Level-set-based artery-vein separation in blood pool agent CE-MR angiograms

Blood pool agents (BPAs) for contrast-enhanced (CE) magnetic-resonance angiography (MRA) allow prolonged imaging times for higher contrast and resolution. Imaging is performed during the steady state when the contrast agent is distributed through the complete vascular system. However, simultaneous v...

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Veröffentlicht in:	IEEE transactions on medical imaging Jg. 22; H. 10; S. 1224 - 1234
Hauptverfasser:	van Bemmel, C.M., Spreeuwers, L.J., Viergever, M.A., Niessen, W.J.
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	New York, NY IEEE 01.10.2003 Institute of Electrical and Electronics Engineers The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Schlagworte:	Algorithms Angiography Arteries Arteries - anatomy & histology Biological and medical sciences Blood Contrast Media Data visualization High-resolution imaging Humans Image Enhancement - methods Image Interpretation, Computer-Assisted - methods Image resolution Image segmentation Imaging, Three-Dimensional - methods Magnetic Resonance Angiography - methods Magnetic separation Medical imaging Medical sciences Pattern Recognition, Automated Radiotherapy. Instrumental treatment. Physiotherapy. Reeducation. Rehabilitation, orthophony, crenotherapy. Diet therapy and various other treatments (general aspects) Reproducibility of Results Sensitivity and Specificity Steady-state Subtraction Technique Technology. Biomaterials. Equipments. Material. Instrumentation Veins Veins & arteries Veins - anatomy & histology Biomedical engineering
ISSN:	0278-0062, 1558-254X
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Abstract	Blood pool agents (BPAs) for contrast-enhanced (CE) magnetic-resonance angiography (MRA) allow prolonged imaging times for higher contrast and resolution. Imaging is performed during the steady state when the contrast agent is distributed through the complete vascular system. However, simultaneous venous and arterial enhancement in this steady state hampers interpretation. In order to improve visualization of the arteries and veins from steady-state BPA data, a semiautomated method for artery-vein separation is presented. In this method, the central arterial axis and central venous axis are used as initializations for two surfaces that simultaneously evolve in order to capture the arterial and venous parts of the vasculature using the level-set framework. Since arteries and veins can be in close proximity of each other, leakage from the evolving arterial (venous) surface into the venous (arterial) part of the vasculature is inevitable. In these situations, voxels are labeled arterial or venous based on the arrival time of the respective surface. The evolution is steered by external forces related to feature images derived from the image data and by internal forces related to the geometry of the level sets. In this paper, the robustness and accuracy of three external forces (based on image intensity, image gradient, and vessel-enhancement filtering) and combinations of them are investigated and tested on seven patient datasets. To this end, results with the level-set-based segmentation are compared to the reference-standard manually obtained segmentations. Best results are achieved by applying a combination of intensity- and gradient-based forces and a smoothness constraint based on the curvature of the surface. By applying this combination to the seven datasets, it is shown that, with minimal user interaction, artery-vein separation for improved arterial and venous visualization in BPA CE-MRA can be achieved.
AbstractList	Blood pool agents (BPAs) for contrast-enhanced (CE) magnetic-resonance angiography (MRA) allow prolonged imaging times for higher contrast and resolution. Imaging is performed during the steady state when the contrast agent is distributed through the complete vascular system. However, simultaneous venous and arterial enhancement in this steady state hampers interpretation. In order to improve visualization of the arteries and veins from steady-state BPA data, a semiautomated method for artery-vein separation is presented. In this method, the central arterial axis and central venous axis are used as initializations for two surfaces that simultaneously evolve in order to capture the arterial and venous parts of the vasculature using the level-set framework. Since arteries and veins can be in close proximity of each other, leakage from the evolving arterial (venous) surface into the venous (arterial) part of the vasculature is inevitable. In these situations, voxels are labeled arterial or venous based on the arrival time of the respective surface. The evolution is steered by external forces related to feature images derived from the image data and by internal forces related to the geometry of the level sets. In this paper, the robustness and accuracy of three external forces (based on image intensity, image gradient, and vessel-enhancement filtering) and combinations of them are investigated and tested on seven patient datasets. To this end, results with the level-set-based segmentation are compared to the reference-standard manually obtained segmentations. Best results are achieved by applying a combination of intensity- and gradient-based forces and a smoothness constraint based on the curvature of the surface. By applying this combination to the seven datasets, it is shown that, with minimal user interaction, artery-vein separation for improved arterial and venous visualization in BPA CE-MRA can be achieved. Blood pool agents (BPAs) for contrast-enhanced (CE) magnetic-resonance angiography (MRA) allow prolonged imaging times for higher contrast and resolution. Imaging is performed during the steady state when the contrast agent is distributed through the complete vascular system. However, simultaneous venous and arterial enhancement in this steady state hampers interpretation. In