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Robust and fully automated segmentation of mandible from CT scans [article]

Neslisah Torosdagli, Denise K. Liberton, Payal Verma, Murat Sincan Janice Lee, Sumanta Pattanaik, Ulas Bagci
<span title="2017-02-23">2017</span> <i > arXiv </i> &nbsp; <span class="release-stage" >pre-print</span>
Mandible bone segmentation from computed tomography (CT) scans is challenging due to mandible's structural irregularities, complex shape patterns, and lack of contrast in joints.  ...  Despite heavy CT artifacts and dental fillings, consisting half of the CT image data in our experiments, we have achieved highly accurate detection and delineation results.  ...  DISCUSSIONS AND CONCLUDING REMARKS In this work, we develop a data-driven, robust, and accurate method for automatic mandible detection and delineation from CT scans.  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener" href="https://arxiv.org/abs/1702.07059v1">arXiv:1702.07059v1</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/5qnoyeqahrfavbdyl2lzeq2tra">fatcat:5qnoyeqahrfavbdyl2lzeq2tra</a> </span>
<a target="_blank" rel="noopener" href="https://web.archive.org/web/20200825150215/https://arxiv.org/pdf/1702.07059v1.pdf" title="fulltext PDF download" data-goatcounter-click="serp-fulltext" data-goatcounter-title="serp-fulltext"> <button class="ui simple right pointing dropdown compact black labeled icon button serp-button"> <i class="icon ia-icon"></i> Web Archive [PDF] <div class="menu fulltext-thumbnail"> <img src="https://blobs.fatcat.wiki/thumbnail/pdf/1f/b5/1fb5bea035e10ed5178ea45732e853961415b08c.180px.jpg" alt="fulltext thumbnail" loading="lazy"> </div> </button> </a> <a target="_blank" rel="external noopener" href="https://arxiv.org/abs/1702.07059v1" title="arxiv.org access"> <button class="ui compact blue labeled icon button serp-button"> <i class="file alternate outline icon"></i> arxiv.org </button> </a>

Automated Segmentation of CBCT Image Using Spiral CT Atlases and Convex Optimization [chapter]

Li Wang, Ken Chung Chen, Feng Shi, Shu Liao, Gang Li, Yaozong Gao, Steve GF Shen, Jin Yan, Philip K. M. Lee, Ben Chow, Nancy X. Liu, James J. Xia (+1 others)
<span title="">2013</span> <i title="Springer Berlin Heidelberg"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/2w3awgokqne6te4nvlofavy5a4" style="color: black;">Lecture Notes in Computer Science</a> </i> &nbsp;
In this paper, we presented a novel fully automated method for CBCT image segmentation.  ...  However, a major limitation of CBCT scans is the widespread image artifacts such as noise, beam hardening and inhomogeneity, causing great difficulties for accurate segmentation of bony structures from  ...  In this paper, we propose a fully automated CBCT segmentation method to 1) segment bony structures from the soft tissues, and 2) further separate the mandible from the maxilla.  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1007/978-3-642-40760-4_32">doi:10.1007/978-3-642-40760-4_32</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/czq5ihckzraonjnturfwc76exu">fatcat:czq5ihckzraonjnturfwc76exu</a> </span>
<a target="_blank" rel="noopener" href="https://web.archive.org/web/20170809013409/http://www.unc.edu/~fengs/documents/MICCAI2013_Wang_Automated.pdf" title="fulltext PDF download" data-goatcounter-click="serp-fulltext" data-goatcounter-title="serp-fulltext"> <button class="ui simple right pointing dropdown compact black labeled icon button serp-button"> <i class="icon ia-icon"></i> Web Archive [PDF] <div class="menu fulltext-thumbnail"> <img src="https://blobs.fatcat.wiki/thumbnail/pdf/59/d8/59d8bd32d5e32c946b9826f3d2136406f3acace1.180px.jpg" alt="fulltext thumbnail" loading="lazy"> </div> </button> </a> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1007/978-3-642-40760-4_32"> <button class="ui left aligned compact blue labeled icon button serp-button"> <i class="external alternate icon"></i> springer.com </button> </a>

Recurrent Convolutional Neural Networks for 3D Mandible Segmentation in Computed Tomography

