Discriminative Cue Integration for Medical Image Annotation

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In a recent paper Kirtley and Milroy [D. Kirtley, R. Milroy, J. of Fusion Energy (2023) 42:30] discuss the Helion concept for a pulsed reactor, in which two supersonic field-reversed configurations (FRCs) merge and the resulting plasmoid is adiabatically compressed to fusion conditions. Using D-He3 as fuel this would allow for efficient electromagnetic energy conversion during the subsequent expansion phase. Essential for their very promising projections of energy gain is the assumed large temperature ratio

At the intersection of computational imaging and biomedical optics, this thesis applies physics-based modeling and computational methods to solve inverse problems in optical imaging. We focus on three representative imaging modalities where we push the limits of imaging depth and spatial resolution: optical projection tomography (OPT); photoacoustic imaging (PAI); and single-molecule localization microscopy (SMLM). OPT and PAI overcome the diffusion limit to enable greater imaging depths, while SMLM breaks

Computational imaging combines innovative camera designs with physics-informed algorithms to enable new sensing capabilities, modalities, and applications. Such cameras can relax optical design constraints and enable encoding of higher-dimensional data. Mask-based lensless cameras are one such design, which replaces the focusing lens with a thin mask, and image formation is shifted from the optics to digital post-processing. Classical methods recover images by solving optimization problems involving data fi

Realistic body images (avatars) have been long utilized in virtual reality applications, and they are becoming increasingly used in Neuroscience and Neuroprosthetics fields. To elucidate monkeys' perception of avatars, we have measured reaction of two naive rhesus monkeys when confronted to realistic 3D monkey avatars with different facial expressions and different levels of realism. We have compared it with their reaction to images of real monkeys with similar facial expressions. Monkeys were initially ove

We present a novel framework for automatically determining whether or not to apply black point compensation (BPC) in image reproduction. Visually salient objects have a larger influence on determining image quality than the number of dark pixels in an image, and thus should drive the use of BPC. We propose a simple and efficient algorithmic implementation to determine when to apply BPC based on low-level saliency estimation. We evaluate our algorithm with a psychophysical experiment on an image data set pri

In this paper, we present a fast method to detect humans from videos captured in surveillance applications. It is based on a cascade of LogitBoost classifiers relying on features mapped from the Riemanian manifold of region covariance matrices computed from input image features. The method was extended in several ways. First, as the mapping process is slow for high dimensional input image feature space, we propose to select weak classifiers based on subsets of the complete image feature space, corresponding

This paper presents a fingerprinting method based on equivalence classes. An equivalence class is composed of a reference image and all its variations (or replicas). For each reference image, a decision function is built. The latter determines if a given image belongs to its corresponding equivalence class. This function is built in three steps: synthesis, projection, and analysis. In the first step, the reference image is replicated using different image operators (like JPEG compression, average filtering,

We propose a deep study on tissue modelization and classification techniques on T1-weighted MR images. Six approaches have been taken into account to perform this validation study. We consider first the Finite Gaussian Mixture model (A-FGMM) and a Bayes classification. Second method is the same as A-FGMM but introducing a Hidden Markov Random Field (HMRF) model to encode spatial information and classification is then performed by Maximum a Posteriori (MAP). Third, we study a method that models mixture tissu

Shadows are integral parts of natural scenes and one of the elements contributing to naturalness of synthetic scenes. In many image analysis and interpretation applications, shadows interfere with fundamental tasks such as object extraction and description. For this reason, shadow segmentation is an important step in image analysis. In this paper, we propose a new cast shadow segmentation algorithm for both still and moving images. The proposed technique exploits spectral and geometrical properties of shado

We present applications of a recently developed method, the singular value decomposition inversion (SVD-I), for inverting line integrated multichannel interferometer measurements in fusion devices. The method expands the local electron density profiles into a limited series of orthogonal basis functions formed from the singular value decomposition of Thomson scattering measurements, which are obtained at much lower frequencies than the interferometer data. Because these basis functions are formed from a loc

