiography Students for Final-Year Clinical Placements: An Educational Perspective","authors":"Yobelli Alexandra Jimenez,&nbsp;Laura Di Michele,&nbsp;Susan Said,&nbsp;Peter Kench,&nbsp;Frances Gray","doi":"10.1016/j.jmir.2024.101784","DOIUrl":"10.1016/j.jmir.2024.101784","url":null,"abstract":"<div><h3>Introduction/Background</h3><div>The aim of this educational perspective is to describe a program of learning activities developed to prepare radiography students for final year clinical placements. Authors’ reflections are integrated with student feedback to discuss the educational value and feasibility of implementing the activities presented.</div></div><div><h3>Methods</h3><div>A program of six components was developed: (1) Simulation-based learning, (2) clinical supervision, (3) tutorials and workshops, (4) medical imaging facility learning tours (5) lecture series and (6) journal club. Student volunteers provided anonymous and voluntary feedback on each activity's engagement, effectiveness, promotion of interaction and collaboration, role in future placement or professional role, and the perceived value to their learning needs.</div></div><div><h3>Results</h3><div>Activities with clear links to practice were rated highest by students, including clinical supervision, 2-day simulation program, CT tutorials and interprofessional simulation. All students reported that half of all activities (6/12, 50%) were either very valuable or valuable, with only a minority of students indicating three activities to not be valuable to their learning needs.</div></div><div><h3>Discussion</h3><div>Student feedback highlighted activities considered to support skill development, stemming from active learning opportunities. Overall characteristics considered to support students’ clinical skill development were interprofessional teaching team, mixture of activities including simulation, and collaboration with clinical and industry partners.</div></div><div><h3>Conclusion</h3><div>Based on student feedback and academics’ perceptions of suitability of activities for preparing students for final year clinical placement, faculty have shifted their focus towards dedicated resources to support scale-up and sustainability pertaining to integration into curriculum. The goal is to embed these activities into the core curriculum, offering students consistent, up-to-date learning, while expanding preparatory activities with diverse, specialised clinical scenarios to better prepare them for practice.</div></div>","PeriodicalId":46420,"journal":{"name":"Journal of Medical Imaging and Radiation Sciences","volume":"56 1","pages":"Article 101784"},"PeriodicalIF":1.3,"publicationDate":"2024-10-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142553385","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Enhancing radiation therapy student's cultural competency and safety of Canadian Indigenous populations using cultural immersion","authors":"T. Lundstrom ,&nbsp;K. Osmar ,&nbsp;K. Fitzpatrick ,&nbsp;S. Fawcett ,&nbsp;A. Bolderston ,&nbsp;R. Lightning ,&nbsp;H. McKennitt","doi":"10.1016/j.jmir.2024.101723","DOIUrl":"10.1016/j.jmir.2024.101723","url":null,"abstract":"<div><h3>Introduction</h3><div>Indigenous peoples in Canada have a higher cancer burden and shorter life expectancy compared to the non-Indigenous population. Canada's colonial legacy has resulted in many Indigenous people experiencing high mistrust in healthcare providers which can result in healthcare avoidance, such as delays seeking preventative care as well as lower screening rates. This may be compounded by language barriers as well as a lack of culturally safe care in healthcare settings. Cultural competency and safety education, which can include cultural immersion methods, has been widely prioritized and implemented in health care and academic institutions. This manuscript reports the results of a pilot cultural immersion experience in an Indigenous community (Maskwacîs, Treaty 6 Territory) for University of Alberta Radiation Therapy Department radiation therapy students and clinical faculty.</div></div><div><h3>Methods</h3><div>This project used the Etuaptmumk or Two-Eyed Seeing approach as the research framework to tie Western methodologies with Indigenous knowledge. The cultural immersion day included a sweat lodge ceremony, a traditional lunch and a sharing circle. Following the event, two focus groups were conducted to gather participants’ perspectives. The discussions were transcribed and the data was analysed thematically.</div></div><div><h3>Results</h3><div>Seven senior radiation therapy students and five faculty members participated in the cultural immersion day. The majority of the feedback from the day was positive. The four main themes that emerged from the focus groups were; (1) enhanced cultural safety, (2) improved peer to peer and peer to educator relationships, (3) responsibility to social accountability, advocacy, and personal growth, and (4) facilitation of a bridge between Western and Indigenous views.