Bingjiang Qiu, Jiapan Guo, Joep Kraeima, Haye Hendrik Glas, Weichuan Zhang, Ronald J. H. Borra, Max Johannes Hendrikus Witjes, Peter M. A. van Ooijen
<span title="2021-05-31">2021</span> <i title="MDPI AG"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/xuwogpw7hnaoljkcejqtymrqsa" style="color: black;">Journal of Personalized Medicine</a> </i> &nbsp;
The proposed RCNNSeg was evaluated on 109 head and neck CT scans from a local dataset and 40 scans from the PDDCA public dataset.  ...  standard and the automated segmentation.  ...  However, there are still significant challenges to completely automate the segmentation of the mandible from CT scans, whereas manual delineation is time consuming and has high inter-rater variabilities  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.3390/jpm11060492">doi:10.3390/jpm11060492</a> <a target="_blank" rel="external noopener" href="https://www.ncbi.nlm.nih.gov/pubmed/34072714">pmid:34072714</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/bw6fs44a5zcxpgqpj7lofp4k2i">fatcat:bw6fs44a5zcxpgqpj7lofp4k2i</a> </span>
<a target="_blank" rel="noopener" href="https://web.archive.org/web/20210611075642/https://res.mdpi.com/d_attachment/jpm/jpm-11-00492/article_deploy/jpm-11-00492.pdf" title="fulltext PDF download" data-goatcounter-click="serp-fulltext" data-goatcounter-title="serp-fulltext"> <button class="ui simple right pointing dropdown compact black labeled icon button serp-button"> <i class="icon ia-icon"></i> Web Archive [PDF] <div class="menu fulltext-thumbnail"> <img src="https://blobs.fatcat.wiki/thumbnail/pdf/3e/3e/3e3e43931864d9f905db2213a4387a6af7551cd5.180px.jpg" alt="fulltext thumbnail" loading="lazy"> </div> </button> </a> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.3390/jpm11060492"> <button class="ui left aligned compact blue labeled icon button serp-button"> <i class="unlock alternate icon" style="background-color: #fb971f;"></i> mdpi.com </button> </a>

Robust and Accurate Mandible Segmentation on Dental CBCT Scans Affected by Metal Artifacts Using a Prior Shape Model

Bingjiang Qiu, Hylke van der Wel, Joep Kraeima, Haye Hendrik Glas, Jiapan Guo, Ronald J. H. Borra, Max Johannes Hendrikus Witjes, Peter M. A. van Ooijen
<span title="2021-05-01">2021</span> <i title="MDPI AG"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/xuwogpw7hnaoljkcejqtymrqsa" style="color: black;">Journal of Personalized Medicine</a> </i> &nbsp;
Accurate mandible segmentation is significant in the field of maxillofacial surgery to guide clinical diagnosis and treatment and develop appropriate surgical plans.  ...  To overcome this problem, this paper proposes a novel deep learning-based approach (SASeg) for automated mandible segmentation that perceives overall mandible anatomical knowledge.  ...  The authors would like to acknowledge the support received from NVIDIA by providing a GPU as part of their GPU grant program.  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.3390/jpm11050364">doi:10.3390/jpm11050364</a> <a target="_blank" rel="external noopener" href="https://www.ncbi.nlm.nih.gov/pubmed/34062762">pmid:34062762</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/laskojq3g5akpcrfjeuoq4ipju">fatcat:laskojq3g5akpcrfjeuoq4ipju</a> </span>
<a target="_blank" rel="noopener" href="https://web.archive.org/web/20210715010804/https://pure.rug.nl/ws/files/171657673/Robust_and_Accurate_Mandible_Segmentation_on_Dental_CBCT_Scans_Affected_by_Metal_Artifacts_Using_a_Prior_Shape_Model.pdf" title="fulltext PDF download" data-goatcounter-click="serp-fulltext" data-goatcounter-title="serp-fulltext"> <button class="ui simple right pointing dropdown compact black labeled icon button serp-button"> <i class="icon ia-icon"></i> Web Archive [PDF] <div class="menu fulltext-thumbnail"> <img src="https://blobs.fatcat.wiki/thumbnail/pdf/87/e1/87e1db7890ba9fbfc5b118f132763269092b68fa.180px.jpg" alt="fulltext thumbnail" loading="lazy"> </div> </button> </a> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.3390/jpm11050364"> <button class="ui left aligned compact blue labeled icon button serp-button"> <i class="unlock alternate icon" style="background-color: #fb971f;"></i> mdpi.com </button> </a>