Humans have the ability to learn. Having seen an object we can recognise it later. We can do this because our nervous system uses an efficient and robust visual processing and capabilities to learn from sensory input. On the other hand, designing algorithms to learn from visual data is a difficult task. More than fifty years ago, Rosenblatt proposed the perceptron algorithm. The perceptron learns from data examples a linear separation, which categorises the data in two classes. The algorithm served as a sim

Text characters embedded in images and video sequences represents a rich source of information for content-based indexing and retrieval applications. However, these text characters are difficult to be detected and recognized due to their various sizes, grayscale values and complex backgrounds. This thesis investigates methods for building an efficient application system for detecting and recognizing text of any grayscale values embedded in images and video sequences. Both empirical image processing methods

Splines, which were invented by Schoenberg more than fifty years ago, constitute an elegant framework for dealing with interpolation and discretization problems. They are widely used in computer-aided design and computer graphics, but have been neglected in medical imaging applications, mostly as a consequence of what one may call the "bad press" phenomenon. Thanks to some recent research efforts in signal processing and wavelet-related techniques, the virtues of splines have been revived in our community.

Nowadays, the ability to create panoramic photographs is included with most of the commercial digital cameras. The principle is to shoot several pictures and stitch them together to build a panorama. To ensure the quality of the final image, the different pictures have to be perfectly aligned and the colors of the images should match. While the alignment of images has received a lot of attention from the computer vision community, the mismatch in colors was often ignored and handled using smooth transitions

Compact optimized stellarators offer novel solutions for confining high-beta plasmas and developing magnetic confinement fusion. The three-dimensional plasma shape can be designed to enhance the magnetohydrodynamic (MHD) stability without feedback or nearby conducting structures and provide drift-orbit confinement similar to tokamaks. These configurations offer the possibility of combining the steady-state low-recirculating power, external control, and disruption resilience of previous stellarators with the

The method of wavelet thresholding for removing noise, or denoising, has been researched extensively due to its effectiveness and simplicity. Much of the literature has focused on developing the best uniform threshold or best basis selection. However, not much has been done to make the threshold values adaptive to the spatially changing statistics of images. Such adap- tivity can improve the wavelet thresholding performance because it allows additional local information of the image (such as the identificat

The prediction of the thermal energy confinement time, tau(th), for ITER size experiments is based on power law scalings obtained using data sets of present tokamak results in specific regimes, the most relevant being the ELMy H mode regime. A thorough statistical approach has provided a bust fit to these data with an estimation of the error bars which forms the basis for the ITER EDA design parameters. In this article the range of variation of the main parameters in the database are studied individually an

Within the range of plasma shapes and plasma currents investigated, the electron confinement time, tau_Ee, increases with safety factor, density and negative triangularity similar to the Ohmic heating case. There is little dependence of tau_Ee on the heating location provided power deposition occurs inside the q=1 surface; as power deposition moves out of the inversion surface, tau_Ee decreases. The power-induced energy confinement degradation exponent (tau_Ee~PaP) is as usual: alpha_P ~-0.5. As a general t

Within the range of plasma shapes and plasma currents investigated, the electron confinement time, Tau_E increases with density, elongation and negative triangularity (-0.4

Due to its pulsed operation mode, a fusion device will have to sustain thermal stresses and at the same time be exposed to a flux of 14 MeV neutrons. In order to simulate this irradiation condition, a new irradiation device has been developed, in which the specimen can be stress and strain-controlled during the irradiation. For the simulation of the fusion neutrons, a 590 MeV proton beam is used. This type of particle produces from spallation reactions the displacement damage and the helium typical of fusio

Discriminative Cue Integration for Medical Image Annotation

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Social interaction probed by reaching to face images: Rhesus monkeys consider a textured monkey avatar as a conspecific.

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Identification of Image Variations based on Equivalence Classes

Validation of Tissue Modelization and Classification Techniques in T1-weighted MR Brain Images

Cast shadow segmentation using invariant colour features

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