Automatic Segmentation and Tracking of Thrombus Formation within In Vitro Microscopic Video Sequences

In vitro experiments on human blood samples are crucial to assess correlation between thrombus disorders and genetic variance. A blood flow is drained through collagen fibers resulting in a progressive aggregation of platelets. This paper proposes a method of segmentation of thrombi during such acquisitions. Three complementary gradient-based features are introduced and included in a regularized machine learning framework. A novel tracking method of thrombi as deformable growing objects under split and merge conditions is also introduced.     «

In vitro experiments on human blood samples are crucial to assess correlation between thrombus disorders and genetic variance. A blood flow is drained through collagen fibers resulting in a progressive aggregation of platelets. This paper proposes a method of segmentation of thrombi during such acquisitions. Three complementary gradient-based features are introduced and included in a regularized machine learning framework. A novel tracking method of thrombi as deformable growing objects under sp...     »