Model Constructions for Computational Anatomy
計算解剖モデルの構築

Hiroshi FUJITA, Takeshi HARA, Xiangrong ZHOU, Chisako MURAMATSU, Naoki KAMIYA
<span title="">2013</span> <i title="The Japanese Society of Medical Imaging Technology"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/vjsh2o3grvhhhcl4or2vfmmggy" style="color: black;">Medical Imaging Technology</a> </i> &nbsp;
recognizing the anatomical structures and analyzing the functions of different organs in a whole body region, all of which are imaged with imaging modalities such as CT, MR, PET, eye fundus photograph  ...  These progresses show the efficiency and potential usefulness of the proposed research works by the promising results.  ...  Acknowledgments Authors thank to many members in our Laboratory for their collaboration and advices.  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.11409/mit.31.278">doi:10.11409/mit.31.278</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/lokkx2pglnfave4bwbqblogl74">fatcat:lokkx2pglnfave4bwbqblogl74</a> </span>
<a target="_blank" rel="noopener" href="https://web.archive.org/web/20220314162544/https://www.jstage.jst.go.jp/article/mit/31/5/31_278/_pdf" title="fulltext PDF download" data-goatcounter-click="serp-fulltext" data-goatcounter-title="serp-fulltext"> <button class="ui simple right pointing dropdown compact black labeled icon button serp-button"> <i class="icon ia-icon"></i> Web Archive [PDF] <div class="menu fulltext-thumbnail"> <img src="https://blobs.fatcat.wiki/thumbnail/pdf/ef/c6/efc6c82fc3932ca4d21ba13d64a8839b009d77a4.180px.jpg" alt="fulltext thumbnail" loading="lazy"> </div> </button> </a> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.11409/mit.31.278"> <button class="ui left aligned compact blue labeled icon button serp-button"> <i class="external alternate icon"></i> Publisher / doi.org </button> </a>

Marker-based watershed transform method for fully automatic mandibular segmentation from low-dose CBCT images [article]

Yi Fan, Richard Beare, Harold Matthews, Paul Schneider, Nicky Kilpatrick, John Clement, Peter Claes, Anthony Penington, Christopher Adamson
<span title="2018-08-21">2018</span> <i title="Cold Spring Harbor Laboratory"> bioRxiv </i> &nbsp; <span class="release-stage" >pre-print</span>
We applied this method to segment the mandible from the rest of the CBCT image.  ...  Objectives: To propose a reliable and practical method for automatically segmenting the mandible from low-dose CBCT images.  ...  We would like to thank (Hidden Content) for sharing his CBCT images; (Hidden Content) for providing the test cases and manually segmenting the mandibles.  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1101/397166">doi:10.1101/397166</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/xkhfviyyjnevbpkj7x65og6lci">fatcat:xkhfviyyjnevbpkj7x65og6lci</a> </span>
<a target="_blank" rel="noopener" href="https://web.archive.org/web/20190429074654/https://www.biorxiv.org/content/biorxiv/early/2018/08/21/397166.full.pdf" title="fulltext PDF download" data-goatcounter-click="serp-fulltext" data-goatcounter-title="serp-fulltext"> <button class="ui simple right pointing dropdown compact black labeled icon button serp-button"> <i class="icon ia-icon"></i> Web Archive [PDF] <div class="menu fulltext-thumbnail"> <img src="https://blobs.fatcat.wiki/thumbnail/pdf/4f/36/4f360b661a454d872379e07f413250763a1bfd3f.180px.jpg" alt="fulltext thumbnail" loading="lazy"> </div> </button> </a> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1101/397166"> <button class="ui left aligned compact blue labeled icon button serp-button"> <i class="external alternate icon"></i> biorxiv.org </button> </a>

Marker-based watershed transform method for fully automatic mandibular segmentation from CBCT images

