2-s2.0-85067057346

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[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 University of Dicle.Development of negative panoramic-based radiograph system into digital imaging often getting the unexpected quality. There are many methods of the quality improvement process (enhancement) thus needs to be assessed. The objective of this research was to obtain the best quality improvement method based on an objective radiograph quality analysis. This research was a comparative descriptive research with as much as 30 samples of analogue panoramic radiograph taken with the purposive sampling method from data of Dental Hospital of Faculty of Dentistry Universitas Padjadjaran (RSGM). The next stage was the digitalization process using a scanner with mode settings as follows: transmission; intensity resolution of 8-bit and spatial resolution of 800 dpi; Intel® Pentium Dual Core 2 GHz PC Processor; 4 GB RAM; Scanner; So Epson® Perfection V700; Software; LED LCD Screen. The program file setting was set in the *.tif format. Enhancement of the radiograph quality was performed by using the software, each was using the Contrast Stretching (SC) method, Adaptive Histogram Equalization (AHE), Histogram Equalization (HE), and Contrast Limited Adaptive Histogram Equalization (CLAHE). The objective assessment was using the variables as follows: mean; standard deviation; peak signal to noise ratio (PSNR); root mean square error (RMSE); average difference (AD); normalized absolute error (NAE); and structural content (SC). From the measurement results obtained the values of Mean, SD, PSNR, RMSE, AD, NAE, and SC with the CLAHE method were 106.17; 47.27; 17.11; 35.56; 9.29; 0.1679; and 1.2252 consecutively. The CLAHE method was the best quality improvement method because the ability to overcome the limitations of the AHE method by limiting the increase in brightness and contrast thus maintained the object details.[/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][/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]Enhancement,Objective quality,Panoramic digitalization[/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][/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][/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]