Automatic Registration of MR and SPECT Images for Treatment Planning in Prostate Cancer

To aid in surgical and radiation therapy planning for prostate adenocarcinoma, a general-purpose automatic registration method that is based on mutual information was used to align magnetic resonance (MR) images and single photon emission computed tomographic (SPECT) images of the pelvis and prostat...

Ausführliche Beschreibung

Gespeichert in:
Bibliographische Detailangaben
Veröffentlicht in:Academic radiology 2003-06, Vol.10 (6), p.673-684
Hauptverfasser: Lee, Zhenghong, Nagano, Kenichi K, Duerk, Jeffrey L, Sodee, D.Bruce, Wilson, David L
Format: Artikel
Sprache:eng
Schlagworte:
Online-Zugang:Volltext
Tags: Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
container_end_page 684
container_issue 6
container_start_page 673
container_title Academic radiology
container_volume 10
creator Lee, Zhenghong
Nagano, Kenichi K
Duerk, Jeffrey L
Sodee, D.Bruce
Wilson, David L
description To aid in surgical and radiation therapy planning for prostate adenocarcinoma, a general-purpose automatic registration method that is based on mutual information was used to align magnetic resonance (MR) images and single photon emission computed tomographic (SPECT) images of the pelvis and prostate. The authors assessed the effects of various factors on alignment between pairs of MR and SPECT images, including the use of particular pulse sequences in MR imaging, image voxel intensity scaling, the use of different regions on the MR-SPECT histogram, spatial masking of nonoverlapping visual data between images, and multiresolution optimization. A mutual information algorithm was used as the cost function for automatic registration. Automatic registration was deemed acceptable when it resulted in a transformation with less than 2 voxel units (6 mm) difference in translation and less than 2° difference in rotation from that obtained with manual registration performed independently by nuclear medicine radiologists. Paired sets of MR and SPECT image volumes from four of five patients were successfully registered. For successful registration, MR images must be optimal and registration must be performed at full spatial resolution and at the full intensity range. Masking, cropping, and the normalization of mutual information, used to register partially overlapping MR-SPECT volumes, were not successful. Multiresolution optimization had little effect on the accuracy and speed of the registration. Automatic registration between MR and SPECT images of the pelvis can be achieved when data acquisition and image processing are performed properly. It should prove useful for prostate cancer diagnosis, staging, and treatment planning.
doi_str_mv 10.1016/S1076-6332(03)80088-0
format Article
fullrecord <record><control><sourceid>proquest_cross</sourceid><recordid>TN_cdi_proquest_miscellaneous_73438409</recordid><sourceformat>XML</sourceformat><sourcesystem>PC</sourcesystem><els_id>S1076633203800880</els_id><sourcerecordid>73438409</sourcerecordid><originalsourceid>FETCH-LOGICAL-c392t-d3a9a66ecd76bb23abd7d949fe120dbce3bd8af6665ba21d51b8e94002eb5d203</originalsourceid><addsrcrecordid>eNqFkEtPGzEURq2qVRNof0KRVxUshl7bMx7PqooiCkhUjUgQS8uPO5FRZobaDlL_fSckiGVW91uc-zqEfGNwyYDJH0sGtSykEPwcxIUCUKqAD2TKVK2KEkr5ccxvyIScpPQEwCqpxGcyYVxBU3IxJY-zbR46k4Oj97gOKccxDz0dWvr7npre0-Xiar6it51ZY6LtEOkqoskd9pkuNqbvQ7-moaeLOKRsMtK56R3GL-RTazYJvx7qKXn4dbWa3xR3f65v57O7womG58IL0xgp0flaWsuFsb72Tdm0yDh461BYr0wrpays4cxXzCpsSgCOtvIcxCn5vp_7HIe_W0xZdyE53IyX4bBNuhalUCU0R0HBWS2aqh7Bag-68aMUsdXPMXQm_tMM9E69flWvd141CP2qXu8uOTss2NoO_XvXwfUI_NwDOPp4CRh1cgFHWT5EdFn7IRxZ8R9iaJMP</addsrcrecordid><sourcetype>Aggregation Database</sourcetype><iscdi>true</iscdi><recordtype>article</recordtype><pqid>32173957</pqid></control><display><type>article</type><title>Automatic Registration of MR and SPECT Images for Treatment Planning in Prostate Cancer</title><source>Elsevier ScienceDirect Journals Complete - AutoHoldings</source><source>MEDLINE</source><creator>Lee, Zhenghong ; Nagano, Kenichi K ; Duerk, Jeffrey L ; Sodee, D.Bruce ; Wilson, David L</creator><creatorcontrib>Lee, Zhenghong ; Nagano, Kenichi K ; Duerk, Jeffrey L ; Sodee, D.Bruce ; Wilson, David L</creatorcontrib><description>To aid in surgical and radiation therapy planning for prostate adenocarcinoma, a general-purpose automatic registration method that is based on mutual information was