{"title":"Radiomics: A Powerful Tool","authors":"Shahid Kamal","doi":"10.21089/njhs.91.0001","DOIUrl":null,"url":null,"abstract":"The Artificial Intelligence based technique of radiomics is an evolving modality that employs data characterization algorithms to extract a variety of useful features from medical images [1].Tumoral patterns are revealed that cannot be appreciated by the naked eye [2]. This can aid in assessing prognosis and gauging the response of tumor cells to therapy [3]. Various imaging modalities like CT, PET MR provide essential raw data. Extraction tools then use the raw data volumes to analyze pixel/voxel characteristics. Using these images, “volumes of interest” can be generated since such segmentation entails handling and processing of large image data; automatic and semiautomatic segmentation algorithms are employed enabling automation [4]. However, thorough testing and quality assurance are vital to ensure that the algorithm used is not only accurate, consistent, and reproducible but also time-efficient [5].","PeriodicalId":441304,"journal":{"name":"National Journal of Health Sciences","volume":"23 3","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2024-03-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"National Journal of Health Sciences","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.21089/njhs.91.0001","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
The Artificial Intelligence based technique of radiomics is an evolving modality that employs data characterization algorithms to extract a variety of useful features from medical images [1].Tumoral patterns are revealed that cannot be appreciated by the naked eye [2]. This can aid in assessing prognosis and gauging the response of tumor cells to therapy [3]. Various imaging modalities like CT, PET MR provide essential raw data. Extraction tools then use the raw data volumes to analyze pixel/voxel characteristics. Using these images, “volumes of interest” can be generated since such segmentation entails handling and processing of large image data; automatic and semiautomatic segmentation algorithms are employed enabling automation [4]. However, thorough testing and quality assurance are vital to ensure that the algorithm used is not only accurate, consistent, and reproducible but also time-efficient [5].