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Evaluation of medical Prescribers’ Theoretical Knowledge on medical imaging in the Northern Region of Burkina Faso

Open Journal of Radiology 2024年第2期14卷 33-41页

作者： Some Milckisédek Judicaël Marouruana Ouedraogo Pakisba Ali Tankoano Aïda Ida Savadogo Habibou Kindo Bassirou Ouedraogo Nina-Astrid Bamouni Yomboé Abel Diallo Ousseini Department of medical imaging Ouahigouya Regional University Hospital University of Ouahigouya Ouahigouya Burkina Faso Department of medical imaging Souro Sanou University Hospital Nazi Boni University Bobo Dioulasso Burkina Faso Department of medical imaging Bogodogo University Hospital Joseph Ki Zerbo University Ouagadougou Burkina Faso Workers Health Office Joseph Ki Zerbo University Ouagadougou Burkina Faso Department of medical imaging Yalgado Oudraogo University Hospital Joseph Ki Zerbo University Ouagadougou Burkina Faso

Introduction: medical imaging is a medical specialty that involves producing images of the human body and interpreting them for diagnostic, therapeutic purposes, and for monitoring the progress of pathologies. We aimed to assess the theoretical knowledge of doctors and interns in medical imaging in the northern region of Burkina Faso. Methodology: This was a descriptive cross-sectional survey based on a self-administered questionnaire. Prescribers knowledge was estimated based on scores derived from questionnaire responses. Results: We collected 106 questionnaires out of 163, i.e. a participation rate of 65.03%. The average knowledge score was 81.71% for the contribution of medical imaging to patient management. It was 60.02% for the indications/counter-indications of radiological examinations and 72.56% for the risks associated with exposure to radiation during these examinations. The score was 59.83% for the methods used to select the appropriate radiological examination. As regards the completeness of the clinical and biological information on the forms requesting imaging examinations, the score was 96.65%. Specialist doctors had the highest overall level of knowledge (74.68%). Conclusion: Improved technical facilities, good initial and in-service training, and interdisciplinary collaboration will help to ensure that imaging tests are properly prescribed, leading to better patient care.

关键词： Theoretical Knowledge medical imaging Northern Region Burkina Faso

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Ideological and Political Exploration of Academic Continuing Education Professional Diploma in medical imaging

IJLAI Transactions on Science and Engineering

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IJLAI Transactions on Science and Engineering 2024年第2期2卷 74-80页

作者： Lin Sun Haitong Wang Kai Wang Lina Zhang Chao Yang The First Affiliated Hospital of Dalian medical University No.150 Lianhe RoadXigang DistrictDalian CityLiaoning Province 116000China Dalian medical University 9 West Section of Lvshun South RoadDalian CityLiaoning Province116044China

In alignment with the 20th National Congress of the Communist Party of China’s commitment to establish a healthier nation,the focus on healthcare strategically prioritizes human *** necessitates redefining medical service ***,the training of medical students and continuing education is *** recent years,the notion of incorporating“ideological and political education within the curriculum”is becoming more explicit,especially within university talent *** paper,exploring the unique attributes of professional medical imaging student training and continuing education,proposes the innovative model of“3+4+2”ideological and political education at the First Affiliated Hospital of Dalian medical *** introduces a new system of“school-family-society”tripartite co-education,a new mechanism of“party committee-functional departments-teaching and research office-teachers”four-level linkage,and a novel approach of“party branch-teaching and research office”dual-wheel drive,integrating value shaping,knowledge imparting,and ability *** goal is to nurture Party talents and educate patriots,thereby enhancing the effectiveness of“comprehensive education”and bolstering the construction of new medical sciences.

关键词： Curriculum ideological and political medical imaging imaging technology Academic continuing education medical education

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Importance of Features Selection,Attributes Selection,Challenges and Future Directions for medical imaging Data:A Review

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Computer Modeling in Engineering & Sciences 2020年第10期125卷 315-344页

作者： Nazish Naheed Muhammad Shaheen Sajid Ali Khan Mohammed Alawairdhi Muhammad Attique Khan Faculty of Engineering&Information Technology Foundation University IslamabadIslamabadPakistan College of Computing and Informatics Saudi Electronic UniversityRayadhSaudi Arabia Department of Computer Science HITEC UniversityTaxilaPakistan

