Journal of medical imaging and radiation sciences最新文献

{"title":"AWARENESS, KNOWLEDGE, AND CURRENT PRACTICE IN EYE LENS RADIATION PROTECTION AMONG INTERVENTIONAL RADIOLOGY AND CARDIOLOGY MEDICAL PERSONNEL IN MALAYSIA","authors":"Kamarulzaman Shahnulatiqa, M. Shafini, Abdul Karim Mohammad Azwin, Shamsuddin Nurul Saadiah, Olyvea Deloura, Emildah Pauli","doi":"10.1016/j.jmir.2023.06.134","DOIUrl":"https://doi.org/10.1016/j.jmir.2023.06.134","url":null,"abstract":"","PeriodicalId":94092,"journal":{"name":"Journal of medical imaging and radiation sciences","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"48620949","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":"CONTRAST-ENHANCED SPECTRAL MAMMOGRAPHY (CESM) VERSUS BREAST MAGNETIC RESONANCE IMAGING (MRI) IN BREAST CANCER DETECTION AMONG PATIENTS WITH NEWLY DIAGNOSED BREAST CANCER: A SYSTEMATIC REVIEW","authors":"Thew Jessica","doi":"10.1016/j.jmir.2023.06.129","DOIUrl":"https://doi.org/10.1016/j.jmir.2023.06.129","url":null,"abstract":"","PeriodicalId":94092,"journal":{"name":"Journal of medical imaging and radiation sciences","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"136265474","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":"EXPOSURE INDICES IN A BUSY INDONESIAN HOSPITAL SHOW VARYING LEVELS OF COMPLIANCE TO THE MANUFACTURER'S RECOMMENDATIONS: EXTENT OF NON-COMPLIANCE AND CAUSAL AGENTS","authors":"Putu Irma Wulandari, Putu Krisna Ariadi, I. M. Ayusta, P. Brennan","doi":"10.1016/j.jmir.2023.06.110","DOIUrl":"https://doi.org/10.1016/j.jmir.2023.06.110","url":null,"abstract":"","PeriodicalId":94092,"journal":{"name":"Journal of medical imaging and radiation sciences","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"44217585","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":"MAGNETIC RESONANCE IMAGING FOR RARE ABDOMINAL ECTOPIC PREGNANCY: A CASE REPORT","authors":"Triningsih Triningsih, P. Wulandari, I. P. Sugiartha","doi":"10.1016/j.jmir.2023.06.115","DOIUrl":"https://doi.org/10.1016/j.jmir.2023.06.115","url":null,"abstract":"","PeriodicalId":94092,"journal":{"name":"Journal of medical imaging and radiation sciences","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"48644374","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":"MITIGATING THE UMBRELLA ARTIFACT: EXPLORING ALTERNATIVE COUPLING AGENTS FOR IMPROVED ABDOMINAL SKIN ULTRASOUND","authors":"Muhammad Hanif Hakimi Zainudin, K. A. Abdullah","doi":"10.1016/j.jmir.2023.06.143","DOIUrl":"https://doi.org/10.1016/j.jmir.2023.06.143","url":null,"abstract":"","PeriodicalId":94092,"journal":{"name":"Journal of medical imaging and radiation sciences","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"43213825","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":"ADVANCEMENTS IN AI TRAINING AND EDUCATION FOR A FUTURE-READY HEALTHCARE SYSTEM","authors":"Kumar Shamie","doi":"10.1016/j.jmir.2023.06.122","DOIUrl":"https://doi.org/10.1016/j.jmir.2023.06.122","url":null,"abstract":"","PeriodicalId":94092,"journal":{"name":"Journal of medical imaging and radiation sciences","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"47064319","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":"SAFETY AND ACCURACY OF MULTIPLE PRENATAL ULTRASOUND EXAMINATIONS FOR FETAL GENDER IDENTIFICATION: A SCOPING REVIEW","authors":"F. A. Hadi, F. W. A. Zaiki","doi":"10.1016/j.jmir.2023.06.133","DOIUrl":"https://doi.org/10.1016/j.jmir.2023.06.133","url":null,"abstract":"","PeriodicalId":94092,"journal":{"name":"Journal of medical imaging and radiation sciences","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"44373998","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":"A COMPREHENSIVE REVIEW OF INDONESIAN DIAGNOSTIC REFERENCE LEVELS (IDRLs) FOR CT SCAN EXAMINATIONS","authors":"P. Wulandari, Ppw Gitawiarsa, Putu Adi Susanta","doi":"10.1016/j.jmir.2023.06.113","DOIUrl":"https://doi.org/10.1016/j.jmir.2023.06.113","url":null,"abstract":"","PeriodicalId":94092,"journal":{"name":"Journal of medical imaging and radiation sciences","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"49012753","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":"DIAGNOSTIC