dicom reader based tracking and monitoring software (Radimetrics Inc)
90
Structured Review
Radimetrics Inc
dicom reader based tracking and monitoring software
Dicom Reader Based Tracking And Monitoring Software, supplied by Radimetrics Inc, used in various techniques. Bioz Stars score: 90/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
https://www.bioz.com/product/dicom+reader+software/dose+tracking+software/pm28027768-56-37-39
Average 90 stars, based on 1 article reviews
Dicom Reader Based Tracking And Monitoring Software, supplied by Radimetrics Inc, used in various techniques. Bioz Stars score: 90/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
https://www.bioz.com/product/dicom+reader+software/dose+tracking+software/pm28027768-56-37-39
Average 90 stars, based on 1 article reviews
dicom reader based tracking and monitoring software - by Bioz Stars,
2026-10
90/100 stars
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other:Article Title: Effective Dose Estimation in Computed Tomography by Machine Learning Article Snippet: We collected 69,037 CT acquisitions of two different devices of the same vendor from January 2019 to February 2021 and sent them to the commercial Article Title: Two-year experience of radiation dose watch for pediatric general fluoroscopic examinations. Article Snippet: Background The radiation dose of pediatric general fluoroscopy exams has historically been a topic of concern, with ongoing efforts and significant progress made.. Objective The purpose of this study is to evaluate dose performance with a dose monitor program for pediatric general fluoroscopy.. Materials and methods Pediatric general fluoroscopy exams performed between April 1, 2020, and Dec. 31, 2022 were collected and monitored. Article Title: Effective Dose Estimation in Computed Tomography by Machine Learning. Article Snippet: The primary aim of our work is to explore the power of machine learning in effective dose estimation, starting from values obtained using a commercial Article Title: Effectiveness of body size stratification for patient exposure optimization in Computed Tomography. Article Snippet: Purpose: To establish size-dependent DRL and to estimate the effectiveness of the size-dependent DRLs over sizeindependent DRLs for a CT exposure optimization process.. Methods: The study included 16,933 adult CT body examinations of the most common CT protocols.. Acquisitions were included following an image quality assessment. Article Title: Pediatric contrast-enhanced chest CT on a photon-counting detector CT: radiation dose and image quality compared to energy-integrated detector CT. Article Snippet: Background Photon counting detector (PCD) CT benefits from reduced noise compared with conventional energy-integrating detector (EID) CT, which should translate to improved image quality and reduced radiation exposure for pediatric patients undergoing chest CT with IV contrast.. Objective To determine the differences in radiation exposure and image quality of PCD CT and EID CT in pediatric chest CT with intravenous (IV) contrast.. Materials and methods In this institutional review board–approved retrospective observational study, 20 scan pairs (20 PCD CT; 20 EID CT) for children who underwent chest CT with IV contrast on both a PCD CT (Siemens NAEOTOM Alpha) and an EID CT (Siemens SOMATOM Definition Edge or Force) within 12 months were reviewed independently by three pediatric radiologists for three subjective quality features on 5-point Likert scales: overall quality, small structure delineation, and motion artifact. Article Title: Effective Dose Estimation in Computed Tomography by Machine Learning Article Snippet: The primary aim of our work is to explore the power of machine learning in effective dose estimation, starting from values obtained using a commercial Article Title: Effective Dose Estimation in Computed Tomography by Machine Learning. Article Snippet: Internal Dataset and Variable Description We collected 69,037 CT acquisitions of two different devices of the same vendor from January 2019 to February 2021 and sent them to the commercial Software:Article Title: Machine learning-based estimation of patient body weight from radiation dose metrics in computed tomography. Article Snippet: .. The dose metrics and descriptive data were either obtained from DICOM metadata or automatically calculated from the CT images using |