Nikolay Aleexevich Korenevskiy, Vladimir Anatolievich Belozerov, Riad Taha Al-Kasasbeh, Moaath Musa Al-Smadi, Altyn A Aikeyeva, Mohammad Al-Jundi, Sofia N Rodionova, Sergey Filist, Mahdi Salman Alshamasin, Osama M Al-Habahbeh, Ilyash Maksim
{"title":"基于模糊数学模型的病灶轮廓性质分析的内窥镜超声波检查对胰腺癌和慢性胰腺炎的鉴别诊断。","authors":"Nikolay Aleexevich Korenevskiy, Vladimir Anatolievich Belozerov, Riad Taha Al-Kasasbeh, Moaath Musa Al-Smadi, Altyn A Aikeyeva, Mohammad Al-Jundi, Sofia N Rodionova, Sergey Filist, Mahdi Salman Alshamasin, Osama M Al-Habahbeh, Ilyash Maksim","doi":"10.1615/CritRevBiomedEng.2023048046","DOIUrl":null,"url":null,"abstract":"<p><p>One of the key echographic signs of focal pathology of the pancreas is the presence of formation contours and their nature. Endoscopic ultrasonography has a unique ability to visualize the echographic texture of the pancreatic parenchyma, and also allows you to assess in detail the boundaries and nature of the contours of the tumor formations of the organ due to the proximity of the ultrasound sensor. However, the differential diagnosis of focal pancreatic lesions remains a difficult clinical task due to the similarity of their echosemiotics. One of the ways to objectify and improve the accuracy of ultrasound data is the use of artificial intelligence methods for interpreting images. Improving the quality of differential diagnosis of focal pathology of the pancreas according to endoscopic ultrasonography based on the analysis of the nature of the contours of focal formations using fuzzy mathematical models.</p>","PeriodicalId":53679,"journal":{"name":"Critical Reviews in Biomedical Engineering","volume":"51 3","pages":"59-76"},"PeriodicalIF":0.0000,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Differential Diagnosis of Pancreatic Cancer and Chronic Pancreatitis According to Endoscopic Ultrasonography Based on the Analysis of the Nature of the Contours of Focal Formations Based on Fuzzy Mathematical Models.\",\"authors\":\"Nikolay Aleexevich Korenevskiy, Vladimir Anatolievich Belozerov, Riad Taha Al-Kasasbeh, Moaath Musa Al-Smadi, Altyn A Aikeyeva, Mohammad Al-Jundi, Sofia N Rodionova, Sergey Filist, Mahdi Salman Alshamasin, Osama M Al-Habahbeh, Ilyash Maksim\",\"doi\":\"10.1615/CritRevBiomedEng.2023048046\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><p>One of the key echographic signs of focal pathology of the pancreas is the presence of formation contours and their nature. Endoscopic ultrasonography has a unique ability to visualize the echographic texture of the pancreatic parenchyma, and also allows you to assess in detail the boundaries and nature of the contours of the tumor formations of the organ due to the proximity of the ultrasound sensor. However, the differential diagnosis of focal pancreatic lesions remains a difficult clinical task due to the similarity of their echosemiotics. One of the ways to objectify and improve the accuracy of ultrasound data is the use of artificial intelligence methods for interpreting images. Improving the quality of differential diagnosis of focal pathology of the pancreas according to endoscopic ultrasonography based on the analysis of the nature of the contours of focal formations using fuzzy mathematical models.</p>\",\"PeriodicalId\":53679,\"journal\":{\"name\":\"Critical Reviews in Biomedical Engineering\",\"volume\":\"51 3\",\"pages\":\"59-76\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2023-01-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Critical Reviews in Biomedical Engineering\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1615/CritRevBiomedEng.2023048046\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q3\",\"JCRName\":\"Engineering\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Critical Reviews in Biomedical Engineering","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1615/CritRevBiomedEng.2023048046","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"Engineering","Score":null,"Total":0}
Differential Diagnosis of Pancreatic Cancer and Chronic Pancreatitis According to Endoscopic Ultrasonography Based on the Analysis of the Nature of the Contours of Focal Formations Based on Fuzzy Mathematical Models.
One of the key echographic signs of focal pathology of the pancreas is the presence of formation contours and their nature. Endoscopic ultrasonography has a unique ability to visualize the echographic texture of the pancreatic parenchyma, and also allows you to assess in detail the boundaries and nature of the contours of the tumor formations of the organ due to the proximity of the ultrasound sensor. However, the differential diagnosis of focal pancreatic lesions remains a difficult clinical task due to the similarity of their echosemiotics. One of the ways to objectify and improve the accuracy of ultrasound data is the use of artificial intelligence methods for interpreting images. Improving the quality of differential diagnosis of focal pathology of the pancreas according to endoscopic ultrasonography based on the analysis of the nature of the contours of focal formations using fuzzy mathematical models.
期刊介绍:
Biomedical engineering has been characterized as the application of concepts drawn from engineering, computing, communications, mathematics, and the physical sciences to scientific and applied problems in the field of medicine and biology. Concepts and methodologies in biomedical engineering extend throughout the medical and biological sciences. This journal attempts to critically review a wide range of research and applied activities in the field. More often than not, topics chosen for inclusion are concerned with research and practice issues of current interest. Experts writing each review bring together current knowledge and historical information that has led to the current state-of-the-art.