Yi Fan, Richard Beare, Harold Matthews, Paul Schneider, Nicky Kilpatrick, John Clement, Peter Claes, Anthony Penington, Christopher Adamson
<span title="2018-11-09">2019</span> <i title="British Institute of Radiology"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/ynd2dahnqfgmjnmhybgs7sstca" style="color: black;">Dentomaxillofacial Radiology</a> </i> &nbsp;
We applied this method to segment the mandible from the rest of the CBCT image.  ...  To propose a reliable and practical method for automatically segmenting the mandible from CBCT images.  ...  We would like to thank (Hidden Content) for sharing his CBCT images; (Hidden Content) for providing the test cases and manually segmenting the mandibles.  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1259/dmfr.20180261">doi:10.1259/dmfr.20180261</a> <a target="_blank" rel="external noopener" href="https://www.ncbi.nlm.nih.gov/pubmed/30379569">pmid:30379569</a> <a target="_blank" rel="external noopener" href="https://pubmed.ncbi.nlm.nih.gov/PMC6476380/">pmcid:PMC6476380</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/wywsum26hvd3zhlm2he6tsq57y">fatcat:wywsum26hvd3zhlm2he6tsq57y</a> </span>
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Deep Geodesic Learning for Segmentation and Anatomical Landmarking

Neslisah Torosdagli, Denise K. Liberton, Payal Verma, Murat Sincan, Janice S. Lee, Ulas Bagci
<span title="2018-10-12">2019</span> <i title="Institute of Electrical and Electronics Engineers (IEEE)"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/yhnt2pif75h2bmnnmdg7m6nlc4" style="color: black;">IEEE Transactions on Medical Imaging</a> </i> &nbsp;
Specifically, we focus on the challenging problem of mandible segmentation from cone-beam computed tomography (CBCT) scans and identification of 9 anatomical landmarks of the mandible on the geodesic space  ...  The proposed fully automated method showed superior efficacy compared to the state-of-the-art mandible segmentation and landmarking approaches in craniofacial anomalies and diseased states.  ...  Our study focuses on developing a fully automated mandible segmentation and anatomical landmark localization method using CBCT scans, which is robust to challenging CMF anomalies that have the greatest  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1109/tmi.2018.2875814">doi:10.1109/tmi.2018.2875814</a> <a target="_blank" rel="external noopener" href="https://www.ncbi.nlm.nih.gov/pubmed/30334750">pmid:30334750</a> <a target="_blank" rel="external noopener" href="https://pubmed.ncbi.nlm.nih.gov/PMC6475529/">pmcid:PMC6475529</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/ub7hwjh2nbhb3ockc2f37zfb3y">fatcat:ub7hwjh2nbhb3ockc2f37zfb3y</a> </span>
<a target="_blank" rel="noopener" href="https://web.archive.org/web/20190304144225/http://pdfs.semanticscholar.org/dddb/83d211a2f48333c09eaf8c4bc317f062ad01.pdf" title="fulltext PDF download" data-goatcounter-click="serp-fulltext" data-goatcounter-title="serp-fulltext"> <button class="ui simple right pointing dropdown compact black labeled icon button serp-button"> <i class="icon ia-icon"></i> Web Archive [PDF] <div class="menu fulltext-thumbnail"> <img src="https://blobs.fatcat.wiki/thumbnail/pdf/dd/db/dddb83d211a2f48333c09eaf8c4bc317f062ad01.180px.jpg" alt="fulltext thumbnail" loading="lazy"> </div> </button> </a> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1109/tmi.2018.2875814"> <button class="ui left aligned compact blue labeled icon button serp-button"> <i class="external alternate icon"></i> ieee.com </button> </a> <a target="_blank" rel="external noopener" href="https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6475529" title="pubmed link"> <button class="ui compact blue labeled icon button serp-button"> <i class="file alternate outline icon"></i> pubmed.gov </button> </a>

Semi-automatic CT Image Segmentation using Random Forests Learned from Partial Annotations

