کد مقاله کد نشریه سال انتشار مقاله انگلیسی نسخه تمام متن
5513782 1541272 2017 12 صفحه PDF دانلود رایگان
عنوان انگلیسی مقاله ISI
Computer-aided quantification of microvascular networks: Application to alterations due to pathological angiogenesis in the hamster
ترجمه فارسی عنوان
اندازه گیری های کامپیوتری از شبکه های میکروسکوپیک: کاربرد در تغییرات ناشی از آنژیوژنز پاتولوژیک در هامستر
موضوعات مرتبط
علوم زیستی و بیوفناوری بیوشیمی، ژنتیک و زیست شناسی مولکولی زیست شیمی
چکیده انگلیسی


- An automatic image processing pipeline to analyze intravital-microscopy fluoroscopy images of the hamster cheek pouch is presented, called PN-method. Comparisons with an intensity-threshold based method are performed.
- Several image-based quantification indexes are used to characterize microvascular alterations.
- The PN-method renders an accurate and robust segmentation of blood vessels for different microvascular scenarios, normal and pathological.
- Images with angiogenesis can be differentiated from controls using a set of quantification indexes.
- All segmentation-independent indexes (RFU, H, AvF) presented potentiality for identification of normal and neo-vascularized microvasculature.

Angiogenesis is both a physiological and a pathological process of great complexity, which is difficult to measure objectively and automatically. The hamster cheek pouch (HCP) prepared for intravital-microscopy (IVM) has been used to characterize microvascular functions in many studies and was chosen to investigate microvascular characteristics observed in normal non-infected hamsters as compared to those HCPs parasitized by Trypanosoma cruzi. Images of HCPs captured at IVM were subjected to computer based measurements of angiogenesis and histamine-induced macromolecular (FITC-dextran) leakage with an image segmentation approach that has the capacity to discriminate between fluorescence emitted by macromolecular tracers inside the vasculature and in the extravascular space. We present such an automatic segmentation methodology using known tools from image processing field that, to our knowledge, have not been tested in IVM images. We have compared this methodology with a recently published segmentation strategy based on image intensity thresholding. Our method renders an accurate and robust segmentation of blood vessels for different microvascular scenarios, normal and pathological. Application of the proposed strategy for objective and automatic measurement of angiogenesis detection was explored in detail.

ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Microvascular Research - Volume 112, July 2017, Pages 53-64
نویسندگان
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