Automated generation of directed graphs from vascular segmentations.
Automated feature extraction from medical images is an important task in imaging informatics. We describe a graph-based technique for automatically identifying vascular substructures within a vascular tree segmentation. We illustrate our technique using vascular segmentations from computed tomograph...
| Publicado en: | Journal of Biomedical Informatics Vol. 56; pp. 395 - 406 |
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| Autores principales: | , , |
| Formato: | Journal Article |
| Publicado: |
Academic Press Inc.
Aug2015
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| 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=109616580&site=ehost-live header: @attributes: shortDbName: ccm uiTerm: 109616580 longDbName: CINAHL Complete uiTag: AN controlInfo: bkinfo: dissinfo: jinfo: jid: 15320464 OMB jtl: Journal of Biomedical Informatics issn: 15320464 maglogo: N pubinfo: dt: Aug2015 vid: 56 pid: 735 pub: Academic Press Inc. place: Burlington, Massachusetts artinfo: ui: 109616580 NLM26165778 2013116464 10.1016/j.jbi.2015.07.002 NLM26165778 PMC4547695 109616580 ppf: 395 ppct: 11 formats: tig: atl: Automated generation of directed graphs from vascular segmentations. aug: au: Chapman, Brian E Berty, Holly P Schulthies, Stuart L sug: ab: Automated feature extraction from medical images is an important task in imaging informatics. We describe a graph-based technique for automatically identifying vascular substructures within a vascular tree segmentation. We illustrate our technique using vascular segmentations from computed tomography pulmonary angiography images. The segmentations were acquired in a semi-automated fashion using existing segmentation tools. A 3D parallel thinning algorithm was used to generate the vascular skeleton and then graph-based techniques were used to transform the skeleton to a directed graph with bifurcations and endpoints as nodes in the graph. Machine-learning classifiers were used to automatically prune false vascular structures from the directed graph. Semantic labeling of portions of the graph with pulmonary anatomy (pulmonary trunk and left and right pulmonary arteries) was achieved with high accuracy (percent correct⩾0.97). Least-squares cubic splines of the centerline paths between nodes were computed and were used to extract morphological features of the vascular tree. The graphs were used to automatically obtain diameter measurements that had high correlation (r⩾0.77) with manual measurements made from the same arteries. pubtype: Academic Journal doctype: Journal Article ougenre: Article language: English refInfo: holdings: @attributes: islocal: N |
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