File Download

There are no files associated with this item.

  Links for fulltext
     (May Require Subscription)
Supplementary

Conference Paper: On Segmentation of Maxillary Sinus Membrane using Automatic Vertex Screening

TitleOn Segmentation of Maxillary Sinus Membrane using Automatic Vertex Screening
Authors
Keywordsmaxillary sinus membrane segmentation
vertex screening
cone beam computed tomography
Issue Date2020
PublisherIEEE. The Journal's web site is located at https://ieeexplore.ieee.org/xpl/conhome/1800602/all-proceedings
Citation
2020 IEEE International Conference on Visual Communications and Image Processing (VCIP), Macau, China, 1-4 December 2020, p. 108-111 How to Cite?
AbstractThe purpose of this study is to develop an automatic technique to segment the membrane of the maxillary sinus with morphological changes (e.g. thickened membrane and cysts) for the detection of abnormalities. The first step is to segment the sinus bone cavity in the CBCT image using fuzzy C-mean algorithm. Then, the vertices of inner bone walls of sinus in the mesh model are screened with vertex normal direction and angular based mean-distance filtering. The resulted vertices are then used to generate the bony sinus cavity mesh model by using Poisson surface reconstruction. Finally, the sinus membrane morphological changes are segmented by subtracting the air sinus segmentation from the reconstructed bony sinus cavity. The proposed method has been applied on 5 maxillary sinuses with mucosal thickening and has demonstrated that it can segment thin membrane thickening (<; 2 mm) successfully within 4.1% and 3.5% error in volume and surface area respectively. Existing methods have issues of leakages at openings and thin bones, and inaccuracy with irregular contours commonly seen in maxillary sinus. The current method overcomes these shortcomings.
Persistent Identifierhttp://hdl.handle.net/10722/307650
ISSN

 

DC FieldValueLanguage
dc.contributor.authorLi, KR-
dc.contributor.authorHsung, TC-
dc.contributor.authorYeung, WKA-
dc.contributor.authorBornstein, MM-
dc.date.accessioned2021-11-12T13:35:46Z-
dc.date.available2021-11-12T13:35:46Z-
dc.date.issued2020-
dc.identifier.citation2020 IEEE International Conference on Visual Communications and Image Processing (VCIP), Macau, China, 1-4 December 2020, p. 108-111-
dc.identifier.issn1018-8770-
dc.identifier.urihttp://hdl.handle.net/10722/307650-
dc.description.abstractThe purpose of this study is to develop an automatic technique to segment the membrane of the maxillary sinus with morphological changes (e.g. thickened membrane and cysts) for the detection of abnormalities. The first step is to segment the sinus bone cavity in the CBCT image using fuzzy C-mean algorithm. Then, the vertices of inner bone walls of sinus in the mesh model are screened with vertex normal direction and angular based mean-distance filtering. The resulted vertices are then used to generate the bony sinus cavity mesh model by using Poisson surface reconstruction. Finally, the sinus membrane morphological changes are segmented by subtracting the air sinus segmentation from the reconstructed bony sinus cavity. The proposed method has been applied on 5 maxillary sinuses with mucosal thickening and has demonstrated that it can segment thin membrane thickening (<; 2 mm) successfully within 4.1% and 3.5% error in volume and surface area respectively. Existing methods have issues of leakages at openings and thin bones, and inaccuracy with irregular contours commonly seen in maxillary sinus. The current method overcomes these shortcomings.-
dc.languageeng-
dc.publisherIEEE. The Journal's web site is located at https://ieeexplore.ieee.org/xpl/conhome/1800602/all-proceedings-
dc.relation.ispartof2020 IEEE International Conference on Visual Communications and Image Processing (VCIP)-
dc.rightsVisual Communications and Image Processing (VCIP). Copyright © IEEE.-
dc.rights©2020 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.-
dc.subjectmaxillary sinus membrane segmentation-
dc.subjectvertex screening-
dc.subjectcone beam computed tomography-
dc.titleOn Segmentation of Maxillary Sinus Membrane using Automatic Vertex Screening-
dc.typeConference_Paper-
dc.identifier.emailHsung, TC: tchsung@hku.hk-
dc.identifier.emailYeung, WKA: ndyeung@hku.hk-
dc.identifier.emailBornstein, MM: bornst@hku.hk-
dc.identifier.authorityYeung, WKA=rp02143-
dc.identifier.authorityBornstein, MM=rp02217-
dc.description.naturelink_to_subscribed_fulltext-
dc.identifier.doi10.1109/VCIP49819.2020.9301845-
dc.identifier.hkuros329816-
dc.identifier.spage108-
dc.identifier.epage111-
dc.publisher.placeUnited States-

Export via OAI-PMH Interface in XML Formats


OR


Export to Other Non-XML Formats