Abstract：
:The detection and assessment of intravascular filling defects is important, because they may represent a process central to cerebral malaria pathogenesis: neurovascular sequestration. We have developed and validated a framework that can automatically detect intravascular filling defects in fluorescein angiogram images. It first employs a state-of-the-art segmentation approach to extract the vessels from images and then divide them into individual segments by geometrical analysis. A feature vector based on the intensity and shape of saliency maps is generated to represent the level of abnormality of each vessel segment. An AdaBoost classifier with weighted cost coefficient is trained to classify the vessel segments into normal and abnormal categories. To demonstrate its effectiveness, we apply this framework to 6,358 vessel segments in images from 10 patients with malarial retinopathy. The test sensitivity, specificity, accuracy, and area under curve (AUC) are 74.7%, 73.5%, 74.1% and 74.2% respectively when compared to the reference standard of human expert manual annotations. This performance is comparable to the agreement that we find between human observers of intravascular filling defects. Our method will be a powerful new tool for studying malarial retinopathy.
journal_name
Sci Repjournal_title
Scientific reportsauthors
Zhao Y,MacCormick IJ,Parry DG,Beare NA,Harding SP,Zheng Ydoi
10.1038/srep11154subject
Has Abstractpub_date
2015-06-08 00:00:00pages
11154issn
2045-2322pii
srep11154journal_volume
5pub_type
杂志文章abstract：:Hematopoietic stem/progenitor cells (HSPC) in zebrafish emerge from the aortic hemogenic endothelium (HE) and migrate towards the caudal hematopoietic tissue (CHT), where they expand and differentiate during definitive hematopoiesis. Phospholipase C gamma 1 (Plcγ1) has been implicated for hematopoiesis in vivo and in ...
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journal_title：Scientific reports
pub_type： 杂志文章
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journal_title：Scientific reports
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pub_type： 已发布勘误
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