</div></div><div><h3>Conclusion</h3><div>Support for Indigenous patients with cancer and caregivers is essential to improve care in the radiation therapy department. As this pilot project was a success, the cultural immersion day is now a component of the cultural competency and safety training for radiation therapy students at the University of Alberta. However, more opportunities are needed for staff to consistently facilitate and foster culturally safe care for Indigenous patients undergoing radiation therapy.</div></div>","PeriodicalId":46420,"journal":{"name":"Journal of Medical Imaging and Radiation Sciences","volume":"55 4","pages":"Article 101723"},"PeriodicalIF":1.3,"publicationDate":"2024-10-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142515446","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Current Radiology workforce perspective on the integration of artificial intelligence in clinical practice: A systematic review","authors":"Samuel Arkoh ,&nbsp;Theophilus N. Akudjedu ,&nbsp;Cletus Amedu ,&nbsp;William K. Antwi ,&nbsp;Wiam Elshami ,&nbsp;Benard Ohene-Botwe","doi":"10.1016/j.jmir.2024.101769","DOIUrl":"10.1016/j.jmir.2024.101769","url":null,"abstract":"<div><h3>Introduction</h3><div>Artificial Intelligence (AI) represents the application of computer systems to tasks traditionally performed by humans. The medical imaging profession has experienced a transformative shift through the integration of AI. While there have been several independent primary studies describing various aspects of AI, the current review employs a systematic approach towards describing the perspectives of radiologists and radiographers about the integration of AI in clinical practice. This review provides a holistic view from a professional standpoint towards understanding how the broad spectrum of AI tools are perceived as a unit in medical imaging practice.</div></div><div><h3>Methods</h3><div>The study utilised a systematic review approach to collect data from quantitative, qualitative, and mixed-methods studies. Inclusion criteria encompassed articles concentrating on the viewpoints of either radiographers or radiologists regarding the incorporation of AI in medical imaging practice. A stepwise approach was employed in the systematic search across various databases. The included studies underwent quality assessment using the Quality Assessment Tool for Studies with Diverse Designs (QATSSD) checklist. A parallel-result convergent synthesis approach was employed to independently synthesise qualitative and quantitative evidence and to integrate the findings during the discussion phase.</div></div><div><h3>Results</h3><div>Forty-one articles were included, all of which employed a cross-sectional study design. The main findings were themed around considerations and perspectives relating to AI education, impact on image quality and radiation dose, ethical and medico-legal implications for the use of AI, patient considerations and their perceived significance of AI for their care, and factors that influence development, implementation and job security. Despite varying emphasis, these themes collectively provide a global perspective on AI in medical imaging practice.</div></div><div><h3>Conclusion</h3><div>While expertise levels are varied and different, both radiographers and radiologists were generally optimistic about incorporation of AI in medical imaging practice. However, low levels of AI education and knowledge remain a critical barrier. Furthermore, equipment errors, cost, data security and operational difficulties, ethical constraints, job displacement concerns and insufficient implementation efforts are integration challenges that should merit the attention of stakeholders.</div></div>","PeriodicalId":46420,"journal":{"name":"Journal of Medical Imaging and Radiation Sciences","volume":"56 1","pages":"Article 101769"},"PeriodicalIF":1.3,"publicationDate":"2024-10-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142515447","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"For the busy clinical-imaging professional in an AI world: Gaining intuition about deep learning without math","authors":"Dolly Y. Wu ,&nbsp;Dat T. Vo ,&nbsp;Stephen J. Seiler","doi":"10.1016/j.jmir.2024.101762","DOIUrl":"10.1016/j.jmir.2024.101762","url":null,"abstract":"<div><div>Medical diagnostics comprise recognizing patterns in images, tissue slides, and symptoms. Deep learning algorithms (DLs) are well suited to such tasks, but they are black boxes in various ways. To explain DL Computer-Aided Diagnostic (CAD) results and their accuracy to patients, to manage or drive the direction of future medical DLs, to make better decisions with CAD, etc., clinical professionals may benefit from hands-on, under-the-hood lessons about medical DL. For those who already have some high-level knowledge about DL, the next step is to gain a more-fundamental understanding of DLs, which may help illuminate inside the boxes. The objectives of this Continuing Medical Education (CME) article include:<ul><li><span>•</span><span><div>Gain an intuitive understanding of DL</div></span></li><li><span>•</span><span><div>Learn example DL architectures for pattern recognition</div></span></li><li><span>•</span><span><div>Explore optimization of DLs and some factors that affect their accuracy using non-clinical images as input data</div></span></li><li><span>•</span><span><div>Gain insights from