Evaluation of advanced Lukas-Kanade optical flow on thoracic 4D-CT.
Extensive use of high frequency imaging in medical applications permit the estimation of velocity fields which corresponds to motion of landmarks in the imaging field. The focus of this work is on the development of a robust local optical flow algorithm for velocity field estimation in medical appli...
| Publicado en: | Journal of Clinical Monitoring & Computing Vol. 27; no. 4; pp. 433 - 442 |
|---|---|
| Autores principales: | , , , |
| Formato: | research Journal Article |
| Publicado: |
Springer Nature
Aug2013
|
| Acceso en línea: | Ver este registro en EBSCOhost |
| fields | @attributes: recordID: 1 pdfLink: plink: https://search.ebscohost.com/login.aspx?direct=true&db=ccm&AN=104078509&site=ehost-live header: @attributes: shortDbName: ccm uiTerm: 104078509 longDbName: CINAHL Complete uiTag: AN controlInfo: bkinfo: dissinfo: jinfo: jid: 13871307 OHC jtl: Journal of Clinical Monitoring & Computing issn: 13871307 maglogo: N pubinfo: dt: Aug2013 vid: 27 iid: 4 pid: 237 pub: Springer Nature place: New York, New York artinfo: ui: 104078509 NLM23549645 2012165905 10.1007/s10877-013-9454-5 NLM23549645 104078509 ppf: 433 ppct: 9 formats: fmt: @attributes: type: P tig: atl: Evaluation of advanced Lukas-Kanade optical flow on thoracic 4D-CT. aug: au: Hoog Antink, Christoph Bernhard Singh, Tarunraj Singla, Puneet Podgorsak, Matthew affil: Department of Mechanical and Aerospace Engineering, SUNY at Buffalo, Buffalo, NY, 14260, USA, choogant@buffalo.edu. sug: subj: Tomography, X-Ray Computed Methods Optics Algorithms Human Statistics Information Science Methods Radiographic Image Interpretation, Computer-Assisted Radiography, Thoracic Methods Reproducibility of Results ab: Extensive use of high frequency imaging in medical applications permit the estimation of velocity fields which corresponds to motion of landmarks in the imaging field. The focus of this work is on the development of a robust local optical flow algorithm for velocity field estimation in medical applications. Local polynomial fits to the medical image intensity-maps are used to generate convolution operators to estimate the spatial gradients. A novel polynomial window function with a compact support is used to differentially weight the optical flow gradient constraints in the region of interest. Tikhonov regularization is exploited to synthesize a well posed optimization problem and to penalize large displacements. The proposed algorithm is tested and validated on benchmark datasets for deformable image registration. The ten datasets include large and small deformations, and illustrate that the proposed algorithm outperforms or is competitive with other algorithms tested on this dataset, when using mean and variance of the displacement error as performance metrics. pubtype: Academic Journal doctype: research Journal Article ougenre: Article language: English refInfo: holdings: @attributes: islocal: N |
|---|