In the area of pattern recognition and machine learning,features play a key role in *** famous applications of features are medical imaging,image classification,and name a few *** the exponential growth of information investments in medical data repositories and health service provision,medical institutions are collecting large volumes of *** data repositories contain details information essential to support medical diagnostic decisions and also improve patient care *** the other hand,this growth also made it difficult to comprehend and utilize data for various *** results of imaging data can become biased because of extraneous features present in larger *** selection gives a chance to decrease the number of components in such large *** selection techniques,ousting the unimportant features and selecting a subset of components that produces prevalent characterization *** correct decision to find a good attribute produces a precise grouping model,which enhances learning pace and forecast *** paper presents a review of feature selection techniques and attributes selection measures for medical *** review is meant to describe feature selection techniques in a medical domainwith their pros and cons and to signify its application in imaging data and data mining *** review reveals the shortcomings of the existing feature and attributes selection techniques to multi-sourced ***,this review provides the importance of feature selection for correct classification of medical *** the end,critical analysis and future directions are provided.

关键词： medical imaging imaging data feature selection data mining attribute selection medical challenges future directions

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Deep Learning for Image Segmentation: A Focus on medical imaging

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计算机、材料和连续体（英文） 2023年第4期75卷 1995-2024页

作者： Ali F.Khalifa Eman Badr Faculty of Computers and Artificial Intelligence Cairo UniversityGiza12613Egypt Zewail City of Science and Technology Giza12578Egypt

Image segmentation is crucial for various research areas. Manycomputer vision applications depend on segmenting images to understandthe scene, such as autonomous driving, surveillance systems, robotics, andmedical imaging. With the recent advances in deep learning (DL) and itsconfounding results in image segmentation, more attention has been drawnto its use in medical image segmentation. This article introduces a surveyof the state-of-the-art deep convolution neural network (CNN) models andmechanisms utilized in image segmentation. First, segmentation models arecategorized based on their model architecture and primary working ***, CNN categories are described, and various models are discussed withineach category. Compared with other existing surveys, several applicationswith multiple architectural adaptations are discussed within each category.A comparative summary is included to give the reader insights into utilizedarchitectures in different applications and datasets. This study focuses onmedical image segmentation applications, where the most widely used architecturesare illustrated, and other promising models are suggested that haveproven their success in different domains. Finally, the present work discussescurrent limitations and solutions along with future trends in the field.

关键词： Deep learning medical imaging convolution neural network image segmentation medical applications survey

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A 12-bit 80 MS/s 2 mW SAR ADC with Deliberated Digital Calibration and Redundancy Schemes for medical imaging

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Journal of Shanghai Jiaotong university(Science) 2022年第2期27卷 250-255页

作者： Han Gang Wu Bin Pu Yilin Intelligent Manufacturing Center Institute of Microelectronics of the Chinese Academy of SciencesBeijing100029China University of Chinese Academy of Sciences Beijing100029China

In this article,we presented a 12-bit 80 MS/s low power successive approximation register(SAR)analog to digital converter(ADC)design.A simplified but effective digital calibration scheme was exploited to make the ADC achieve high resolution without sacrificing more silicon area and power efficiency.A modified redundancy technique was also adopted to guarantee the feasibility of the calibration and meantime ease the burden of the reference buffer *** prototype SAR ADC can work up to a sampling rate of 80 MS/s with the performance of>10.5 bit equivalent number of bits(ENOB),medical imaging.

关键词： successive approximation register(SAR) analog to digital converter(ADC) medical imaging low power calibration redundancy

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AI in spotting high-risk characteristics of medical imaging and molecular pathology

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Precision Clinical Medicine 2021年第4期4卷 271-286页

作者： Chong Zhang Jionghui Gu Yangyang Zhu Zheling Meng Tong Tong Dongyang Li Zhenyu Liu Yang Du Kun Wang Jie Tian Department of Big Data Management and Application School of International Economics and ManagementBeijing Technology and Business UniversityBeijing 100048China CAS Key Laboratory of Molecular imaging Institute of AutomationChinese Academy of SciencesBeijing 100190China School of Artificial Intelligence University of Chinese Academy of SciencesBeijing 100049China Beijing Advanced Innovation Center for Big Data-Based Precision Medicine School of Medicine and EngineeringBeihang UniversityBeijing 100191China

medical imaging provides a comprehensive perspective and rich information for disease *** with artificial intelligence technology,medical imaging can be further mined for detailed pathological *** studies have shown that the macroscopic imaging characteristics of tumors are closely related to microscopic gene,protein and molecular *** order to explore the function of artificial intelligence algorithms in in-depth analysis of medical imaging information,this paper reviews the articles published in recent years from three perspectives:medical imaging analysis method,clinical applications and the development of medical imaging in the direction of pathologicalmolecular *** believe that AI-aidedmedical imaging analysis will be extensively contributing to precise and efficient clinical decision.

