Image quality fig. evaluator used in radiography based on contrast-detail phantom
In radiology, it is significantly important to produce adequate diagnostic information for affecting the patient with the lowest amount of dose. A contrast-detail phantom is generally used to study the quality of the image and the amount of radiation dose for a digital X-ray imaging system. For eval...
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creator | Ching-Lin Wang Chuin-Mu Wang Yung-Kuan Chan Shihrong Wang Ming-Ru Liou |
description | In radiology, it is significantly important to produce adequate diagnostic information for affecting the patient with the lowest amount of dose. A contrast-detail phantom is generally used to study the quality of the image and the amount of radiation dose for a digital X-ray imaging system. For evaluating the quality of a phantom image, the radiologists are required to indicate the location of the holes in each square in the phantom image. Then, the image quality figure (IQF) of the image can be calculated. However, evaluation by the human eye is subjective and time-consuming. In this paper, an image processing based IQF evaluation method is proposed to automatically measure the quality of a phantom image. The experimental results tell that the proposed method is more sensitive in estimating the IQF of a phantom image than the observation of radiologists. |
doi_str_mv | 10.1109/ICCSN.2011.6014757 |
format | Conference Proceeding |
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The experimental results tell that the proposed method is more sensitive in estimating the IQF of a phantom image than the observation of radiologists.</description><subject>CD curve</subject><subject>contrast-detail phantom</subject><subject>image quality figure</subject><subject>Pattern recognition</subject><subject>Phantoms</subject><isbn>9781612844855</isbn><isbn>1612844855</isbn><isbn>1612844863</isbn><isbn>1612844847</isbn><isbn>9781612844848</isbn><isbn>9781612844862</isbn><fulltext>true</fulltext><rsrctype>conference_proceeding</rsrctype><creationdate>2011</creationdate><recordtype>conference_proceeding</recordtype><sourceid>6IE</sourceid><sourceid>RIE</sourceid><recordid>eNo1kNtKxDAYhCMiqGtfQG_yAq3_36RpcinFQ2FRxL1f0ibpRnqyTYW-vSuuczPMdzEwQ8gtQoII6r4sio_XJAXERADyPMvPyDUKTCXnUrBzEqlc_ucsuyTRPH_CUUJIBfkVeS873Vj6tejWh5U63yTUfut20WGY6DJbQ31PJ2380Ex6PKy00r9w6Gk99GHSc4iNDdq3dDzoPgzdDblwup1tdPIN2T097oqXePv2XBYP29grCDFjuXNgHGCtTColMxVaJUAqo3iOruJWmOq4y7ra1EamyKHiGQKoumKpYRty91frrbX7cfKdntb96QT2A-lXUQI</recordid><startdate>201105</startdate><enddate>201105</enddate><creator>Ching-Lin Wang</creator><creator>Chuin-Mu Wang</creator><creator>Yung-Kuan Chan</creator><creator>Shihrong Wang</creator><creator>Ming-Ru Liou</creator><general>IEEE</general><scope>6IE</scope><scope>6IL</scope><scope>CBEJK</scope><scope>RIE</scope><scope>RIL</scope></search><sort><creationdate>201105</creationdate><title>Image quality fig. evaluator used in radiography based on contrast-detail phantom</title><author>Ching-Lin Wang ; Chuin-Mu Wang ; Yung-Kuan Chan ; Shihrong Wang ; Ming-Ru Liou</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-i90t-337ff0df01c9d2883db1e96089d9471fb4e6db011efcdcd82140b451009cb32d3</frbrgroupid><rsrctype>conference_proceedings</rsrctype><prefilter>conference_proceedings</prefilter><language>eng</language><creationdate>2011</creationdate><topic>CD curve</topic><topic>contrast-detail phantom</topic><topic>image quality figure</topic><topic>Pattern recognition</topic><topic>Phantoms</topic><toplevel>online_resources</toplevel><creatorcontrib>Ching-Lin Wang</creatorcontrib><creatorcontrib>Chuin-Mu Wang</creatorcontrib><creatorcontrib>Yung-Kuan Chan</creatorcontrib><creatorcontrib>Shihrong Wang</creatorcontrib><creatorcontrib>Ming-Ru Liou</creatorcontrib><collection>IEEE Electronic Library (IEL) Conference Proceedings</collection><collection>IEEE Proceedings Order Plan All Online (POP All Online) 1998-present by volume</collection><collection>IEEE Xplore All Conference Proceedings</collection><collection>IEEE/IET Electronic Library (IEL)</collection><collection>IEEE Proceedings Order Plans (POP All) 1998-Present</collection></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext_linktorsrc</fulltext></delivery><addata><au>Ching-Lin Wang</au><au>Chuin-Mu Wang</au><au>Yung-Kuan Chan</au><au>Shihrong Wang</au><au>Ming-Ru Liou</au><format>book</format><genre>proceeding</genre><ristype>CONF</ristype><atitle>Image quality fig. evaluator used in radiography based on contrast-detail phantom</atitle><btitle>2011 IEEE 3rd International Conference on Communication Software and Networks</btitle><stitle>ICCSN</stitle><date>2011-05</date><risdate>2011</risdate><spage>431</spage><epage>435</epage><pages>431-435</pages><isbn>9781612844855</isbn><isbn>1612844855</isbn><eisbn>1612844863</eisbn><eisbn>1612844847</eisbn><eisbn>9781612844848</eisbn><eisbn>9781612844862</eisbn><abstract>In radiology, it is significantly important to produce adequate diagnostic information for affecting the patient with the lowest amount of dose. A contrast-detail phantom is generally used to study the quality of the image and the amount of radiation dose for a digital X-ray imaging system. For evaluating the quality of a phantom image, the radiologists are required to indicate the location of the holes in each square in the phantom image. Then, the image quality figure (IQF) of the image can be calculated. However, evaluation by the human eye is subjective and time-consuming. In this paper, an image processing based IQF evaluation method is proposed to automatically measure the quality of a phantom image. The experimental results tell that the proposed method is more sensitive in estimating the IQF of a phantom image than the observation of radiologists.</abstract><pub>IEEE</pub><doi>10.1109/ICCSN.2011.6014757</doi><tpages>5</tpages></addata></record> |
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subjects | CD curve contrast-detail phantom image quality figure Pattern recognition Phantoms |
title | Image quality fig. evaluator used in radiography based on contrast-detail phantom |
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