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GPU-accelerated framework for intracoronary optical coherence tomography imaging at the push of a button.

Han M, Kim K, Jang SJ, Cho HS, Bouma BE, Oh WY, Ryu S - PLoS ONE (2015)

Bottom Line: To help more accurate diagnosis and monitoring of the disease, many researchers have recently worked on visualization of various coronary microscopic features including stent struts by constructing three-dimensional (3D) volumetric rendering from series of cross-sectional intracoronary FD-OCT images.In this paper, we present the first, to our knowledge, "push-of-a-button" graphics processing unit (GPU)-accelerated framework for intracoronary OCT imaging.Our framework visualizes 3D microstructures of the vessel wall with stent struts from raw binary OCT data acquired by the system digitizer as one seamless process.

View Article: PubMed Central - PubMed

Affiliation: Department of Computer Science, Korea Advanced Institute of Science and Technology, Daejeon, Republic of Korea.

ABSTRACT
Frequency domain optical coherence tomography (FD-OCT) has become one of the important clinical tools for intracoronary imaging to diagnose and monitor coronary artery disease, which has been one of the leading causes of death. To help more accurate diagnosis and monitoring of the disease, many researchers have recently worked on visualization of various coronary microscopic features including stent struts by constructing three-dimensional (3D) volumetric rendering from series of cross-sectional intracoronary FD-OCT images. In this paper, we present the first, to our knowledge, "push-of-a-button" graphics processing unit (GPU)-accelerated framework for intracoronary OCT imaging. Our framework visualizes 3D microstructures of the vessel wall with stent struts from raw binary OCT data acquired by the system digitizer as one seamless process. The framework reports the state-of-the-art performance; from raw OCT data, it takes 4.7 seconds to provide 3D visualization of a 5-cm-long coronary artery (of size 1600 samples x 1024 A-lines x 260 frames) with stent struts and detection of malapposition automatically at the single push of a button.

No MeSH data available.


Related in: MedlinePlus

Catheter and guide-wire in a sample FD-OCT image.(b) is an enlarged image of the yellow box in (a). The left (red) arrow denotes the sheath of the catheter and the right (blue) arrow denotes guide-wire.
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pone.0124192.g003: Catheter and guide-wire in a sample FD-OCT image.(b) is an enlarged image of the yellow box in (a). The left (red) arrow denotes the sheath of the catheter and the right (blue) arrow denotes guide-wire.

Mentions: First, we automatically segment the sheath of the catheter by using its unique characteristic. Consider the yellow box in Fig 3(a), which is enlarged in Fig 3(b). FD-OCT images represent the sheath of the catheter as a horizontal line with strong signal as shown by the left (red) arrow in Fig 3(b). Using this observation, we automatically detect the sheath of the catheter by calculating the average horizontal intensity values in each image and selecting the area with the highest intensity.


GPU-accelerated framework for intracoronary optical coherence tomography imaging at the push of a button.

Han M, Kim K, Jang SJ, Cho HS, Bouma BE, Oh WY, Ryu S - PLoS ONE (2015)

Catheter and guide-wire in a sample FD-OCT image.(b) is an enlarged image of the yellow box in (a). The left (red) arrow denotes the sheath of the catheter and the right (blue) arrow denotes guide-wire.
© Copyright Policy
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC4400174&req=5

pone.0124192.g003: Catheter and guide-wire in a sample FD-OCT image.(b) is an enlarged image of the yellow box in (a). The left (red) arrow denotes the sheath of the catheter and the right (blue) arrow denotes guide-wire.
Mentions: First, we automatically segment the sheath of the catheter by using its unique characteristic. Consider the yellow box in Fig 3(a), which is enlarged in Fig 3(b). FD-OCT images represent the sheath of the catheter as a horizontal line with strong signal as shown by the left (red) arrow in Fig 3(b). Using this observation, we automatically detect the sheath of the catheter by calculating the average horizontal intensity values in each image and selecting the area with the highest intensity.

Bottom Line: To help more accurate diagnosis and monitoring of the disease, many researchers have recently worked on visualization of various coronary microscopic features including stent struts by constructing three-dimensional (3D) volumetric rendering from series of cross-sectional intracoronary FD-OCT images.In this paper, we present the first, to our knowledge, "push-of-a-button" graphics processing unit (GPU)-accelerated framework for intracoronary OCT imaging.Our framework visualizes 3D microstructures of the vessel wall with stent struts from raw binary OCT data acquired by the system digitizer as one seamless process.

View Article: PubMed Central - PubMed

Affiliation: Department of Computer Science, Korea Advanced Institute of Science and Technology, Daejeon, Republic of Korea.

ABSTRACT
Frequency domain optical coherence tomography (FD-OCT) has become one of the important clinical tools for intracoronary imaging to diagnose and monitor coronary artery disease, which has been one of the leading causes of death. To help more accurate diagnosis and monitoring of the disease, many researchers have recently worked on visualization of various coronary microscopic features including stent struts by constructing three-dimensional (3D) volumetric rendering from series of cross-sectional intracoronary FD-OCT images. In this paper, we present the first, to our knowledge, "push-of-a-button" graphics processing unit (GPU)-accelerated framework for intracoronary OCT imaging. Our framework visualizes 3D microstructures of the vessel wall with stent struts from raw binary OCT data acquired by the system digitizer as one seamless process. The framework reports the state-of-the-art performance; from raw OCT data, it takes 4.7 seconds to provide 3D visualization of a 5-cm-long coronary artery (of size 1600 samples x 1024 A-lines x 260 frames) with stent struts and detection of malapposition automatically at the single push of a button.

No MeSH data available.


Related in: MedlinePlus