Shape-driven segmentation of the arterial wall in intravascular ultrasound images

Segmentation of arterial wall boundaries from intravascular images is an important problem for many applications in the study of plaque characteristics, mechanical properties of the arterial wall, its 3D reconstruction, and its measurements such as lumen size, lumen radius, and wall radius. We present a shape-driven approach to segmentation of the arterial wall from intravascular ultrasound images in the rectangular domain. In a properly built shape space using training data, we constrain the lumen and media-adventitia contours to a smooth, closed geometry, which increases the segmentation quality without any tradeoff with a regularizer term. In addition to a shape prior, we utilize an intensity prior through a non-parametric probability density based image energy, with global image measurements rather than pointwise measurements used in previous methods. Furthermore, a detection step is included to address the challenges introduced to the segmentation process by side branches and calcifications. All these features greatly enhance our segmentation method. The tests of our algorithm on a large dataset demonstrate the effectiveness of our approach

Shape-driven segmentation of the arterial wall in intravascular ultrasound images

Segmentation of arterial wall boundaries from intravascular images is an important problem for many applications in the study of plaque characteristics, mechanical properties of the arterial wall, its 3D reconstruction, and its measurements such as lumen size, lumen radius, and wall radius. We present a shape-driven approach to segmentation of the arterial wall from intravascular ultrasound images in the rectangular domain. In a properly built shape space using training data, we constrain the lumen and media-adventitia contours to a smooth, closed geometry, which increases the segmentation quality without any tradeoff with a regularizer term. In addition to a shape prior, we utilize an intensity prior through a non-parametric probability density based image energy, with global image measurements rather than pointwise measurements used in previous methods. Furthermore, a detection step is included to address the challenges introduced to the segmentation process by side branches and calcifications. All these features greatly enhance our segmentation method. The tests of our algorithm on a large dataset demonstrate the effectiveness of our approach

Saving regret

We define saving regret as the wish in hindsight to have saved more earlier in life. We measured saving regret and possible determinants in a survey of a probability sample of those aged 60-79. We investigate two main causes of saving regret: procrastination along with other psychological traits, and the role of shocks, both positive and negative. We find high levels of saving regret but relatively little of the variation is explained by procrastination and psychological factors. Shocks such as unemployment, health and divorce explain much more of the variation. The results have important implications for retirement saving policies

Saving regret

We define saving regret as the wish in hindsight to have saved more earlier in life. We measured saving regret and possible determinants in a survey of a probability sample of those aged 60-79. We investigate two main causes of saving regret: procrastination along with other psychological traits, and the role of shocks, both positive and negative. We find high levels of saving regret but relatively little of the variation is explained by procrastination and psychological factors. Shocks such as unemployment, health and divorce explain much more of the variation. The results have important implications for retirement saving policies

Clathrin-adaptor ratio and membrane tension regulate the flat-to-curved transition of the clathrin coat during endocytosis

Dataset used in 'Clathrin-adaptor ratio and membrane tension regulate the flat-to-curved transition of the clathrin coat during endocytosis'<br