关键词： machine learning radiomics medical imaging pathology artificial intelligence

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Study design of deep learning based automatic detection of cerebrovascular diseases on medical imaging: a position paper from Chinese Association of Radiologists

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Intelligent Medicine 2022年第4期2卷 221-229页

作者： Longjiang Zhang Zhao Shi Min Chen Yingmin Chen Jingliang Cheng Li Fan Nan Hong Wenxiao Jia Guihua Jiang Shenghong Ju Xiaogang Li Xiuli Li Changhong Liang Weihua Liao Shiyuan Liu Zaiming Lu Lin Ma Ke Ren Pengfei Rong Bin Song Gang Sun Rongpin Wang Zhibo Wen Haibo Xu Kai Xu Fuhua Yan Yizhou Yu Yunfei Zha Fandong Zhang Minwen Zheng Zhen Zhou Wenzhen Zhu Guangming Lu Zhengyu Jin on behalf of Chinese Association of Radiologists Department of Radiology Affiliated Jinling HospitalMedical School of Nanjing UniversityNanjingJiangsu 210002China Department of Radiology Beijing HospitalNational Center of GerontologyBeijing 100005China Department of Radiology Hebei General HospitalShijiazhuangHebei 050199China Department of Magnetic Resonance imaging The First Affiliated Hospital of Zhengzhou UniversityZhengzhouHenan 450052China Department of medical imaging and Nuclear Medicine Changzheng Hospital of Naval Medical UniversityShanghai 200072China Department of Radiology Peking University People’s HospitalBeijing 100044China imaging Center First AffiliatedHospital of Xinjiang Medical UniversityUrumqiXinjiang Uygur Autonomous Region 830054China Department of medical imaging Guangdong Second Provincial General HospitalGuangzhouGuangdong 510050China Department of Radiology Zhongda HospitalSchool of MedicineSoutheast UniversityNanjingJiangsu 211189China Department of Radiology General Hospital of Northern Theater CommandShenyangLiaoning 110011China DeepWise AI lab.Beijing 100089 China Department of Radiology Guangdong Provincial People’s HospitalGuangdong Academy of Medical SciencesGuangzhouGuangdong 519041China Department of Radiology Xiangya HospitalCentral South UniversityChangshaHunan 410008China Department of Radiology Shengjing Hospital of China Medical UniversityShenyangLiaoning 110001China Department of Radiology Chinese PLA(People’s Liberation Army)General HospitalBeijing 100853China Department of Radiology Xiang’an Hospital of Xiamen UniversitySchool of MedicineXiamen UniversityXiamenFujian 361005China Department of Radiology Third Xiangya HospitalCentral South UniversityChangshaHunan 410013China Department of Radiology Functional and Molecular Imaging Key Laboratory of Sichuan ProvinceWest China HospitalSichuan UniversityChengduSichuan 610044China Department of Nuclear Medicine 960 Hospital of PLAJi’nanShandong 250012China Department of Radiology Guizhou Provincial People’s Hosp

In recent years,with the development of artificial intelligence,especially deep learning technology,researches on automatic detection of cerebrovascular diseases on medical images have made tremendous progress and these models are gradually entering into clinical ***,because of the complexity and flexibility of the deep learning algorithms,these researches have great variability on model building,validation process,performance description and results *** lack of a reliable,consistent,standardized design protocol has,to a certain extent,affected the progress of clinical translation and technology development of computer aided detection *** reviewing a large number of literatures and extensive discussion with domestic experts,this position paper put forward recommendations of standardized design on the key steps of deep learning-based automatic image detection models for cerebrovascular *** further research and application expansion,this position paper would continue to be updated and gradually extended to evaluate the generalizability and clinical application efficacy of such tools.

关键词： Cerebrovascular diseases Deep learning Study design medical imaging

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Advances of Artificial Intelligence Application in medical imaging of Ovarian Cancers

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Chinese medical Sciences Journal 2021年第3期36卷 196-203页

作者： Chen Xu Huo Xiaofei Wu Zhe Lu Jingjing Department of Radiology Beijing United Family HospitalBeijing 100015China Department of Radiology Fushun Central HospitalLiaoning 113006China

Ovarian cancer is one of the three most common gynecological cancers in the world,and is regarded as a priority in terms of women’s *** the past few years,many researchers have attempted to develop and apply artificial intelligence(AI)techniques to multiple clinical scenarios of ovarian cancer,especially in the field of medical ***-assisted imaging studies have involved computer tomography(CT),ultrasonography(US),and magnetic resonance imaging(MRI).In this review,we perform a literature search on the published studies that using AI techniques in the medical care of ovarian cancer,and bring up the advances in terms of four clinical aspects,including medical diagnosis,pathological classification,targeted biopsy guidance,and prognosis ***,current status and existing issues of the researches on AI application in ovarian cancer are discussed.