Oldřich Kodym, Michal Španěl
<span title="">2018</span> <i title="SCITEPRESS - Science and Technology Publications"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/lxwop3qtazexrkwj5xfe7k3uqm" style="color: black;">Proceedings of the 11th International Joint Conference on Biomedical Engineering Systems and Technologies</a> </i> &nbsp;
Manual segmentation of three-dimensional data obtained through CT scanning is very time demanding task for clinical experts and therefore the automation of this process is required.  ...  Precision of the proposed method is evaluated on various CT datasets using fully expert-annotated segmentations of these tissues.  ...  ACKNOWLEDGEMENTS This work was supported in part by the company 3Dim Laboratory and by the Technology Agency of the Czech Republic project TE01020415 (V3C -Visual Computing Competence Center).  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.5220/0006588801240131">doi:10.5220/0006588801240131</a> <a target="_blank" rel="external noopener" href="https://dblp.org/rec/conf/biostec/KodymS18.html">dblp:conf/biostec/KodymS18</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/3fzmuarux5d5fjioxsjlskjsoi">fatcat:3fzmuarux5d5fjioxsjlskjsoi</a> </span>
<a target="_blank" rel="noopener" href="https://web.archive.org/web/20190307182342/http://pdfs.semanticscholar.org/dae2/fd2a0b9655545c260f8985c3e694e75434d2.pdf" title="fulltext PDF download" data-goatcounter-click="serp-fulltext" data-goatcounter-title="serp-fulltext"> <button class="ui simple right pointing dropdown compact black labeled icon button serp-button"> <i class="icon ia-icon"></i> Web Archive [PDF] <div class="menu fulltext-thumbnail"> <img src="https://blobs.fatcat.wiki/thumbnail/pdf/da/e2/dae2fd2a0b9655545c260f8985c3e694e75434d2.180px.jpg" alt="fulltext thumbnail" loading="lazy"> </div> </button> </a> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.5220/0006588801240131"> <button class="ui left aligned compact blue labeled icon button serp-button"> <i class="external alternate icon"></i> Publisher / doi.org </button> </a>

Automated Skeleton Based Multi-modal Deformable Registration of Head&Neck Datasets [chapter]

Sebastian Steger, Stefan Wesarg
<span title="">2012</span> <i title="Springer Berlin Heidelberg"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/2w3awgokqne6te4nvlofavy5a4" style="color: black;">Lecture Notes in Computer Science</a> </i> &nbsp;
An articulated atlas is used to jointly obtain a segmentation of the skull, the mandible and the vertebrae C1-Th2 from the CT image.  ...  Unlike existing approaches it is fully automated, spatial relation of the bones is considered during their registration and only one of the images must be a CT scan.  ...  Methods not requiring explicit segmentation [8] [13] of the individual bones can only be used if both images are CT scans from which the bone surface can easily be extracted.  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1007/978-3-642-33418-4_9">doi:10.1007/978-3-642-33418-4_9</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/llajsjpz25e75dzvgpnminip3m">fatcat:llajsjpz25e75dzvgpnminip3m</a> </span>
<a target="_blank" rel="noopener" href="https://web.archive.org/web/20190505090003/https://link.springer.com/content/pdf/10.1007%2F978-3-642-33418-4_9.pdf" title="fulltext PDF download" data-goatcounter-click="serp-fulltext" data-goatcounter-title="serp-fulltext"> <button class="ui simple right pointing dropdown compact black labeled icon button serp-button"> <i class="icon ia-icon"></i> Web Archive [PDF] <div class="menu fulltext-thumbnail"> <img src="https://blobs.fatcat.wiki/thumbnail/pdf/12/92/1292ca01acef2ef188475c004cd68fdf2dd99518.180px.jpg" alt="fulltext thumbnail" loading="lazy"> </div> </button> </a> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1007/978-3-642-33418-4_9"> <button class="ui left aligned compact blue labeled icon button serp-button"> <i class="external alternate icon"></i> springer.com </button> </a>

A Novel Registration-Based Semiautomatic Mandible Segmentation Pipeline Using Computed Tomography Images to Study Mandibular Development

Ying Ji Chuang, Benjamin M. Doherty, Nagesh Adluru, Moo K. Chung, Houri K. Vorperian
<span title="">2017</span> <i title="Ovid Technologies (Wolters Kluwer Health)"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/5g5cxpi4szglzmnm6hdow7ckl4" style="color: black;">Journal of computer assisted tomography</a> </i> &nbsp;
Results: This pipeline was assessed using 20 mandibles from CT studies ages 1-19 years, segmented using both SAMS-processing and manual segmentation.  ...  Conclusions: Findings are indicative of a robust pipeline that reduces manual segmentation time by 75% and increases the feasibility of large-scale mandibular growth studies.  ...  Two raters who were experienced in segmenting mandibles from CT scans independently rated a total of 40 models from the 20 subjects in Group II.  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1097/rct.0000000000000669">doi:10.1097/rct.0000000000000669</a> <a target="_blank" rel="external noopener" href="https://www.ncbi.nlm.nih.gov/pubmed/28937489">pmid:28937489</a> <a target="_blank" rel="external noopener" href="https://pubmed.ncbi.nlm.nih.gov/PMC5847411/">pmcid:PMC5847411</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/2yove56cvzbkplyojggdpuhojq">fatcat:2yove56cvzbkplyojggdpuhojq</a> </span>
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Image-to-patient registration by natural anatomical surfaces of the head