used to align magnetic resonance (MR) images and single photon emission computed tomographic (SPECT) images of the pelvis and prostate. The authors assessed the effects of various factors on alignment between pairs of MR and SPECT images, including the use of particular pulse sequences in MR imaging, image voxel intensity scaling, the use of different regions on the MR-SPECT histogram, spatial masking of nonoverlapping visual data between images, and multiresolution optimization. A mutual information algorithm was used as the cost function for automatic registration. Automatic registration was deemed acceptable when it resulted in a transformation with less than 2 voxel units (6 mm) difference in translation and less than 2° difference in rotation from that obtained with manual registration performed independently by nuclear medicine radiologists. Paired sets of MR and SPECT image volumes from four of five patients were successfully registered. For successful registration, MR images must be optimal and registration must be performed at full spatial resolution and at the full intensity range. Masking, cropping, and the normalization of mutual information, used to register partially overlapping MR-SPECT volumes, were not successful. Multiresolution optimization had little effect on the accuracy and speed of the registration. Automatic registration between MR and SPECT images of the pelvis can be achieved when data acquisition and image processing are performed properly. It should prove useful for prostate cancer diagnosis, staging, and treatment planning.</description><identifier>ISSN: 1076-6332</identifier><identifier>EISSN: 1878-4046</identifier><identifier>DOI: 10.1016/S1076-6332(03)80088-0</identifier><identifier>PMID: 12809423</identifier><language>eng</language><publisher>United States: Elsevier Inc</publisher><subject>Adenocarcinoma - diagnosis ; Algorithms ; Automatic Data Processing ; Bone Marrow - diagnostic imaging ; Clinical Protocols ; Femur - diagnostic imaging ; Humans ; Image Processing, Computer-Assisted ; Images, processing ; Magnetic Resonance Imaging ; Male ; monoclonal antibodies ; prostate neoplasms, MR ; prostate neoplasms, radionuclide studies ; Prostatic Neoplasms - diagnosis ; Pubic Symphysis - diagnostic imaging ; Radiography ; Registries ; Tomography, Emission-Computed, Single-Photon</subject><ispartof>Academic radiology, 2003-06, Vol.10 (6), p.673-684</ispartof><rights>2003 Acad Radiol</rights><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c392t-d3a9a66ecd76bb23abd7d949fe120dbce3bd8af6665ba21d51b8e94002eb5d203</citedby><cites>FETCH-LOGICAL-c392t-d3a9a66ecd76bb23abd7d949fe120dbce3bd8af6665ba21d51b8e94002eb5d203</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktohtml>$$Uhttps://dx.doi.org/10.1016/S1076-6332(03)80088-0$$EHTML$$P50$$Gelsevier$$H</linktohtml><link.rule.ids>314,780,784,3548,27922,27923,45993</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/12809423$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><creatorcontrib>Lee, Zhenghong</creatorcontrib><creatorcontrib>Nagano, Kenichi K</creatorcontrib><creatorcontrib>Duerk, Jeffrey L</creatorcontrib><creatorcontrib>Sodee, D.Bruce</creatorcontrib><creatorcontrib>Wilson, David L</creatorcontrib><title>Automatic Registration of MR and SPECT Images for Treatment Planning in Prostate Cancer</title><title>Academic radiology</title><addtitle>Acad Radiol</addtitle><description>To aid in surgical and radiation therapy planning for prostate adenocarcinoma, a general-purpose automatic registration method that is based on mutual information was used to align magnetic resonance (MR) images and single photon emission computed tomographic (SPECT) images of the pelvis and prostate. The authors assessed the effects of various factors on alignment between pairs of MR and SPECT images, including the use of particular pulse sequences in MR imaging, image voxel intensity scaling, the use of different regions on the MR-SPECT histogram, spatial masking of nonoverlapping visual data between images, and multiresolution optimization. A mutual information algorithm was used as the cost function for automatic registration. Automatic registration was deemed acceptable when it resulted in a transformation with less than 2 voxel units (6 mm) difference in translation and less than 2° difference in rotation from that obtained with manual registration performed independently