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10.1120/jacmp.v15i2.4628 http://scihub22266oqcxt.onion/10.1120/jacmp.v15i2.4628 C5875472!5875472!24710451     free     free     free Deprecated: Implicit conversion from float 217.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 217.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 217.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 217.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 217.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534       J+Appl+Clin+Med+Phys 2014 ; 15 (2): 252-61 Nephropedia Template TP {{tp|p=24710451|t=2014. Improving image accuracy of region?of?interest in cone?beam CT using prior image |pdf=|usr=}}{{24710451}} gab.com Text Improving image accuracy of region of interest in cone beam CT using prior image JO: J Appl Clin Med Phys http://www.kidney.de/pget.php?&tw=1&pmid=24710451 #FOAvip In diagnostic follow?ups of diseases, such as calcium scoring in kidney or fat content assessment in liver using repeated CT scans, quantitatively accurate and consistent CT values are desirable at a low cost of radiation dose to the patient. Region?of?interest (ROI) imaging technique is considered a reasonable dose reduction method in CT scans for its shielding geometry outside the ROI. However, image artifacts in the reconstructed images caused by missing data outside the ROI may degrade overall image quality and, more importantly, can decrease image accuracy of the ROI substantially. In this study, we propose a method to increase image accuracy of the ROI and to reduce imaging radiation dose via utilizing the outside ROI data from prior scans in the repeated CT applications. We performed both numerical and experimental studies to validate our proposed method. In a numerical study, we used an XCAT phantom with its liver and stomach changing their sizes from one scan to another. Image accuracy of the liver has been improved as the error decreased from 44.4 HU to ?0.1 HU by the proposed method, compared to an existing method of data extrapolation to compensate for the missing data outside the ROI. Repeated cone?beam CT (CBCT) images of a patient who went through daily CBCT scans for radiation therapy were also used to demonstrate the performance of the proposed method experimentally. The results showed improved image accuracy inside the ROI. The magnitude of error decreased from ?73.2 HU to 18 HU, and effectively reduced image artifacts throughout the entire image.PACS number: 87.57. Q? Twit Text FOAVip Improving image accuracy of region of interest in cone beam CT using prior image ????J Appl Clin Med Phys http://www.kidney.de/pget.php?&tw=1&pmid=24710451 #FOAvip Twit Text # Free Paper on # # # # # LINK http://www.kidney.de/pget.php?&tw=1&pmid=24710451 #FOAvip English Wikipedia <ref>{{Cite pmid|24710451}}</ref> Improving image accuracy of region?of?interest in cone?beam CT using prior image #MMPMID24710451 Lee J; Kim JS; Cho S J Appl Clin Med Phys 2014[Mar]; 15 (2): 252-61 PMID24710451show ga In diagnostic follow?ups of diseases, such as calcium scoring in kidney or fat content assessment in liver using repeated CT scans, quantitatively accurate and consistent CT values are desirable at a low cost of radiation dose to the patient. Region?of?interest (ROI) imaging technique is considered a reasonable dose reduction method in CT scans for its shielding geometry outside the ROI. However, image artifacts in the reconstructed images caused by missing data outside the ROI may degrade overall image quality and, more importantly, can decrease image accuracy of the ROI substantially. In this study, we propose a method to increase image accuracy of the ROI and to reduce imaging radiation dose via utilizing the outside ROI data from prior scans in the repeated CT applications. We performed both numerical and experimental studies to validate our proposed method. In a numerical study, we used an XCAT phantom with its liver and stomach changing their sizes from one scan to another. Image accuracy of the liver has been improved as the error decreased from 44.4 HU to ?0.1 HU by the proposed method, compared to an existing method of data extrapolation to compensate for the missing data outside the ROI. Repeated cone?beam CT (CBCT) images of a patient who went through daily CBCT scans for radiation therapy were also used to demonstrate the performance of the proposed method experimentally. The results showed improved image accuracy inside the ROI. The magnitude of error decreased from ?73.2 HU to 18 HU, and effectively reduced image artifacts throughout the entire image.PACS number: 87.57. Q? äImproving image accuracy of region?of?interest in cone?beam CT using p(epmc).pdf DeepDyve Pubget Overpricing