order to improve visualization of the arteries and veins from steady-state BPA data, a semiautomated method for artery-vein separation is presented. In this method, the central arterial axis and central venous axis are used as initializations for two surfaces that simultaneously evolve in order to capture the arterial and venous parts of the vasculature using the level-set framework. Since arteries and veins can be in close proximity of each other, leakage from the evolving arterial (venous) surface into the venous (arterial) part of the vasculature is inevitable. In these situations, voxels are labeled arterial or venous based on the arrival time of the respective surface. The evolution is steered by external forces related to feature images derived from the image data and by internal forces related to the geometry of the level sets. In this paper, the robustness and accuracy of three external forces (based on image intensity, image gradient, and vessel-enhancement filtering) and combinations of them are investigated and tested on seven patient datasets. To this end, results with the level-set-based segmentation are compared to the reference-standard manually obtained segmentations. Best results are achieved by applying a combination of intensity- and gradient-based forces and a smoothness constraint based on the curvature of the surface. By applying this combination to the seven datasets, it is shown that, with minimal user interaction, artery-vein separation for improved arterial and venous visualization in BPA CE-MRA can be achieved.Blood pool agents (BPAs) for contrast-enhanced (CE) magnetic-resonance angiography (MRA) allow prolonged imaging times for higher contrast and resolution. Imaging is performed during the steady state when the contrast agent is distributed through the complete vascular system. However, simultaneous venous and arterial enhancement in this steady state hampers interpretation. In order to improve visualization of the arteries and veins from steady-state BPA data, a semiautomated method for artery-vein separation is presented. In this method, the central arterial axis and central venous axis are used as initializations for two surfaces that simultaneously evolve in order to capture the arterial and venous parts of the vasculature using the level-set framework. Since arteries and veins can be in close proximity of each other, leakage from the evolving arterial (venous) surface into the venous (arterial) part of the vasculature is inevitable. In these situations, voxels are labeled arterial or venous based on the arrival time of the respective surface. The evolution is steered by external forces related to feature images derived from the image data and by internal forces related to the geometry of the level sets. In this paper, the robustness and accuracy of three external forces (based on image intensity, image gradient, and vessel-enhancement filtering) and combinations of them are investigated and tested on seven patient datasets. To this end, results with the level-set-based segmentation are compared to the reference-standard manually obtained segmentations. Best results are achieved by applying a combination of intensity- and gradient-based forces and a smoothness constraint based on the curvature of the surface. By applying this combination to the seven datasets, it is shown that, with minimal user interaction, artery-vein separation for improved arterial and venous visualization in BPA CE-MRA can be achieved. In this method, the central arterial axis and central venous axis are used as initializations for two surfaces that simultaneously evolve in order to capture the arterial and venous parts of the vasculature using the level-set framework. Since arteries and veins can be in close proximity of each other, leakage from the evolving arterial (venous) surface into the venous (arterial) part of the vasculature is inevitable.
Author	Niessen, W.J. Viergever, M.A. van Bemmel, C.M. Spreeuwers, L.J.
Author_xml	– sequence: 1 givenname: C.M. surname: van Bemmel fullname: van Bemmel, C.M. organization: Image Sci. Inst., Univ. Med. Center, Utrecht, Netherlands – sequence: 2 givenname: L.J. surname: Spreeuwers fullname: Spreeuwers, L.J. organization: Image Sci. Inst., Univ. Med. Center, Utrecht, Netherlands – sequence: 3 givenname: M.A. surname: Viergever fullname: Viergever, M.A. organization: Image Sci. Inst., Univ. Med. Center, Utrecht, Netherlands – sequence: 4 givenname: W.J. surname: Niessen fullname: Niessen, W.J. organization: Image Sci. Inst., Univ. Med. Center, Utrecht, Netherlands
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Snippet	Blood pool agents (BPAs) for contrast-enhanced (CE) magnetic-resonance angiography (MRA) allow prolonged imaging times for higher contrast and resolution.... In this method, the central arterial axis and central venous axis are used as initializations for two surfaces that simultaneously evolve in order to capture...
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SubjectTerms	Algorithms Angiography Arteries Arteries - anatomy & histology Biological and medical sciences Blood Contrast Media Data visualization High-resolution imaging Humans Image Enhancement - methods Image Interpretation, Computer-Assisted - methods Image resolution Image segmentation Imaging, Three-Dimensional - methods Magnetic Resonance Angiography - methods Magnetic separation Medical imaging Medical sciences Pattern Recognition, Automated Radiotherapy. Instrumental treatment. Physiotherapy. Reeducation. Rehabilitation, orthophony, crenotherapy. Diet therapy and various other treatments (general aspects) Reproducibility of Results Sensitivity and Specificity Steady-state Subtraction Technique Technology. Biomaterials. Equipments. Material. Instrumentation Veins Veins & arteries Veins - anatomy & histology
Title	Level-set-based artery-vein separation in blood pool agent CE-MR angiograms
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