nils-herrmann/clean_scirepeval huggingface dataset:
Atlas-based segmentation of white matter structures from DTI using tensor invariants and orientation

This paper presents a novel method for the segmentation of anatomical structures in the white matter from DTI (Diffusion Tensor Imaging) data. Our approach is based on: (a) the use of a DTI white matter atlas to guide the segmentation process, (b) the use of tensor invariants and the orientation information of the tensor as features, and (c) a statistical modeling of the data with a level set implementation. This formulation allows for controlling the relative importance of the different properties of the diffusion tensor and uses the anatomical information of the atlas to constrain the segmentation. The method has been applied to the segmentation of DTI volumes, and results show it constitutes a valid alternative to other approaches such as VBM or TBSS for white matter analysis.
Multiresolution compression schemes for medical image and volume data

In this paper we propose a multiresolution compression scheme applied to image and volume data. It is intended for rapid browsing in graphical files, in which some regions of interest may exist; therefore the compression algorithms focus on incorporating quick full-reconstruction procedures, both in images and volumes. This scheme is based on vector quantization of the coefficients of a wavelet decomposition. The differences in the methods lie on how vectors in the multiresolution decompositions are selected for vector quantization. We have also developed a client-server application using this scheme, which allows images with increasing levels of detail to be represented in the client system as they are received from the server and decoded. Numerical results show the performances of all the selections made.
A new proposal for 3D fiber tracking in synthetic diffusion tensor magnetic resonance images

In this paper a new fiber tracking algorithm to be used with diffusion tensor fields acquired via magnetic resonance imaging is developed. The research effort in tracking fibers of nervous cells in the human brain affords many benefits to the medical community. The proposed method is an improvement over a previously developed algorithm that uses both geometrical and probabilistic criteria. The new scheme offers better results in regions with branching and crossing fibers, showing better computational and robustness properties. Like its predecessor, it also offers the capability of reporting an uncertainty value for the computed tracts.
A fully automatic algorithm for contour detection of bones in hand radiographs using active contours

This paper presents an algorithm for automatically detecting bone contours from hand radiographs using active contours. Prior knowledge is first used to locate initial contours for the snakes inside each bone of interest. Next, an adaptive snake algorithm is applied so that parameters are properly adjusted for each bone specifically. We introduce a novel truncation technique to prevent the external forces of the snake from pulling the contour outside the bones boundaries, yielding excellent results.
Anomaly Detection in Network Traffic Based on Statistical Inference and \alpha-Stable Modeling

This paper proposes a novel method to detect anomalies in network traffic, based on a nonrestricted α-stable first-order model and statistical hypothesis testing. To this end, we give statistical evidence that the marginal distribution of real traffic is adequately modeled with α-stable functions and classify traffic patterns by means of a Generalized Likelihood Ratio Test (GLRT). The method automatically chooses traffic windows used as a reference, which the traffic window under test is compared with, with no expert intervention needed to that end. We focus on detecting two anomaly types, namely floods and flash-crowds, which have been frequently studied in the literature. Performance of our detection method has been measured through Receiver Operating Characteristic (ROC) curves and results indicate that our method outperforms the closely-related state-of-the-art contribution described in. All experiments use traffic data collected from two routers at our university-a 25,000 students institution-which provide two different levels of traffic aggregation for our tests (traffic at a particular school and the whole university). In addition, the traffic model is tested with publicly available traffic traces. Due to the complexity of α-stable distributions, care has been taken in designing appropriate numerical algorithms to deal with the model.
Neural posterior probabilities for microcalcification detection in breast cancer diagnoses

We apply the a Posteriori Probability Model Selection (PPMS) algorithm with the help of Generalized Softmax Perceptron (GSP) neural architecture in order to obtain estimates of the posterior class probabilities at its outputs, in the binary problem of microcalcification detection in a hospital digitalized mammogram database. We first detect windowed images with high probability to belong to the class microcalcification is present, then we locally segment the shape of the calcifications, and finally show the segmented microcalcifications to the radiologist. The segmented images together with the posterior probabilities for each window image can be employed as a valuable information to help predicting a breast diagnosis, in order to distinguish between benignant calcium deposit and malignant accumulation, that is, breast carcinoma.
Stochastic Modeling of the PPG Signal: A Synthesis-by-Analysis Approach With Applications

In this paper, we propose a stochastic model of photoplethysmographic signals that is able to synthesize an arbitrary number of other statistically equivalent signals to the one under analysis. To that end, we first preprocess the pulse signal to normalize and time-align pulses. In a second stage, we design a single-pulse model, which consists of ten parameters. In the third stage, the time evolution of this ten-parameter vector is approximated by means of two autoregressive moving average models, one for the trend and one for the residue; this model is applied after a decorrelation step which let us to process each vector component in parallel. The experiments carried out show that the model we here propose is able to maintain the main features of the original signal; this is accomplished by means of both a linear spectral analysis and also by comparing two measures obtained from a nonlinear analysis. Finally, we explore the capability of the model to: 1) track physical activity; 2) obtain statistics of clinical parameters by model sampling; and 3) recover corrupted or missing signal epochs by synthesis.
Time-domain design of linear-phase PR filter banks