关键词： artificial intelligence machine learning ovarian cancer radiomics algorithm medical imaging

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Reliability of medical imaging in the Pre-Therapeutic Assessment of Acute Intestinal Obstruction at the Centre Hospitalier Universitaire Du Point “G”.

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Open Journal of medical imaging 2022年第3期12卷 147-156页

作者： Abdoulaye Koné Mahamadou Daou Youssouf Koné Moussa Traoré Moussa Konaté Ouncoumba Diarra Ibrahima Coulibaly Youssouf Diawara Amadou Doumbia Cheick Oumar Touré Kassim Sidibé Mody A. Camara Oumar Aba Ata Mahamadou Diallo Adama Diaman Keita Salia Coulibaly Zimogo Zié Sanogo Siaka Sidibe Faculty of Medicine and Odontostomatology Bamako Mali medical imaging Department of the University Hospital of Point G Bamako Mali Radiology Department of the Jacques Boutard Hospital Saint-Yrieix-la-Perche France medical imaging Department of GABRIEL TOURE Hospital Bamako Mali Radiology Department of CSREF Commune III Bamako Mali medical imaging Service Health Center of Ref Commune VI Bamako Mali medical imaging Service Health Center of Ref Commune IV Bamako Mali DCSSA Kati Mali medical imaging Department of Mali Hospital Bamako Mali medical imaging Department of Kati Hospital Bamako Mali Department of General Surgery of Point G University Hospital Bamako Mali

Introduction: Acute intestinal obstruction is a serious pathology, a surgical emergency for which medical imaging plays an important role in the management. We initiated this work in order to study the contribution of imaging in the diagnosis of acute intestinal obstruction at the Point-G University Hospital. Patients and Methods: This was a prospective, descriptive and analytical study of 96 patients collected at the radiology and medical imaging department of CHU Point-G from January 2018 to January 2019. Results: The age of our patients varied from 11 to 86 years, with an average of 36 years old. There was a male predominance of 64.6% against 35.4% for women, i.e., a sex ratio of 1.82. Previous surgery was found in 61.5% of our patients. The pain was present in all patients. An unprepared abdominal X-ray was performed in 89.6% of patients. Hydroaerobic levels were found in 96.5% of patients. Abdominopelvic CT scans were performed on 12 patients, all of whom were diagnosed with occlusion. These positive diagnostic findings were consistent with intraoperative findings in 92% of cases. The causes were dominated by bridges in 46 patients and tumors in 9 patients. Signs of severity on CT were dominated by signs of distress of the upstream bile ducts in 8.3%. Exactly 8% of our patients spontaneously resumed transit, 91% received surgical treatment and 1% died before surgery. The outcome was favorable in 80 patients (83.3%) and poor with death in 16 patients (16.7%). Conclusion: Acute intestinal obstruction remains a serious pathology for which the X-ray of the PSA is often the only radiological examination performed in an emergency. However, abdominopelvic CT seems to us to be widely indicated thanks to its contribution both to the positive diagnosis and to the diagnosis of severity and etiology. However, this imaging technique is widely underused in our practice because of its high cost and lack of availability.

关键词： medical imaging Acute Intestinal Obstruction Abdominal CT Reliability

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Exploration and Practice of Postgraduate Training Mode Based on medical imaging Information Security

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计算机教育 2023年第12期 71-77页

作者： Yi Ding Jiaqi Zhang Zhen Qin Yang Zhao Mingsheng Cao Network and Data Security Key Laboratory of Sichuan Province School of Information and Software EngineeringUniversity of Electronic Science and Technology of ChinaChengdu610051China

In the process of continuous maturity and development of medical imaging diagnosis,it is common to transmit images through public *** to ensure the security of transmission,cultivate talents who combine medical imaging and information security,and explore and cultivate new discipline growth points are difficult problems and challenges for schools and *** order to cope with industrial changes,a new round of scientific and technological revolution,and the challenges of the further development of artificial intelligence in medicine,this article will analyze the existing problems in the training of postgraduates in medical imaging information security by combining the actual conditions and characteristics of universities,and put forward countermeasures and suggestions to promote the progress of technology in universities.

关键词： medical imaging Information security Postgraduate training Countermeasures and suggestions

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