Search results for "Image"
showing 10 items of 6818 documents
Deep Learning-Based Methods for Prostate Segmentation in Magnetic Resonance Imaging
2021
Magnetic Resonance Imaging-based prostate segmentation is an essential task for adaptive radiotherapy and for radiomics studies whose purpose is to identify associations between imaging features and patient outcomes. Because manual delineation is a time-consuming task, we present three deep-learning (DL) approaches, namely UNet, efficient neural network (ENet), and efficient residual factorized convNet (ERFNet), whose aim is to tackle the fully-automated, real-time, and 3D delineation process of the prostate gland on T2-weighted MRI. While UNet is used in many biomedical image delineation applications, ENet and ERFNet are mainly applied in self-driving cars to compensate for limited hardwar…
GPU-accelerated integral imaging and full-parallax 3D display using stereo-plenoptic camera system
2019
Abstract In this paper, we propose a novel approach to produce integral images ready to be displayed onto an integral-imaging monitor. Our main contribution is the use of commercial plenoptic camera, which is arranged in a stereo configuration. Our proposed set-up is able to record the radiance, spatial and angular, information simultaneously in each different stereo position. We illustrate our contribution by composing the point cloud from a pair of captured plenoptic images, and generate an integral image from the properly registered 3D information. We have exploited the graphics processing unit (GPU) acceleration in order to enhance the integral-image computation speed and efficiency. We…
Group Nonnegative Matrix Factorization with Sparse Regularization in Multi-set Data
2021
Constrained joint analysis of data from multiple sources has received widespread attention for that it allows us to explore potential connections and extract meaningful hidden components. In this paper, we formulate a flexible joint source separation model termed as group nonnegative matrix factorization with sparse regularization (GNMF-SR), which aims to jointly analyze the partially coupled multi-set data. In the GNMF-SR model, common and individual patterns of particular underlying factors can be extracted simultaneously with imposing nonnegative constraint and sparse penalty. Alternating optimization and alternating direction method of multipliers (ADMM) are combined to solve the GNMF-S…
The cone of gaze
2011
Gaze direction is an important cue that regulates social interactions. Although humans are very accurate in determining gaze directions in general, they have a surprisingly liberal criterion for the presence of mutual gaze. We first established a psychophysical task to measure the cone of gaze, which required observers to adjust the eyes of a virtual head to the margins of the area of mutual gaze. Then we examined differences between 2D, 3D, and genuine real life gaze. Finally, the tolerance for image distortions when the virtual head is not viewed from the proper vantage point was investigated. Gaze direction was remarkably robust toward loss in detail and distortion. Important lessons for…
Semi-automated evaluation tool for retinal vasculopathy.
2009
The ocular fundus is the only area of human body where vascular system is visible using relatively simple instrumentation. Furthermore, there is medical suggestive evidence of a direct relationship between certain measures of vascular characteristics in the ocular fundus (arteriolar and venular calibers and focal arteriolar narrowing) and cardiovascular diseases. In order to establish such relationship on sound statistical basis a method must be provided to measure the needed values in an easy, yet precise and repeatable way. This paper presents a system to assist physicians in signaling and storing the data associated to signs of vascular deterioration and vascular calibers in non-mydriati…
Bias artifact suppression on MR volumes.
2007
RF-Inhomogeneity correction is a relevant research topic in the field of Magnetic Resonance Imaging (MRI). A volume corrupted by this artifact exhibits nonuni- form illumination both inside a single slice and between adjacent ones. In this work a bias correction technique is presented, which suppresses this artifact on MR vol- umes scanned from different body parts without any a-priori hypothesis on the artifact model. Theoretical foundations of the method are reported together with experimental results and a comparison is presented with both the 2D version of the algorithm and other techniques that are widely used in MRI literature.
Automatic left ventricle volume calculation with explainability through a deep learning weak-supervision methodology
2021
[EN] Background and objective: Magnetic resonance imaging is the most reliable imaging technique to assess the heart. More specifically there is great importance in the analysis of the left ventricle, as the main pathologies directly affect this region. In order to characterize the left ventricle, it is necessary to extract its volume. In this work we present a neural network architecture that is capable of directly estimating the left ventricle volume in short axis cine Magnetic Resonance Imaging in the end-diastolic frame and provide a segmentation of the region which is the basis of the volume calculation, thus offering explain-ability to the estimated value. Methods: The network was des…
A Novel Marking Reader for Progressive Addition Lenses Based on Gabor Holography
2016
PURPOSE Progressive addition lenses (PALs) are marked with permanent engraved marks (PEMs) at standardized locations. Permanent engraved marks are very useful through the manufacturing and mounting processes, act as locator marks to re-ink the removable marks, and contain useful information about the PAL. However, PEMs are often faint and weak, obscured by scratches, partially occluded, and difficult to recognize on tinted lenses or with antireflection or scratch-resistant coatings. The aim of this article is to present a new generation of portable marking reader based on an extremely simplified concept for visualization and identification of PEMs in PALs. METHODS Permanent engraved marks o…
A framework for modelling the biomechanical behaviour of the human liver during breathing in real time using machine learning
2017
Progress in biomechanical modelling of human soft tissue is the basis for the development of new clinical applications capable of improving the diagnosis and treatment of some diseases (e.g. cancer), as well as the surgical planning and guidance of some interventions. The finite element method (FEM) is one of the most popular techniques used to predict the deformation of the human soft tissue due to its high accuracy. However, FEM has an associated high computational cost, which makes it difficult its integration in real-time computer-aided surgery systems. An alternative for simulating the mechanical behaviour of human organs in real time comes from the use of machine learning (ML) techniq…
Unsupervised image processing scheme for transistor photon emission analysis in order to identify defect location
2015
International audience; The study of the light emitted by transistors in a highly scaled complementary metal oxide semiconductor (CMOS) integrated circuit (IC) has become a key method with which to analyze faulty devices, track the failure root cause, and have candidate locations for where to start the physical analysis. The localization of defective areas in IC corresponds to a reliability check and gives information to the designer to improve the IC design. The scaling of CMOS leads to an increase in the number of active nodes inside the acquisition area. There are also more differences between the spot’s intensities. In order to improve the identification of all of the photon emission sp…