Rüdiger Marmulla, Joachim Mühling, Georg Eggers
<span title="2007-01-01">2007</span> <i title="Walter de Gruyter GmbH"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/pm6j7l3gwjhxtmliqa33qx3y64" style="color: black;">Open Medicine</a> </i> &nbsp;
Placement and measurement of radio-opaque fiducial markers becomes unnecessary. The usability of face, auricle, maxilla and mandible for surface-based registration to CT image data was investigated.  ...  AbstractThe use of registration markers in computer-assisted surgery is combined with high logistic costs and efforts.During the preparation of image guided surgery, automated markerless patient-to-image  ...  CT image data was transferred to the SNN++ system for registration. Face and auricles could be segmented fully automatically. Mandible and maxilla were segmented semi-automatically.  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.2478/s11536-006-0042-7">doi:10.2478/s11536-006-0042-7</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/tgpvbxkiyrcgrjdw336rqbdusq">fatcat:tgpvbxkiyrcgrjdw336rqbdusq</a> </span>
<a target="_blank" rel="noopener" href="https://web.archive.org/web/20200305102333/https://www.degruyter.com/downloadpdf/j/med.2007.2.issue-1/s11536-006-0042-7/s11536-006-0042-7.pdf" title="fulltext PDF download" data-goatcounter-click="serp-fulltext" data-goatcounter-title="serp-fulltext"> <button class="ui simple right pointing dropdown compact black labeled icon button serp-button"> <i class="icon ia-icon"></i> Web Archive [PDF] </button> </a> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.2478/s11536-006-0042-7"> <button class="ui left aligned compact blue labeled icon button serp-button"> <i class="unlock alternate icon" style="background-color: #fb971f;"></i> Publisher / doi.org </button> </a>

Automated bone segmentation from dental CBCT images using patch-based sparse representation and convex optimization

Li Wang, Ken Chung Chen, Yaozong Gao, Feng Shi, Shu Liao, Gang Li, Steve G. F. Shen, Jin Yan, Philip K. M. Lee, Ben Chow, Nancy X. Liu, James J. Xia (+1 others)
<span title="2014-03-25">2014</span> <i title="Wiley"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/4xxxfsh2pjc4nhsa3qijpqv6zy" style="color: black;">Medical Physics (Lancaster)</a> </i> &nbsp;
Methods: To segment CBCT images, the authors propose a new method for fully automated CBCT segmentation by using patch-based sparse representation to (1) segment bony structures from the soft tissues and  ...  (2) further separate the mandible from the maxilla.  ...  This work was supported in part by National Institutes of Health (NIH) Grant Nos. DE022676 and CA140413. The authors report no conflicts of interest in conducting the research.  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1118/1.4868455">doi:10.1118/1.4868455</a> <a target="_blank" rel="external noopener" href="https://www.ncbi.nlm.nih.gov/pubmed/24694160">pmid:24694160</a> <a target="_blank" rel="external noopener" href="https://pubmed.ncbi.nlm.nih.gov/PMC3971832/">pmcid:PMC3971832</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/viok2gqqknfk7h4dy7baofjsuy">fatcat:viok2gqqknfk7h4dy7baofjsuy</a> </span>
<a target="_blank" rel="noopener" href="https://web.archive.org/web/20191013220934/http://europepmc.org/backend/ptpmcrender.fcgi?accid=PMC3971832&amp;blobtype=pdf" title="fulltext PDF download" data-goatcounter-click="serp-fulltext" data-goatcounter-title="serp-fulltext"> <button class="ui simple right pointing dropdown compact black labeled icon button serp-button"> <i class="icon ia-icon"></i> Web Archive [PDF] <div class="menu fulltext-thumbnail"> <img src="https://blobs.fatcat.wiki/thumbnail/pdf/ac/3c/ac3cc9c4c878da431a8a77209dcd97c58999b49e.180px.jpg" alt="fulltext thumbnail" loading="lazy"> </div> </button> </a> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1118/1.4868455"> <button class="ui left aligned compact blue labeled icon button serp-button"> <i class="external alternate icon"></i> Publisher / doi.org </button> </a> <a target="_blank" rel="external noopener" href="https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3971832" title="pubmed link"> <button class="ui compact blue labeled icon button serp-button"> <i class="file alternate outline icon"></i> pubmed.gov </button> </a>

