In this paper we present a fully automatic and accurate segmentation framework for 2D tagged cardiac MR images. This scheme consists of three learning methods: a) an active shape model is implemented to model the heart shape variations, b) an Adaboost learning method is applied to learn confidence-rated boundary criterions from the local appearance features at each landmark point on the shape m...

A stratigraphically oriented series of the Miocene foraminiferal species Brizalina mandoroveensis from Ikang, Cameroon, was analyzed both by conventional multivariate morphometric procedures and by the tensor biometric method of Bookstein (1986; Statist. Sci. 1,181-142), a method which analyzes sets of landmark points rather than specific variables of shape or size. The conventional analysis us...

We use tools from geometric statistics to analyze the usual estimation procedure of a template shape. This applies to shapes from landmarks, curves, surfaces, images etc. We demonstrate the asymptotic bias of the template shape estimation using the stratified geometry of the shape space. We give a Taylor expansion of the bias with respect to a parameter σ describing the measurement error on the...

conclusions the us-guided method for cvc placement was superior to the traditional landmark method in terms of access time, number of attempts, success rate, and fewer complications. objectives this study aimed to compare the traditional landmark method vs. us-guided method of cvc placement in terms of complications and success rate. patients and methods in this randomized controlled trial, pat...

Two experiments investigated how people develop different landmark knowledge at decision points. Participants learned a route in a virtual city once or five times. One distinctive landmark was placed at each intersection of the route. At test, participants were released at each intersection according to the learning order and were required to determine the turning direction. At each intersectio...

This paper presents a novel fuzzy-symbolic approach for the recognition of two-dimensional shapes. The proposed method represents a binary shape using symbolic (multi interval valued) features. The representation scheme is based on the landmark points (dominant points) of the shape and the concept of fuzzy equilateral triangle membership function. A similarity measure to estimate the degree of ...

Maximally Collapsing Metric Learning is a recently proposed algorithm to estimate a metric matrix from labelled data. The purpose of this work is to extend this approach by considering a set of landmark points which can in principle reduce the cost per iteration in one order of magnitude. The proposal is in fact a generalized version of the original algorithm that can be applied to larger amoun...

An automatic method for the selection of subsets of images, both modern and historic, out of a set of landmark large images collected from the Internet is presented in this paper. This selection depends on the extraction of dominant features using Gabor filtering. Features are selected carefully from a preliminary image set and fed into a neural network as a training data. The method collects a...