A call for uniform reporting standards in studies assessing endovascular treatment for chronic ischaemia of lower limb arteries

Endovascular therapy is a rapidly evolving field for the treatment of patients with peripheral arterial disease, and a magnitude of studies reporting on various modern revascularization concepts have been recently published. Thus, studies assessing the efficacy of endovascular therapy of peripheral arteries do not operate with uniformly defined endpoints, rendering a direct comparison of studies difficult. The purpose of this consensus statement is to highlight differences in the terminology used in the current literature and to propose some standardized criteria that must be considered when reporting results of endovascular revascularization for chronic ischaemia of lower limb arteries.

Applied Graph Theory in Computer Vision and Pattern Recognition

This book will serve as a foundation for a variety of useful applications of graph theory to computer vision, pattern recognition, and related areas. It covers a representative set of novel graph-theoretic methods for complex computer vision and pattern recognition tasks. The first part of the book presents the application of graph theory to low-level processing of digital images such as a new method for partitioning a given image into a hierarchy of homogeneous areas using graph pyramids, or a study of the relationship between graph theory and digital topology. Part II presents graph-theoretic learning algorithms for high-level computer vision and pattern recognition applications, including a survey of graph based methodologies for pattern recognition and computer vision, a presentation of a series of computationally efficient algorithms for testing graph isomorphism and related graph matching tasks in pattern recognition and a new graph distance measure to be used for solving graph matching problems. Finally, Part III provides detailed descriptions of several applications of graph-based methods to real-world pattern recognition tasks. It includes a critical review of the main graph-based and structural methods for fingerprint classification, a new method to visualize time series of graphs, and potential applications in computer network monitoring and abnormal event detection.