REFERENCE LEVEL OF RADIATION DOSE AND IMAGE QUALITY OF ADULT CT ABDOMINAL EXAMINATIONS IN A TERTIARY HOSPITAL IN MALAYSIA","authors":"Mohamad Asmawi Mohamad Ariffin, M. Karim","doi":"10.1016/j.jmir.2023.06.108","DOIUrl":"https://doi.org/10.1016/j.jmir.2023.06.108","url":null,"abstract":"","PeriodicalId":94092,"journal":{"name":"Journal of medical imaging and radiation sciences","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"47236520","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":"THE APPLICATION OF ARTIFICIAL INTELLIGENCE ON SCAR SEGMENTATION IN CARDIAC MAGNETIC RESONANCE IMAGING: A SYSTEMATIC LITERATURE REVIEW","authors":"Roslan Nurul Ashikin, Setiawan Agung Nugroho, Norzan Muhammad Ammar, Jasmin Nur Hayati","doi":"10.1016/j.jmir.2023.06.117","DOIUrl":"https://doi.org/10.1016/j.jmir.2023.06.117","url":null,"abstract":"OBJECTIVE We aimed to assess the application of Artificial Intelligence (AI) methodologies for scar segmentation in cardiac magnetic resonance (CMR) imaging and its performance evaluation. MATERIALS & METHODS Following PRISMA (Preferred Reporting Items for Systematic Review and Meta-Analyses) guidelines, a systematic search of PubMed and Science Direct was undertaken from 2012 to 2022 to search for full-text publications that implemented AI methods on scar segmentation in CMR in patients with cardiovascular diseases. RESULTS A total of 21 articles out of 475 articles were selected for the final review. Supervised deep learning and unsupervised machine learning were implemented in 16 (76.2%) and 5 (23.8%) articles respectively, favouring learning methods. Dice similarity coefficient (DSC) value was used as measures of the performance of AI methods in 19 articles. Supervised and unsupervised learning models had similar DSC compared to manual segmentation with a score of 0.74, 95% confidence interval (CI) [0.67, 0.81] vs 0.71, 95% CI [0.63, 0.79], P = 0.35). The application of AI has been advanced with the emerging of sophisticated algorithms allowing for quantification of border zone and microvascular obstruction regions. The performance of AI method is highly depending on the network architecture, training strategies, and data set used for training. CONCLUSION The presence of AI methods in scar segmentation demonstrated high feasibility with good performance evaluation for quantifying myocardial scar. This study can have a huge impact on clinicians in health care by improving their experiences with scar segmentation and enhancing clinically validated application of AI in CMR imaging. We aimed to assess the application of Artificial Intelligence (AI) methodologies for scar segmentation in cardiac magnetic resonance (CMR) imaging and its performance evaluation. Following PRISMA (Preferred Reporting Items for Systematic Review and Meta-Analyses) guidelines, a systematic search of PubMed and Science Direct was undertaken from 2012 to 2022 to search for full-text publications that implemented AI methods on scar segmentation in CMR in patients with cardiovascular diseases. A total of 21 articles out of 475 articles were selected for the final review. Supervised deep learning and unsupervised machine learning were implemented in 16 (76.2%) and 5 (23.8%) articles respectively, favouring learning methods. Dice similarity coefficient (DSC) value was used as measures of the performance of AI methods in 19 articles. Supervised and unsupervised learning models had similar DSC compared to manual segmentation with a score of 0.74, 95% confidence interval (CI) [0.67, 0.81] vs 0.71, 95% CI [0.63, 0.79], P = 0.35). The application of AI has been advanced with the emerging of sophisticated algorithms allowing for quantification of border zone and microvascular obstruction regions. The performance of AI method is highly depending on the network architecture, training","PeriodicalId":94092,"journal":{"name":"Journal of medical imaging and radiation sciences","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"136265481","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}