simulations to probe DL behavior and options to optimize DLs</div></span></li><li><span>•</span><span><div>Review lessons learned from the simulations</div></span></li></ul>Better understanding can come from relatable medical analogies and personally experiencing quick simulations to observe deep learning in action, akin to the way clinicians are trained to perform other tasks. We developed readily-implementable demonstrations and simulation exercises. We framed the exercises using analogies to breast cancer, malignancy and cancer stage as example diagnostic applications. The simulations revealed a nuanced relationship between DL output accuracy and the quantity and nature of the data. The simulation results provided lessons-learned and implications for the clinical world. Although we focused on DLs for diagnosis, they are similar to DLs for treatment (e.g. radiotherapy) so that treatment providers may also benefit from this tutorial.</div></div>","PeriodicalId":46420,"journal":{"name":"Journal of Medical Imaging and Radiation Sciences","volume":"56 1","pages":"Article 101762"},"PeriodicalIF":1.3,"publicationDate":"2024-10-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142515448","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Enhancing CT examination efficiency with ChatGPT-4o for multilingual Hajj pilgrims: A short communication","authors":"Yasser H. Hadi ,&nbsp;Fatimah K. Altalhi ,&nbsp;Hussam M. Ali ,&nbsp;Mohammed A. Shabli ,&nbsp;Abdulrahman I. Abu Aqil ,&nbsp;Andrew England","doi":"10.1016/j.jmir.2024.101781","DOIUrl":"10.1016/j.jmir.2024.101781","url":null,"abstract":"<div><h3>Introduction/background</h3><div>The annual Hajj pilgrimage brings millions of Muslims from diverse linguistic backgrounds to Makkah, Saudi Arabia. This poses significant communication challenges in medical settings, particularly during complex procedures like computed tomography (CT) examinations. In 2024, a tertiary care hospital integrated ChatGPT-4o real-time translation technology to address these challenges. This short communication aims to provide an initial assessment of the effectiveness of ChatGPT-4o in improving communication, procedure quality, and examination efficiency for multilingual Hajj pilgrims.</div></div><div><h3>Methods</h3><div>This quantitative study, conducted in the radiology department, analysed data from two periods: June 20 to July 8, 2023, and June 7 to June 23, 2024. Ethical clearance was obtained, and key variables measured included examination time (in minutes), patient throughput (cases per shift), and the number of scans with artifacts. Feedback on communication and satisfaction was gathered from both patients and radiographers. Paired t-tests were used to compare mean values of examination times, throughput, and artifact occurrence between the two periods, with a significance level set at <em>P</em> &lt; 0.05.</div></div><div><h3>Results</h3><div>A paired t-test revealed a statistically significant (<em>p</em> &lt; 0.01) reduction in mean examination time (from 15.4 (2.1) minutes in 2023 to 11.1 (1.7) minutes in 2024) following the introduction of ChatGPT-4o. This reduction corresponded with an increase in mean (standard deviation) patient throughput from 49.5 (4.8) cases per shift in 2023 to 56.2 (5.3) cases per shift in 2024 (<em>P</em> &lt; 0.01). The number of scans with artifacts also decreased significantly, from 30 out of 748 scans in 2023 to 8 out of 885 scans in 2024 (<em>P</em> &lt; 0.01).</div></div><div><h3>Discussion</h3><div>The integration of ChatGPT-4o significantly improved communication between healthcare providers and patients, leading to better compliance with procedure instructions and fewer repeat scans. Training programs facilitated efficient use of the technology by radiographers, further improving workflow efficiency. Despite initial integration and acceptance challenges, patients and radiographers reported high satisfaction with the improved communication and reduced stress levels.</div></div><div><h3>Conclusion</h3><div>This study demonstrates that ChatGPT-4o real-time translation improved patient communication, procedure quality, and examination efficiency. The technology reduced examination times and increased patient throughput, with positive feedback from patients and radiographers, indicating its effectiveness in multilingual medical settings.</div></div>","PeriodicalId":46420,"journal":{"name":"Journal of Medical Imaging and Radiation Sciences","volume":"56 1","pages":"Article 101781"},"PeriodicalIF":1.3,"publicationDate":"2024-10-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142484373","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Current Alberta radiation therapy care practices for patients with obesity and recommendations for improvement","authors":"Kerry Lui ,&nbsp;Alyssa Morin ,&nbsp;Mackenzie Smith ,&nbsp;Graydon Yee ,&nbsp;Amanda Bolderston ,&nbsp;Jacqueline M. Middleton ,&nbsp;Tina Wu ,&nbsp;Winter Dixon","doi":"10.1016/j.jmir.2024.101768","DOIUrl":"10.1016/j.jmir.2024.101768","url":null,"abstract":"<div><h3>Introduction</h3><div>Obesity has been associated with increased incidence of cancer thereby impacting the number of patients with obesity who may require radiation therapy (RT) treatment. Previous studies have detailed the impacts of obesity on RT treatment delivery including considerations when positioning, imaging, and communicating with patients. However, there is limited literature regarding best clinical practices used by Canadian RT departments when treating patients with obesity. This study aimed to answer the following question: How can the current standards of care (SOC) used by Alberta RT departments be improved to ensure safe and quality care of patients with obesity?