CT substitute derived from MRI sequences with ultrashort echo time
A Johansson, M Karlsson, T Nyholm - Medical physics, 2011 - Wiley Online Library
Purpose: Methods for deriving computed tomography (CT) equivalent information from MRI
are needed for attenuation correction in PET/MRI applications, as well as for patient …
are needed for attenuation correction in PET/MRI applications, as well as for patient …
Continuous and simultaneous estimation of finger kinematics using inputs from an EMG-to-muscle activation model
Background Surface electromyography (EMG) signals are often used in many robot and
rehabilitation applications because these reflect motor intentions of users very well …
rehabilitation applications because these reflect motor intentions of users very well …
Textons, contours and regions: Cue integration in image segmentation
The paper makes two contributions: it provides (1) an operational definition of textons, the
putative elementary units of texture perception, and (2) an algorithm for partitioning the …
putative elementary units of texture perception, and (2) an algorithm for partitioning the …
Normalized cuts in 3-D for spinal MRI segmentation
J Carballido-Gamio, SJ Belongie… - IEEE transactions on …, 2004 - ieeexplore.ieee.org
Segmentation of medical images has become an indispensable process to perform
quantitative analysis of images of human organs and their functions. Normalized Cuts …
quantitative analysis of images of human organs and their functions. Normalized Cuts …
An affective computing approach to physiological emotion specificity: Toward subject‐independent and stimulus‐independent classification of film‐induced emotions
The hypothesis of physiological emotion specificity has been tested using pattern
classification analysis (PCA). To address limitations of prior research using PCA, we studied …
classification analysis (PCA). To address limitations of prior research using PCA, we studied …
Improving RBF networks performance in regression tasks by means of a supervised fuzzy clustering
Several fuzzy c-means based clustering techniques have been developed to tackle many
problems in a number of areas such as pattern recognition, image analysis, communication …
problems in a number of areas such as pattern recognition, image analysis, communication …
A probabilistic classifier for transformer dissolved gas analysis with a particle swarm optimizer
WH Tang, JY Goulermas, QH Wu… - IEEE transactions on …, 2008 - ieeexplore.ieee.org
This paper presents a Parzen-Windows (PW)-based classifier for transformer fault diagnosis,
which is able to interpret transformer dissolved gas analysis (DGA) with a probabilistic …
which is able to interpret transformer dissolved gas analysis (DGA) with a probabilistic …
Feature selection for MLP neural network: the use of random permutation of probabilistic outputs
This paper presents a new wrapper-based feature selection method for multilayer
perceptron (MLP) neural networks. It uses a feature ranking criterion to measure the …
perceptron (MLP) neural networks. It uses a feature ranking criterion to measure the …
Estimating intrinsic component images using non-linear regression
MF Tappen, EH Adelson… - 2006 IEEE Computer …, 2006 - ieeexplore.ieee.org
Images can be represented as the composition of multiple intrinsic component images, such
as shading, albedo, and noise images. In this paper, we present a method for estimating …
as shading, albedo, and noise images. In this paper, we present a method for estimating …
Prediction of landing gear loads using machine learning techniques
G Holmes, P Sartor, S Reed… - Structural Health …, 2016 - journals.sagepub.com
This article investigates the feasibility of using machine learning algorithms to predict the
loads experienced by a landing gear during landing. For this purpose, the results on drop …
loads experienced by a landing gear during landing. For this purpose, the results on drop …