WFRF:(Wang Chunliang)
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| Fältnamn | Indikatorer | Metadata |
|---|---|---|
| 000 | 03012naa a2200433 4500 | |
| 001 | oai:DiVA.org:kth-218488 | |
| 003 | SwePub | |
| 008 | 171129s2017 | |||||||||||000 ||eng| | |
| 024 | 7 | a https://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-2184882 URI |
| 024 | 7 | a https://doi.org/10.1016/B978-0-08-101291-8.00014-62 DOI |
| 040 | a (SwePub)kth | |
| 041 | a engb eng | |
| 042 | 9 SwePub | |
| 072 | 7 | a vet2 swepub-contenttype |
| 072 | 7 | a kap2 swepub-publicationtype |
| 100 | 1 | a Lidayová, K.4 aut |
| 245 | 1 0 | a Skeleton-based fast, fully automated generation of vessel tree structure for clinical evaluation of blood vessel systems |
| 264 | 1 | b Elsevier,c 2017 |
| 338 | a print2 rdacarrier | |
| 500 | a QC 20171129 | |
| 520 | a This chapter focuses on skeleton detection for clinical evaluation of blood vessel systems. In clinical evaluation, there is a need for fast and accurate segmentation algorithms that can reliably provide vessel measurements and additional information for clinicians to decide the diagnosis.Since blood vessels have a characteristic tubular shape, their segmentation can be accelerated and facilitated by first identifying the rough vessel centerlines, which can be seen as a special case of an image skeleton extraction algorithm. A segmentation algorithm will finally use the resulting skeleton as a seed region during the segmentation. The proposed method takes an unprocessed 3D computed tomography angiography (CTA) scan as an input and generates a connected graph of centrally located arterial voxels. The method works in two levels, where large arteries are captured in the first level, and small arteries are added in the second one. Experimental results show that the method can achieve high overlap rate and acceptable detection rate accuracies. High computational efficiency of the method opens the possibility for an interactive clinical use. | |
| 650 | 7 | a TEKNIK OCH TEKNOLOGIERx Medicinteknikx Medicinsk bildbehandling0 (SwePub)206032 hsv//swe |
| 650 | 7 | a ENGINEERING AND TECHNOLOGYx Medical Engineeringx Medical Image Processing0 (SwePub)206032 hsv//eng |
| 653 | a Anatomy-based analysis | |
| 653 | a Artery nodes connection | |
| 653 | a Artery nodes detection | |
| 653 | a Blood vessel systems | |
| 653 | a Computed tomography angiography | |
| 653 | a Skeleton extraction | |
| 653 | a Vascular segmentation | |
| 653 | a Vessel tree structure | |
| 700 | 1 | a Frimmel, H.4 aut |
| 700 | 1 | a Wang, Chunliang,d 1980-u KTH,Medicinsk bildbehandling och visualisering4 aut0 (Swepub:kth)u1tbkeej |
| 700 | 1 | a Bengtsson, E.4 aut |
| 700 | 1 | a Smedby, Örjanu KTH,Medicinsk bildbehandling och visualisering4 aut0 (Swepub:kth)u1vc2uzb |
| 710 | 2 | a KTHb Medicinsk bildbehandling och visualisering4 org |
| 773 | 0 | t Skeletonizationd : Elsevierg , s. 345-382q <345-382z 9780081012925z 9780081012918 |
| 856 | 4 8 | u https://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-218488 |
| 856 | 4 8 | u https://doi.org/10.1016/B978-0-08-101291-8.00014-6 |
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