Bildgebende Charakterisierung und Quantifizierung der Angiogenese bei Arthritis mittels μCT im Mausmodell

Angiogenesis is a key pathophysiological process in chronic inflammatory reactions, especially in arthritis, the progression and course of the disease influences. For quantification of changes of bone blood flow in mice with rheumatoid arthritis (RA)a multi-level segmentation method was developed. The blood vessels in the area of ​​inflamed knee joint were segmented and then quantitative 3D histomorphometric parameters were calculated. Two groups of mice (WT and RA) were investigated in vitro and the results compared to each other.Angiogenese ist ein wesentlicher pathophysiologischer Prozess bei chronischen Entz¨undungsreaktionen, insbesondere bei Arthritis, der das Fortschreiten und den Verlauf der Krankheit beeinflusst. Bei der Suche nach m¨oglichen Arthritistherapien sind die therapeutischen Ans¨atze gegen Angiogenese von großem Interesse. Um die ¨Anderungen der Knochendurchblutung bei M¨ausen mit rheumatoider Arthritis (RA) zu quantifizieren, wurde ein mehrstufiges Segmentierungsverfahren entwickelt. Dabei wurden die Blutgef¨aße im Bereich des entz¨undetes Kniegelenks segmentiert und anschließend quantitative 3D histomorphometrische Parameter berechnet. Zwei Gruppen von M¨ause (RA und WT) wurden in-vitro untersucht und die Ergebnisse miteinander verglichen

Characterization and quantification of angiogenesis in rheumatoid arthritis in a mouse model using Micro-CT

Angiogenese ist ein wesentlicher pathophysiologischer Prozess bei chronischen Entz¨undungsreaktionen, insbesondere bei Arthritis, der das Fortschreiten und den Verlauf der Krankheit beeinflusst. Bei der Suche nach m¨oglichen Arthritistherapien sind die therapeutischen Ans¨atze gegen Angiogenese von großem Interesse. Um die ¨Anderungen der Knochendurchblutung bei M¨ausen mit rheumatoider Arthritis (RA) zu quantifizieren, wurde ein mehrstufiges Segmentierungsverfahren entwickelt. Dabei wurden die Blutgef¨aße im Bereich des entz¨undetes Kniegelenks segmentiert und anschließend quantitative 3D histomorphometrische Parameter berechnet. Zwei Gruppen von M¨ause (RA und WT) wurden in-vitro untersucht und die Ergebnisse miteinander verglichen.Angiogenesis is a key pathophysiological process in chronic inflammatory reactions, especially in arthritis, the progression and course of the disease influences. For quantification of changes of bone blood flow in mice with rheumatoid arthritis (RA)a multi-level segmentation method was developed. The blood vessels in the area of ​​inflamed knee joint were segmented and then quantitative 3D histomorphometric parameters were calculated. Two groups of mice (WT and RA) were investigated in vitro and the results compared to each other

Automatic Determination of Fiber-Length Distribution in Composite Material Using 3D CT Data

<p/> <p>Determining fiber length distribution in fiber reinforced polymer components is a crucial step in quality assurance, since fiber length has a strong influence on overall strength, stiffness, and stability of the material. The approximate fiber length distribution is usually determined early in the development process, as conventional methods require a destruction of the sample component. In this paper, a novel, automatic, and nondestructive approach for the determination of fiber length distribution in fiber reinforced polymers is presented. For this purpose, high-resolution computed tomography is used as imaging method together with subsequent image analysis for evaluation. The image analysis consists of an iterative process where single fibers are detected automatically in each iteration step after having applied image enhancement algorithms. Subsequently, a model-based approach is used together with a priori information in order to guide a fiber tracing and segmentation process. Thereby, the length of the segmented fibers can be calculated and a length distribution can be deduced. The performance and the robustness of the segmentation method is demonstrated by applying it to artificially generated test data and selected real components.</p

Automatic Determination of Fiber-Length Distribution in Composite Material Using 3D CT Data

Determining fiber length distribution in fiber reinforced polymer components is a crucial step in quality assurance, since fiber length has a strong influence on overall strength, stiffness, and stability of the material. The approximate fiber length distribution is usually determined early in the development process, as conventional methods require a destruction of the sample component. In this paper, a novel, automatic, and nondestructive approach for the determination of fiber length distribution in fiber reinforced polymers is presented. For this purpose, high-resolution computed tomography is used as imaging method together with subsequent image analysis for evaluation. The image analysis consists of an iterative process where single fibers are detected automatically in each iteration step after having applied image enhancement algorithms. Subsequently, a model-based approach is used together with a priori information in order to guide a fiber tracing and segmentation process. Thereby, the length of the segmented fibers can be calculated and a length distribution can be deduced. The performance and the robustness of the segmentation method is demonstrated by applying it to artificially generated test data and selected real components