</div></div><div><h3>Methods</h3><div>Semi-structured interviews were conducted with 19 practitioners including three RT managers, two medical physicists, two clinical educators, two radiation oncologists, a senior practice lead, and nine radiation therapists from five cancer centers across Alberta. Interviews were transcribed and analyzed independently by two researchers and used to inform recommendations for improvement to existing care practices.</div></div><div><h3>Results</h3><div>Four themes emerged as unique considerations for patients with obesity undergoing RT, which included technical factors, interpersonal interactions, patient care factors, and education and training. Recommendations to improve the current SOC in Alberta RT departments included the need for longer appointment times, sufficient staff, accessible mobility equipment, and additional education and training for HCPs tailored towards patients with obesity.</div></div><div><h3>Conclusion</h3><div>SOC in Alberta could be improved for patients with obesity with modified appointment time, increased staff and resources, and more in depth and tailored education. Implementation of these considerations and recommendations for improvement to the current SOC used by Alberta RT departments has the potential to ensure safe and quality care of patients with obesity.</div></div>","PeriodicalId":46420,"journal":{"name":"Journal of Medical Imaging and Radiation Sciences","volume":"56 1","pages":"Article 101768"},"PeriodicalIF":1.3,"publicationDate":"2024-10-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142484372","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Perceptions of radiographers on reporting chest images at Public Hospitals in Malawi","authors":"George Simwaba ,&nbsp;Lynne Janette Hazell ,&nbsp;Jennifer Motto","doi":"10.1016/j.jmir.2024.101764","DOIUrl":"10.1016/j.jmir.2024.101764","url":null,"abstract":"<div><h3>Introduction</h3><div>Malawi health facilities' major challenge is inequalities in access to reporting services due to a shortage of radiologists to report on radiographic images. Radiographers in the developed world acquire formal training in image reporting, however, there is no postgraduate training programme in Malawi. Thus, there is a need to explore radiographers' perceptions of reporting chest images in Malawi's hospitals. The study aims to explore radiographers’ perceptions of being tasked with the responsibility of reporting on chest images at public hospitals in Malawi.</div></div><div><h3>Method</h3><div>The study was conducted through a quantitative cross-sectional design. Data was collected using a self-developed questionnaire. Data collected was analyzed with the assistance of a statistician using the Statistical Package for Social Scientists (SPSS) version 29. The measurement scales and questions included quantitative 10-point Likert. Statistical analysis used the Mann -Whitney U test.</div></div><div><h3>Results</h3><div>Seventy-one (71) radiographers representing 81 % of the total population from five public hospitals participated in the study. The results from this study found that most radiographers (97.2 %) agreed that radiographers needed to report on chest images in the department. Findings demonstrated that the majority of radiographers (80.3 %) supported ongoing professional development, and of the radiographers (78.9 %) also agreed that reporting on chest images required post-graduate training. Overall confidence in reporting chest images was 81.6 % with no difference by years worked as a qualified radiographer (p=0.196) with the less than 10 years were as confident to report chest images as 10 years or more . Confidence in detecting abnormality on chest images (78.8 %) demonstrated no variation by years worked as qualified radiographer (p=0. 196) or level in department (junior of senior radiographer (p =0.323). Perceived impact of radiographer's involvement in chest image reporting to improved cost effective service delivery, work efficiently, and potential impact on patient care and safety.</div></div><div><h3>Conclusion</h3><div>Based on the findings of this study, there were positive perceptions among the majority of radiographers about the reporting of chest images in Malawi. It was recommended that policymakers change Malawi's health care policy, especially the radiological sector to allow radiographers to report on chest images.