Search results for "image processing"
showing 10 items of 3285 documents
STN area detection using K-NN classifiers for MER recordings in Parkinson patients during neurostimulator implant surgery
2016
Deep Brain Stimulation (DBS) applies electric pulses into the subthalamic nucleus (STN) improving tremor and other symptoms associated to Parkinson's disease. Accurate STN detection for proper location and implant of the stimulating electrodes is a complex task and surgeons are not always certain about final location. Signals from the STN acquired during DBS surgery are obtained with microelectrodes, having specific characteristics differing from other brain areas. Using supervised learning, a trained model based on previous microelectrode recordings (MER) can be obtained, being able to successfully classify the STN area for new MER signals. The K Nearest Neighbours (K-NN) algorithm has bee…
From medical data to simple virtual mock-up of scapulo-humeral joint
2008
The surgical operations of shoulder joint are guided by various principles: osteosynthesis in the case of fracture, osteotomy in order to correct a deformation or to modify the functioning of the joint, or implementation of articular prosthesis. At the end of the twentieth century, many innovations in the domains of biomechanics and orthopedic surgery have been performed. Nevertheless, theoretical and practical problems may appear during the operation (visual field of surgeon is very limited, quality and shape of the bone is variable depending on the patient). Biomechanical criteria of success are defined for each intervention. For example, the installation with success of prosthetic implan…
An Efficient Algorithm for Helly Property Recognition in a Linear Hypergraph
2001
International audience; In this article we characterize bipartite graphs whose associated neighborhood hypergraphs have the Helly property. We examine incidence graphs both hypergraphs and linear hypergraphs and we give a polynomial algorithm to recognize if a linear hypergraph has the Helly property.
Hypergraph imaging: an overview
2002
Hypergraph theory as originally developed by Berge (Hypergraphe, Dunod, Paris, 1987) is a theory of finite combinatorial sets, modeling lot of problems of operational research and combinatorial optimization. This framework turns out to be very interesting for many other applications, in particular for computer vision. In this paper, we are going to survey the relationship between combinatorial sets and image processing. More precisely, we propose an overview of different applications from image hypergraph models to image analysis. It mainly focuses on the combinatorial representation of an image and shows the effectiveness of this approach to low level image processing; in particular to seg…
Social Influence Maximization in Hypergraphs
2021
This work deals with a generalization of the minimum Target Set Selection (TSS) problem, a key algorithmic question in information diffusion research due to its potential commercial value. Firstly proposed by Kempe et al., the TSS problem is based on a linear threshold diffusion model defined on an input graph with node thresholds, quantifying the hardness to influence each node. The goal is to find the smaller set of items that can influence the whole network according to the diffusion model defined. This study generalizes the TSS problem on networks characterized by many-to-many relationships modeled via hypergraphs. Specifically, we introduce a linear threshold diffusion process on such …
Online Hyperparameter Search Interleaved with Proximal Parameter Updates
2021
There is a clear need for efficient hyperparameter optimization (HO) algorithms for statistical learning, since commonly applied search methods (such as grid search with N-fold cross-validation) are inefficient and/or approximate. Previously existing gradient-based HO algorithms that rely on the smoothness of the cost function cannot be applied in problems such as Lasso regression. In this contribution, we develop a HO method that relies on the structure of proximal gradient methods and does not require a smooth cost function. Such a method is applied to Leave-one-out (LOO)-validated Lasso and Group Lasso, and an online variant is proposed. Numerical experiments corroborate the convergence …
Passive millimeter wave image classification with large scale Gaussian processes
2017
Passive Millimeter Wave Images (PMMWIs) are being increasingly used to identify and localize objects concealed under clothing. Taking into account the quality of these images and the unknown position, shape, and size of the hidden objects, large data sets are required to build successful classification/detection systems. Kernel methods, in particular Gaussian Processes (GPs), are sound, flexible, and popular techniques to address supervised learning problems. Unfortunately, their computational cost is known to be prohibitive for large scale applications. In this work, we present a novel approach to PMMWI classification based on the use of Gaussian Processes for large data sets. The proposed…
Hyperspectral Texture Metrology Based on Joint Probability of Spectral and Spatial Distribution
2021
International audience; Texture characterization from the metrological point of view is addressed in order to establish a physically relevant and directly interpretable feature. In this regard, a generic formulation is proposed to simultaneously capture the spectral and spatial complexity in hyperspectral images. The feature, named relative spectral difference occurrence matrix (RSDOM) is thus constructed in a multireference, multidirectional, and multiscale context. As validation, its performance is assessed in three versatile tasks. In texture classification on HyTexiLa, content-based image retrieval (CBIR) on ICONES-HSI, and land cover classification on Salinas, RSDOM registers 98.5% acc…
Quantitative image analysis of the chromatolysis in rat facial and hypoglossal motoneurons following axotomy with and without reinnervation.
1996
Image analysis was used to quantify the time course of chromatolysis in regenerating and degenerating motoneurons. Following facial-facial, hypoglossal-hypoglossal nerve suture, or resection of facial and hypoglossal nerves with postoperative survival times of 4 h to 112 days, the texture of the Nissl substance of facial and hypoglossal motoneurons was analyzed on both sides of the brainstem in paraffin serial sections with a VIDASplus image analyzer. In this quantitative study of 149 Wistar rats, alterations of the Nissl substance were measured that were statistically significant but not yet visible to the human eye. Chromatolysis started significantly as early as 8 h and was not fully rev…
The use of texture analysis to study the time course of chromatolysis
1998
Image analysis of the textural feature entropy of the Nissl substance was used to monitor the time course of chromatolysis in regenerating hypoglossal motoneurons and degenerating facial motoneurons 4-112 days after hypoglossal-facial anastomosis in rats. Changes in the Nissl substance were detected that were not obvious on the basis of subjective judgement of the light-microscopical appearance of the neurons. Chromatolysis started 4 days post operation (dpo) and was not reversed at 112 dpo in both nuclei. The increase of chromatolysis was 14-28 dpo faster in the regenerating hypoglossal neurons than in degenerating facial neurons. Maximal chromatolysis was measured at 56-70 dpo in both nuc…