The Experts below are selected from a list of 1152 Experts worldwide ranked by ideXlab platform
Giuseppe Placidi - One of the best experts on this subject based on the ideXlab platform.
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A shape-based segmentation algorithm for X-ray digital subtraction angiography images
Computer methods and programs in biomedicine, 2009Co-Authors: Danilo Franchi, Pasquale Gallo, Luca Marsili, Giuseppe PlacidiAbstract:We present an efficient algorithm for Vessel segmentation of digital subtraction angiography (DSA) images. Continuous DSA images (projections), obtained by X-ray fluoroscopy with contrast-media, are normally used as road maps in Vessel catheterization. A more efficient technique would consist in the use of a 3D model reconstruction of the vascular tree, instead of continuous X-ray scans, as a map. By Separating Vessel information from the undesired background (noise and signals coming from other organs and motion artefacts), efficient segmentation can play a key role in reducing the number of projections (X-ray scans) necessary to reconstruct a 3D vascular model. In what follows, the proposed method is described and some experimental results are reported, thus illustrating the behaviour of the algorithm when compared to other segmentation methods, ideated for the same application. The automatic calculation methods for some of the parameters used are also reported and discussed.
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ISVC (2) - A Novel Segmentation Algorithm for Digital Subtraction Angiography Images: First Experimental Results
Advances in Visual Computing, 2008Co-Authors: Danilo Franchi, Pasquale Gallo, Giuseppe PlacidiAbstract:We present an efficient algorithm for Vessel segmentation of Digital Subtraction Angiography (DSA) images. Continuous DSA images (projections), obtained by X-ray fluoroscopy with contrast-media, are normally used as road maps in Vessel catheterization. A more efficient technique would consist in the use of a 3D model reconstruction of the vascular tree, instead of continuous X-ray scans, as a map. By Separating Vessel information from the undesired background (noise and signals coming from other organs and motion artefacts), efficient segmentation can play a key role in reducing the number of projections (X-ray scans) necessary to reconstruct a 3D vascular model. In what follows, the proposed method is described and some experimental results are reported, thus illustrating the behaviour of the algorithm when compared to other segmentation methods, ideated for the same application. The automatic calculation methods for the parameters used are also reported and discussed.
Danilo Franchi - One of the best experts on this subject based on the ideXlab platform.
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A shape-based segmentation algorithm for X-ray digital subtraction angiography images
Computer methods and programs in biomedicine, 2009Co-Authors: Danilo Franchi, Pasquale Gallo, Luca Marsili, Giuseppe PlacidiAbstract:We present an efficient algorithm for Vessel segmentation of digital subtraction angiography (DSA) images. Continuous DSA images (projections), obtained by X-ray fluoroscopy with contrast-media, are normally used as road maps in Vessel catheterization. A more efficient technique would consist in the use of a 3D model reconstruction of the vascular tree, instead of continuous X-ray scans, as a map. By Separating Vessel information from the undesired background (noise and signals coming from other organs and motion artefacts), efficient segmentation can play a key role in reducing the number of projections (X-ray scans) necessary to reconstruct a 3D vascular model. In what follows, the proposed method is described and some experimental results are reported, thus illustrating the behaviour of the algorithm when compared to other segmentation methods, ideated for the same application. The automatic calculation methods for some of the parameters used are also reported and discussed.
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ISVC (2) - A Novel Segmentation Algorithm for Digital Subtraction Angiography Images: First Experimental Results
Advances in Visual Computing, 2008Co-Authors: Danilo Franchi, Pasquale Gallo, Giuseppe PlacidiAbstract:We present an efficient algorithm for Vessel segmentation of Digital Subtraction Angiography (DSA) images. Continuous DSA images (projections), obtained by X-ray fluoroscopy with contrast-media, are normally used as road maps in Vessel catheterization. A more efficient technique would consist in the use of a 3D model reconstruction of the vascular tree, instead of continuous X-ray scans, as a map. By Separating Vessel information from the undesired background (noise and signals coming from other organs and motion artefacts), efficient segmentation can play a key role in reducing the number of projections (X-ray scans) necessary to reconstruct a 3D vascular model. In what follows, the proposed method is described and some experimental results are reported, thus illustrating the behaviour of the algorithm when compared to other segmentation methods, ideated for the same application. The automatic calculation methods for the parameters used are also reported and discussed.
