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Reference TypeConference Paper (Conference Proceedings)
Last Update2017: administrator
Metadata Last Update2021: administrator
Citation KeyZafalonKovacsFerr:2017:De3DSa
TitleDetection of 3D salient points in magnetic resonance images using the dual-tree complex wavelet transform
Access Date2021, Mar. 02
Number of Files1
Size684 KiB
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Author1 Zafalon Kovacs, Nicole
2 Ferrari, Ricardo José
Affiliation1 Universidade Federal de São Carlos
2 Universidade Federal de São Carlos
EditorTorchelsen, Rafael Piccin
Nascimento, Erickson Rangel do
Panozzo, Daniele
Liu, Zicheng
Farias, Mylène
Viera, Thales
Sacht, Leonardo
Ferreira, Nivan
Comba, João Luiz Dihl
Hirata, Nina
Schiavon Porto, Marcelo
Vital, Creto
Pagot, Christian Azambuja
Petronetto, Fabiano
Clua, Esteban
Cardeal, Flávio
Conference NameConference on Graphics, Patterns and Images, 30 (SIBGRAPI)
Conference LocationNiterói, RJ
DateOct. 17-20, 2017
Book TitleProceedings
PublisherSociedade Brasileira de Computação
Publisher CityPorto Alegre
Tertiary TypeUndergraduate Work
History2017-09-08 14:26:44 :: -> administrator ::
2021-02-23 03:53:31 :: administrator -> :: 2017
Content and structure area
Is the master or a copy?is the master
Content Stagecompleted
Keywords3D salient points, DT-CWT, MRI, complex wavelets.
AbstractDetection of 3D salient points in medical images has many important applications such as image registration and mesh positioning for the purpose of segmentation of important anatomical structures. In this study, we present preliminary results of a proposed method for the detection of 3D salient points in Magnetic Resonance (MR) images of human brain. Our method, which is based on the Dual-Tree Complex Wavelet Transform, combines the oriented wavelet sub-bands (by multiplying the ones on the same scale and upsampling the result to an upper level scale) to create an image map in which local maxima correspond to the salient points. Qualitative assessment was conducted using 566 brain MRI images, whose results were combined together to create a point cloud showing the concentration of the salient points on important brain regions. The results indicate that our method has a great potential to detect important 3D salient points in MR images.
ArrangementSIBGRAPI 2017 > Detection of 3D...
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Next Higher Units8JMKD3MGPAW/3PKCC58
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