by nuclear medicine radiologists. Paired sets of MR and SPECT image volumes from four of five patients were successfully registered. For successful registration, MR images must be optimal and registration must be performed at full spatial resolution and at the full intensity range. Masking, cropping, and the normalization of mutual information, used to register partially overlapping MR-SPECT volumes, were not successful. Multiresolution optimization had little effect on the accuracy and speed of the registration. Automatic registration between MR and SPECT images of the pelvis can be achieved when data acquisition and image processing are performed properly. It should prove useful for prostate cancer diagnosis, staging, and treatment planning.</description><subject>Adenocarcinoma - diagnosis</subject><subject>Algorithms</subject><subject>Automatic Data Processing</subject><subject>Bone Marrow - diagnostic imaging</subject><subject>Clinical Protocols</subject><subject>Femur - diagnostic imaging</subject><subject>Humans</subject><subject>Image Processing, Computer-Assisted</subject><subject>Images, processing</subject><subject>Magnetic Resonance Imaging</subject><subject>Male</subject><subject>monoclonal antibodies</subject><subject>prostate neoplasms, MR</subject><subject>prostate neoplasms, radionuclide studies</subject><subject>Prostatic Neoplasms - diagnosis</subject><subject>Pubic Symphysis - diagnostic imaging</subject><subject>Radiography</subject><subject>Registries</subject><subject>Tomography, Emission-Computed, Single-Photon</subject><issn>1076-6332</issn><issn>1878-4046</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2003</creationdate><recordtype>article</recordtype><sourceid>EIF</sourceid><recordid>eNqFkEtPGzEURq2qVRNof0KRVxUshl7bMx7PqooiCkhUjUgQS8uPO5FRZobaDlL_fSckiGVW91uc-zqEfGNwyYDJH0sGtSykEPwcxIUCUKqAD2TKVK2KEkr5ccxvyIScpPQEwCqpxGcyYVxBU3IxJY-zbR46k4Oj97gOKccxDz0dWvr7npre0-Xiar6it51ZY6LtEOkqoskd9pkuNqbvQ7-moaeLOKRsMtK56R3GL-RTazYJvx7qKXn4dbWa3xR3f65v57O7womG58IL0xgp0flaWsuFsb72Tdm0yDh461BYr0wrpays4cxXzCpsSgCOtvIcxCn5vp_7HIe_W0xZdyE53IyX4bBNuhalUCU0R0HBWS2aqh7Bag-68aMUsdXPMXQm_tMM9E69flWvd141CP2qXu8uOTss2NoO_XvXwfUI_NwDOPp4CRh1cgFHWT5EdFn7IRxZ8R9iaJMP</recordid><startdate>20030601</startdate><enddate>20030601</enddate><creator>Lee, Zhenghong</creator><creator>Nagano, Kenichi K</creator><creator>Duerk, Jeffrey L</creator><creator>Sodee, D.Bruce</creator><creator>Wilson, David L</creator><general>Elsevier Inc</general><scope>CGR</scope><scope>CUY</scope><scope>CVF</scope><scope>ECM</scope><scope>EIF</scope><scope>NPM</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>7U5</scope><scope>8FD</scope><scope>L7M</scope><scope>7X8</scope></search><sort><creationdate>20030601</creationdate><title>Automatic Registration of MR and SPECT Images for Treatment Planning in Prostate Cancer</title><author>Lee, Zhenghong ; Nagano, Kenichi K ; Duerk, Jeffrey L ; Sodee, D.Bruce ; Wilson, David L</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c392t-d3a9a66ecd76bb23abd7d949fe120dbce3bd8af6665ba21d51b8e94002eb5d203</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2003</creationdate><topic>Adenocarcinoma - diagnosis</topic><topic>Algorithms</topic><topic>Automatic Data Processing</topic><topic>Bone Marrow - diagnostic imaging</topic><topic>Clinical Protocols</topic><topic>Femur - diagnostic imaging</topic><topic>Humans</topic><topic>Image Processing, Computer-Assisted</topic><topic>Images, processing</topic><topic>Magnetic Resonance Imaging</topic><topic>Male</topic><topic>monoclonal antibodies</topic><topic>prostate neoplasms, MR</topic><topic>prostate neoplasms, radionuclide studies</topic><topic>Prostatic Neoplasms - diagnosis</topic><topic>Pubic Symphysis - diagnostic imaging</topic><topic>Radiography</topic><topic>Registries</topic><topic>Tomography, Emission-Computed, Single-Photon</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Lee, Zhenghong</creatorcontrib><creatorcontrib>Nagano, Kenichi K</creatorcontrib><creatorcontrib>Duerk, Jeffrey L</creatorcontrib><creatorcontrib>Sodee, D.Bruce</creatorcontrib><creatorcontrib>Wilson, David L</creatorcontrib><collection>Medline</collection><collection>MEDLINE</collection><collection>MEDLINE (Ovid)</collection><collection>MEDLINE</collection><collection>MEDLINE</collection><collection>PubMed</collection><collection>CrossRef</collection><collection>Solid State and Superconductivity