CT image segmentation of bone for medical additive manufacturing using a convolutional neural network

Jordi Minnema, Maureen van Eijnatten, Wouter Kouw, Faruk Diblen, Adriënne Mendrik, Jan Wolff
<span title="">2018</span> <i title="Elsevier BV"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/wdwg5aetkjbgpga7kn2jevifmi" style="color: black;">Computers in Biology and Medicine</a> </i> &nbsp;
Conclusions: The fully-automated CNN was able to accurately segment the skull.  ...  The aim of the present study was to develop and train a convolutional neural network (CNN) for bone segmentation in computed tomography (CT) scans.  ...  Finally, we want to thank the engineers Niels Liberton, Sjoerd te Slaa and Frank Verver from the 3D Innovation Lab of the VU Medical Center Amsterdam for their assistance during data acquisition.  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1016/j.compbiomed.2018.10.012">doi:10.1016/j.compbiomed.2018.10.012</a> <a target="_blank" rel="external noopener" href="https://www.ncbi.nlm.nih.gov/pubmed/30366309">pmid:30366309</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/fbox36ltnvcr5c26pgxu7xi7jq">fatcat:fbox36ltnvcr5c26pgxu7xi7jq</a> </span>
<a target="_blank" rel="noopener" href="https://web.archive.org/web/20190428143506/https://ir.cwi.nl/pub/28072/28072.pdf" title="fulltext PDF download" data-goatcounter-click="serp-fulltext" data-goatcounter-title="serp-fulltext"> <button class="ui simple right pointing dropdown compact black labeled icon button serp-button"> <i class="icon ia-icon"></i> Web Archive [PDF] <div class="menu fulltext-thumbnail"> <img src="https://blobs.fatcat.wiki/thumbnail/pdf/cc/54/cc541fdea73b54cfd2701964e68531ee3d4f549c.180px.jpg" alt="fulltext thumbnail" loading="lazy"> </div> </button> </a> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1016/j.compbiomed.2018.10.012"> <button class="ui left aligned compact blue labeled icon button serp-button"> <i class="external alternate icon"></i> elsevier.com </button> </a>

Deep Learning Method for Mandibular Canal Segmentation in Dental Cone Beam Computed Tomography Volumes

Joel Jaskari, Jaakko Sahlsten, Jorma Järnstedt, Helena Mehtonen, Kalle Karhu, Osku Sundqvist, Ari Hietanen, Vesa Varjonen, Vesa Mattila, Kimmo Kaski
<span title="2020-04-03">2020</span> <i title="Springer Science and Business Media LLC"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/tnqhc2x2aneavcd3gx5h7mswhm" style="color: black;">Scientific Reports</a> </i> &nbsp;
Here we present a deep learning system for automatic localisation of the mandibular canals by applying a fully convolutional neural network segmentation on clinically diverse dataset of 637 cone beam CT  ...  Accurate localisation of mandibular canals in lower jaws is important in dental implantology, in which the implant position and dimensions are currently determined manually from 3D CT images by medical  ...  algorithm for the segmentation of the mandible.  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1038/s41598-020-62321-3">doi:10.1038/s41598-020-62321-3</a> <a target="_blank" rel="external noopener" href="https://www.ncbi.nlm.nih.gov/pubmed/32245989">pmid:32245989</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/zew4nfrehbbahhorg5lt3tjoqa">fatcat:zew4nfrehbbahhorg5lt3tjoqa</a> </span>
<a target="_blank" rel="noopener" href="https://web.archive.org/web/20201106153029/https://acris.aalto.fi/ws/portalfiles/portal/42556109/s41598_020_62321_3.pdf" title="fulltext PDF download" data-goatcounter-click="serp-fulltext" data-goatcounter-title="serp-fulltext"> <button class="ui simple right pointing dropdown compact black labeled icon button serp-button"> <i class="icon ia-icon"></i> Web Archive [PDF] <div class="menu fulltext-thumbnail"> <img src="https://blobs.fatcat.wiki/thumbnail/pdf/ef/31/ef314349ab76cef28be0a5cdc131ef68de044451.180px.jpg" alt="fulltext thumbnail" loading="lazy"> </div> </button> </a> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1038/s41598-020-62321-3"> <button class="ui left aligned compact blue labeled icon button serp-button"> <i class="unlock alternate icon" style="background-color: #fb971f;"></i> Publisher / doi.org </button> </a>
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