Pasquale Gallo - One of the best experts on this subject based on the ideXlab platform.
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A shape-based segmentation algorithm for X-ray digital subtraction angiography images
Computer methods and programs in biomedicine, 2009Co-Authors: Danilo Franchi, Pasquale Gallo, Luca Marsili, Giuseppe PlacidiAbstract:We present an efficient algorithm for Vessel segmentation of digital subtraction angiography (DSA) images. Continuous DSA images (projections), obtained by X-ray fluoroscopy with contrast-media, are normally used as road maps in Vessel catheterization. A more efficient technique would consist in the use of a 3D model reconstruction of the vascular tree, instead of continuous X-ray scans, as a map. By Separating Vessel information from the undesired background (noise and signals coming from other organs and motion artefacts), efficient segmentation can play a key role in reducing the number of projections (X-ray scans) necessary to reconstruct a 3D vascular model. In what follows, the proposed method is described and some experimental results are reported, thus illustrating the behaviour of the algorithm when compared to other segmentation methods, ideated for the same application. The automatic calculation methods for some of the parameters used are also reported and discussed.
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ISVC (2) - A Novel Segmentation Algorithm for Digital Subtraction Angiography Images: First Experimental Results
Advances in Visual Computing, 2008Co-Authors: Danilo Franchi, Pasquale Gallo, Giuseppe PlacidiAbstract:We present an efficient algorithm for Vessel segmentation of Digital Subtraction Angiography (DSA) images. Continuous DSA images (projections), obtained by X-ray fluoroscopy with contrast-media, are normally used as road maps in Vessel catheterization. A more efficient technique would consist in the use of a 3D model reconstruction of the vascular tree, instead of continuous X-ray scans, as a map. By Separating Vessel information from the undesired background (noise and signals coming from other organs and motion artefacts), efficient segmentation can play a key role in reducing the number of projections (X-ray scans) necessary to reconstruct a 3D vascular model. In what follows, the proposed method is described and some experimental results are reported, thus illustrating the behaviour of the algorithm when compared to other segmentation methods, ideated for the same application. The automatic calculation methods for the parameters used are also reported and discussed.
Luca Marsili - One of the best experts on this subject based on the ideXlab platform.
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A shape-based segmentation algorithm for X-ray digital subtraction angiography images
Computer methods and programs in biomedicine, 2009Co-Authors: Danilo Franchi, Pasquale Gallo, Luca Marsili, Giuseppe PlacidiAbstract:We present an efficient algorithm for Vessel segmentation of digital subtraction angiography (DSA) images. Continuous DSA images (projections), obtained by X-ray fluoroscopy with contrast-media, are normally used as road maps in Vessel catheterization. A more efficient technique would consist in the use of a 3D model reconstruction of the vascular tree, instead of continuous X-ray scans, as a map. By Separating Vessel information from the undesired background (noise and signals coming from other organs and motion artefacts), efficient segmentation can play a key role in reducing the number of projections (X-ray scans) necessary to reconstruct a 3D vascular model. In what follows, the proposed method is described and some experimental results are reported, thus illustrating the behaviour of the algorithm when compared to other segmentation methods, ideated for the same application. The automatic calculation methods for some of the parameters used are also reported and discussed.
Franck Christian Bizien - One of the best experts on this subject based on the ideXlab platform.
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anti foaming degassing device for use in fuel dispensing equipment particularly in biofuel dispensing equipment
2008Co-Authors: Franck Christian BizienAbstract:An anti-foaming degassing device for use in fuel dispensing equipment, having: a circulating pump (1) for the fuel, a vortex degassing enclosure (2) connected to the outlet of the pump (1) and provided with a lateral outlet pipe (8) for the degassed fuel and with an axial outlet pipe (9) for a gas-enriched fraction of fuel, a Separating Vessel (3) connected to the axial outlet pipe (9) in which the liquid fuel is separated by gravity before being transferred back to the pump (1), and control means (20) making it possible to vary the flow rate of the fraction collected by the axial outlet pipe (9) according to its gas content. The axial outlet pipe (9) opens in the lower part of the Separating Vessel (3), into the gravity-separated liquid fuel, in such a way as to prevent the formation of foam in this Vessel.
