Abstract：
:This paper presents a new hybrid camera motion tracking method for bronchoscopic navigation combining SIFT, epipolar geometry analysis, Kalman filtering, and image registration. In a thorough evaluation, we compare it to state-of-the-art tracking methods. Our hybrid algorithm for predicting bronchoscope motion uses SIFT features and epipolar constraints to obtain an estimate for inter-frame pose displacements and Kalman filtering to find an estimate for the magnitude of the motion. We then execute bronchoscope tracking by performing image registration initialized by these estimates. This procedure registers the actual bronchoscopic video and the virtual camera images generated from 3D chest CT data taken prior to bronchoscopic examination for continuous bronchoscopic navigation. A comparative assessment of our new method and the state-of-the-art methods is performed on actual patient data and phantom data. Experimental results from both datasets demonstrate a significant performance boost of navigation using our new method. Our hybrid method is a promising means for bronchoscope tracking, and outperforms other methods based solely on Kalman filtering or image features and image registration.
journal_name
Med Image Analjournal_title
Medical image analysisauthors
Luó X,Feuerstein M,Deguchi D,Kitasaka T,Takabatake H,Mori Kdoi
10.1016/j.media.2010.11.001subject
Has Abstractpub_date
2012-04-01 00:00:00pages
577-96issue
3eissn
1361-8415issn
1361-8423pii
S1361-8415(10)00127-1journal_volume
16pub_type
杂志文章abstract：:The problem of respiratory motion has proved a serious obstacle in developing techniques to acquire images or guide interventions in abdominal and thoracic organs. Motion models offer a possible solution to these problems, and as a result the field of respiratory motion modelling has become an active one over the past...
journal_title：Medical image analysis
pub_type： 杂志文章,评审
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journal_title：Medical image analysis
pub_type： 杂志文章
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journal_title：Medical image analysis
pub_type： 杂志文章
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更新日期：2007-12-01 00:00:00
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journal_title：Medical image analysis
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journal_title：Medical image analysis
pub_type： 杂志文章
doi：10.1016/j.media.2014.04.006
更新日期：2014-07-01 00:00:00
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pub_type： 杂志文章
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journal_title：Medical image analysis
pub_type： 杂志文章
doi：10.1016/j.media.2009.11.004
更新日期：2010-04-01 00:00:00
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pub_type： 杂志文章
doi：10.1016/j.media.2015.05.005
更新日期：2016-01-01 00:00:00
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