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A SIMPLIFIED METHOD for the WATER-EQUIVALENT DIAMETER CALCULATION to ESTIMATE PATIENT DOSE in CT EXAMINATIONS
Anam C.a, Arif I.b, Haryanto F.b, Widita R.b, Lestari F.P.b, Adi K.a, Dougherty G.c
a Department of Physics, Faculty of Mathematics and Natural Sciences, Diponegoro University, Semarang, Central Java, Indonesia
b Department of Physics, Faculty of Mathematics and Natural Sciences, Bandung Institute of Technology, Bandung, West Java, Indonesia
c Department of Applied Physics and Medical Imaging, California State University Channel Islands, Camarillo, United States
[vc_row][vc_column][vc_row_inner][vc_column_inner][vc_separator css=”.vc_custom_1624529070653{padding-top: 30px !important;padding-bottom: 30px !important;}”][/vc_column_inner][/vc_row_inner][vc_row_inner layout=”boxed”][vc_column_inner width=”3/4″ css=”.vc_custom_1624695412187{border-right-width: 1px !important;border-right-color: #dddddd !important;border-right-style: solid !important;border-radius: 1px !important;}”][vc_empty_space][megatron_heading title=”Abstract” size=”size-sm” text_align=”text-left”][vc_column_text]© 2018 The Author(s) 2019. Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com.We proposed and evaluated a water-equivalent diameter calculation without using a region of interest (ROI), (Dw,t) and compared it with the results of using a ROI fitted to the patient border (Dw,f). Evaluations were carried out on thoracic and head CT images. We found that the difference between Dw,t and Dw,f was within 5% for all images in the head region, and most images were within 5% (27 of the 30 patients, 90%) in the thoracic region. We also proposed a method to automatically detect and eliminate the patient table (or head support) from images and evaluated the water-equivalent diameter values after the table had been removed (Dw,nt). This method was able to recognize and remove the patient table from all images used. By removing the table, the water-equivalent diameter (Dw,nt) became more accurate and the difference from Dw,f was within 5% for all images (head and thoracic images).[/vc_column_text][vc_empty_space][vc_separator css=”.vc_custom_1624528584150{padding-top: 25px !important;padding-bottom: 25px !important;}”][vc_empty_space][megatron_heading title=”Author keywords” size=”size-sm” text_align=”text-left”][vc_column_text]Head,Humans,Image Processing, Computer-Assisted,Models, Statistical,Radiation Dosage,Radiography, Thoracic,Software,Thorax,Tomography, X-Ray Computed,Water[/vc_column_text][vc_empty_space][vc_separator css=”.vc_custom_1624528584150{padding-top: 25px !important;padding-bottom: 25px !important;}”][vc_empty_space][megatron_heading title=”Indexed keywords” size=”size-sm” text_align=”text-left”][vc_column_text][/vc_column_text][vc_empty_space][vc_separator css=”.vc_custom_1624528584150{padding-top: 25px !important;padding-bottom: 25px !important;}”][vc_empty_space][megatron_heading title=”Funding details” size=”size-sm” text_align=”text-left”][vc_column_text]This work was supported by Penelitian Dasar Unggulan Perguruan Tinggi (PDUPT), Ministry of Research Technology and Higher Education of the Republic of Indonesia, contract number 532z/I1. C01/PL/2018.[/vc_column_text][vc_empty_space][vc_separator css=”.vc_custom_1624528584150{padding-top: 25px !important;padding-bottom: 25px !important;}”][vc_empty_space][megatron_heading title=”DOI” size=”size-sm” text_align=”text-left”][vc_column_text]https://doi.org/10.1093/rpd/ncy214[/vc_column_text][/vc_column_inner][vc_column_inner width=”1/4″][vc_column_text]Widget Plumx[/vc_column_text][/vc_column_inner][/vc_row_inner][/vc_column][/vc_row][vc_row][vc_column][vc_separator css=”.vc_custom_1624528584150{padding-top: 25px !important;padding-bottom: 25px !important;}”][/vc_column][/vc_row]