</div></div>","PeriodicalId":46420,"journal":{"name":"Journal of Medical Imaging and Radiation Sciences","volume":"56 1","pages":"Article 101764"},"PeriodicalIF":1.3,"publicationDate":"2024-10-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142484374","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Assessment of Stroke Onset Time Based on DINOv2 Visual Features","authors":"Dr Jin-jin Wang","doi":"10.1016/j.jmir.2024.101479","DOIUrl":"10.1016/j.jmir.2024.101479","url":null,"abstract":"<div><h3>Background</h3><div>Currently, the thrombolytic treatment for acute ischemic stroke (AIS) strictly depends on the time since stroke onset (TSS) being less than 4.5 hours. However, some patients are excluded from thrombolytic treatment due to uncertain TSS. Clinically, diffusion-weighted imaging (DWI) and fluid-attenuated inversion recovery (FLAIR) mismatch are commonly used to roughly determine TSS.</div></div><div><h3>Methods</h3><div>In this paper, we propose a method based on DINOv2 to classify the TSS as less than or more than 4.5 hours. We conducted model training and external testing using case data from two hospitals. These hospitals respectively included 226 and 85 cases of TSS less than 4.5 hours, along with an equal number of cases with TSS greater than 4.5 hours. Firstly, we utilized DINOv2 for automatic segmentation of lesions and extraction of visual features from DWI and FLAIR images. Then, the visual features of the lesion area were input into four different machine learning models. Finally, a conclusion on whether the patient's onset time is more or less than 4.5 hours is reached through a weighted voting method.</div></div><div><h3>Results</h3><div>The results from the external test set show that in lesion segmentation from DWI and FLAIR images, the Dice coefficients were as high as 0.872 and 0.823, respectively. In the judgment of TTS less than 4.5 hours, our approach achieved an accuracy of 0.865, sensitivity of 0.843, and specificity of 0.902.</div></div><div><h3>Conclusion</h3><div>The assessment of TTS based on DINOv2 visual features demonstrates excellent performance. The results of this approach significantly surpass those of human doctors using the DWI-FLAIR mismatch method. Moreover, it achieves a fully automated process for rapid and efficient handling. This approach is expected to play a key role in treatment decision-making for patients with unknown TSS.</div></div>","PeriodicalId":46420,"journal":{"name":"Journal of Medical Imaging and Radiation Sciences","volume":"55 3","pages":"Article 101479"},"PeriodicalIF":1.3,"publicationDate":"2024-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142530050","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Signal Power Estimation and its Novel Applications in Radiology as two birds with one stone","authors":"Dr. Motohiro Tabuchi","doi":"10.1016/j.jmir.2024.101480","DOIUrl":"10.1016/j.jmir.2024.101480","url":null,"abstract":"<div><h3>Background/Purpose</h3><div>In radiology, MTF and SNR (or CNR) are known as established methods for evaluating the quality of phantom images. However, due to their complexity caused by multiple procedures involved in measuring of multiple ROI statistics such as mean, variance, etc., this study proposes a simplified signal power estimation method calculated directly from a pair of observed images. Then, in this research, MTF* and SNR* utilizing this proposed method are introduced as novel applications.</div></div><div><h3>Methods</h3><div>First, two observed phantom images are prepared by using the same imaging condition. Then, a signal power of the image is estimated from a covariance of a pair of the observed images using the following equation. V(<strong><em>x</em></strong>) = Cov(<strong><em>y</em></strong>₁, <strong><em>y</em></strong>₂) where V(<strong>·</strong>) and Cov(<strong>·</strong>) denote a variance and a covariance of <strong>·</strong> respectively. Here, <strong><em>x</em></strong> is a signal image vector, and <strong><em>y</em></strong>₁ and <strong><em>y</em></strong>₂ are observed image vectors obtained under the same imaging conditions, where <strong><em>y</em></strong> is constructed from the signal vector <strong><em>x</em></strong> summated the additive noise vector <strong><em>n</em></strong>, namely <strong><em>y</em></strong> = <strong><em>x</em></strong> + <strong><em>n</em></strong>. Finally, MTF* and SNR* are calculated using the estimated signal power V(<strong><em>x</em></strong>). The proposed methods are then compared with the conventional methods.</div></div><div><h3>Results</h3><div>While a direct comparison between conventional SNR and SNR* proved difficult due to differences in definition, both methods showed similar trends. On the other hand, the conventional MTF by Droege's method and the MTF* were almost in agreement with two significant figures as expected.</div></div><div><h3>Conclusion</h3><div>This investigation proposed simplified method for estimating signal power derived from the covariance of a pair of observed images. And this proposed method produced novel applications termed MTF* and SNR*, and has an more practical than the conventional method in terms of simplified procedure as two birds with one stone.</div></div>","PeriodicalId":46420,"journal":{"name":"Journal of Medical Imaging and Radiation Sciences","volume":"55 3","pages":"Article 101480"},"PeriodicalIF":1.3,"publicationDate":"2024-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142530051","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}