Abstracts</collection><collection>Technology Research Database</collection><collection>Advanced Technologies Database with Aerospace</collection><collection>MEDLINE - Academic</collection><jtitle>Academic radiology</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Lee, Zhenghong</au><au>Nagano, Kenichi K</au><au>Duerk, Jeffrey L</au><au>Sodee, D.Bruce</au><au>Wilson, David L</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Automatic Registration of MR and SPECT Images for Treatment Planning in Prostate Cancer</atitle><jtitle>Academic radiology</jtitle><addtitle>Acad Radiol</addtitle><date>2003-06-01</date><risdate>2003</risdate><volume>10</volume><issue>6</issue><spage>673</spage><epage>684</epage><pages>673-684</pages><issn>1076-6332</issn><eissn>1878-4046</eissn><abstract>To aid in surgical and radiation therapy planning for prostate adenocarcinoma, a general-purpose automatic registration method that is based on mutual information was used to align magnetic resonance (MR) images and single photon emission computed tomographic (SPECT) images of the pelvis and prostate. The authors assessed the effects of various factors on alignment between pairs of MR and SPECT images, including the use of particular pulse sequences in MR imaging, image voxel intensity scaling, the use of different regions on the MR-SPECT histogram, spatial masking of nonoverlapping visual data between images, and multiresolution optimization. A mutual information algorithm was used as the cost function for automatic registration. Automatic registration was deemed acceptable when it resulted in a transformation with less than 2 voxel units (6 mm) difference in translation and less than 2° difference in rotation from that obtained with manual registration performed independently by nuclear medicine radiologists. Paired sets of MR and SPECT image volumes from four of five patients were successfully registered. For successful registration, MR images must be optimal and registration must be performed at full spatial resolution and at the full intensity range. Masking, cropping, and the normalization of mutual information, used to register partially overlapping MR-SPECT volumes, were not successful. Multiresolution optimization had little effect on the accuracy and speed of the registration. Automatic registration between MR and SPECT images of the pelvis can be achieved when data acquisition and image processing are performed properly. It should prove useful for prostate cancer diagnosis, staging, and treatment planning.</abstract><cop>United States</cop><pub>Elsevier Inc</pub><pmid>12809423</pmid><doi>10.1016/S1076-6332(03)80088-0</doi><tpages>12</tpages></addata></record>
fulltext fulltext
identifier ISSN: 1076-6332
ispartof Academic radiology, 2003-06, Vol.10 (6), p.673-684
issn 1076-6332
1878-4046
language eng
recordid cdi_proquest_miscellaneous_73438409
source Elsevier ScienceDirect Journals Complete - AutoHoldings; MEDLINE
subjects Adenocarcinoma - diagnosis
Algorithms
Automatic Data Processing
Bone Marrow - diagnostic imaging
Clinical Protocols
Femur - diagnostic imaging
Humans
Image Processing, Computer-Assisted
Images, processing
Magnetic Resonance Imaging
Male
monoclonal antibodies
prostate neoplasms, MR
prostate neoplasms, radionuclide studies
Prostatic Neoplasms - diagnosis
Pubic Symphysis - diagnostic imaging
Radiography
Registries
Tomography, Emission-Computed, Single-Photon
title Automatic Registration of MR and SPECT Images for Treatment Planning in Prostate Cancer
url https://sfx.bib-bvb.de/sfx_tum?ctx_ver=Z39.88-2004&ctx_enc=info:ofi/enc:UTF-8&ctx_tim=2025-01-09T15%3A17%3A52IST&url_ver=Z39.88-2004&url_ctx_fmt=infofi/fmt:kev:mtx:ctx&rfr_id=info:sid/primo.exlibrisgroup.com:primo3-Article-proquest_cross&rft_val_fmt=info:ofi/fmt:kev:mtx:journal&rft.genre=article&rft.atitle=Automatic%20Registration%20of%20MR%20and%20SPECT%20Images%20for%20Treatment%20Planning%20in%20Prostate%20Cancer&rft.jtitle=Academic%20radiology&rft.au=Lee,%20Zhenghong&rft.date=2003-06-01&rft.volume=10&rft.issue=6&rft.spage=673&rft.epage=684&rft.pages=673-684&rft.issn=1076-6332&rft.eissn=1878-4046&rft_id=info:doi/10.1016/S1076-6332(03)80088-0&rft_dat=%3Cproquest_cross%3E73438409%3C/proquest_cross%3E%3Curl%3E%3C/url%3E&disable_directlink=true&sfx.directlink=off&sfx.report_link=0&rft_id=info:oai/&rft_pqid=32173957&rft_id=info:pmid/12809423&rft_els_id=S1076633203800880&rfr_iscdi=true