We present a novel way to design biorthogonal and paraunitary linear phase (LPPUFB) filter banks. The square error of the perfect reconstruction condition is expressed in a quadratic form of filter coefficients and the cost function is minimized by solving the linear equation iteratively without nonlinear optimization. With some modifications, the method can be extended to the design of paraunitary filter banks. Using this method, we can design LPPUFB with many channels easily and quickly. Design examples are given to validate the proposed method.
Robust filtering for uncertain nonlinearly parameterized plants

We address the robust filtering problem for a wide class of systems whose state-space data assume a very general nonlinear dependence in the uncertain parameters. Our resolution methods rely on new linear matrix inequality characterizations of /spl Hscr//sub 2/ and /spl Hscr//sub /spl infin// performances, which, in conjunction with suitable linearization transformations of the variables, give rise to practical and computationally tractable formulations for the robust filtering problem.
Resource Allocation for TDMA Video Commtmmunication Over AWGN Using Cross-Layer Optimization Approach

Cross-layer optimization approach is applied to allocate channel times of time-division multiple access (TDMA) to utility functions which send different video streams with different rate-distortion characteristics. Given a channel time, each utility function solves an optimization problem to obtain the optimal source code rate, channel code rate and media access control (MAC) frame size. In this paper, we derive mathematical models to represent end-to-end distortion of video streams and 802.11a-like MAC and PHY with automatic repeat reQuest (ARQ) and rate compatible punctured convolutional code (RCPC) over additive white Gaussian noise (AWGN) channel. These models are formulated as a convex optimization problem, and it is solved by the primal-dual decomposition method. In addition, coexistence among the proposed utility functions and conventional utility functions is discussed. Finally, numerical examples show that significant reduction of overall distortion of utility functions can be achieved.
A Reconfigurable Source-Synchronous On-Chip Network for GALS Many-Core Platforms

This paper presents a globally-asynchronous locally-synchronous (GALS)-compatible circuit-switched on-chip network that is well suited for use in many-core platforms targeting streaming digital signal processing and embedded applications which typically have a high degree of task-level parallelism among computational kernels. Inter-processor communication is achieved through a simple yet effective reconfigurable source-synchronous network. Interconnect paths between processors can sustain a peak throughput of one word per cycle. A theoretical model is developed for analyzing the performance of the network. A 65 nm complementary metal-oxide-semiconductor GALS chip utilizing this network was fabricated which contains 164 programmable processors, three accelerators and three shared memory modules. For evaluating the efficiency of this platform, a complete 802.11a wireless local area network baseband receiver was implemented. It has a real-time throughput of 54 Mb/s with all processors running at 594 MHz and 0.95-V, and consumes an average of 174.8 mW with 12.2 mW (or 7.0%) dissipated by its interconnect links and switches. With the chip's dual supply voltages set at 0.95-V and 0.75-V, and individual processors' oscillators operating at workload-based optimal frequencies, the receiver consumes 123.2 mW, which is a 29.5% reduction in power. Measured power consumption values from the chip are within 2-5% of the estimated values.
Multi-Array Camera Disparity Enhancement

Multi-array camera systems have greater potential for 3-D depth-based application development compared with stereo camera systems. However, there are very few research results on multi-array-based disparity enhancement, extending standard stereo matchings to multi-array systems. In this paper, we propose to alternately use local and global fusion of multi-array disparities to maximize the disparity enhancement in array camera systems. We propose a new cascade regularization based approach, which can restore diagonal structures better than conventional techniques. The detailed analysis and experimental results verify that the cascade approach better regularizes the diagonal variations and in turn yields better image enhancement. We adapt total variation for regularization to the multi-array camera systems in order to globally combine multiple disparity estimates. A local multiple cross-filling algorithm is proposed to achieve cross consistency between array disparity estimates by effectively filling the mismatches. Experimental results show that the proposed multi-array disparity enhancement algorithm can improve the accuracy of the initial array disparity estimates up to 65% while alleviating memory limitation.
A model checking framework for hierarchical systems

BDD-based symbolic model checking is capable of verifying systems with a large number of states. In this work, we report an extensible framework to facilitate symbolic encoding and checking of hierarchical systems. Firstly, a novel library of symbolic encoding functions for compositional operators (e.g., parallel composition, sequential composition, choice operator, etc.) are developed so that users can apply symbolic model checking techniques to hierarchical systems with little knowledge of symbolic encoding techniques (like BDD or CUDD). Secondly, as the library is language-independent, we build an extensible framework with various symbolic model checking algorithms so that the library can be easily applied to encode and verify different modeling languages. Lastly, the applicability and scalability of our framework are demonstrated by applying the framework in the development of symbolic model checkers for three modeling languages as well as a comparison with the NuSMV model checker.
Development of Ultrasound-Switchable Fluorescence Imaging Contrast Agents Based on Thermosensitive Polymers and Nanoparticles

In this paper, we first introduced a recently developed high-resolution, deep-tissue imaging technique, ultrasound-switchable fluorescence (USF). The imaging principles based on two types of USF contrast agents were reviewed. To improve USF imaging techniques further, excellent USF contrast agents were developed based on high-performance thermoresponsive polymers and environment-sensitive fluorophores. Herein, such contrast agents were synthesized and characterized with five key parameters: 1) peak excitation and emission wavelengths (λ<sub>ex</sub> and λ<sub>em</sub>); 2) the fluorescence intensity ratio between on- and off-states (I<sub>On</sub>/I<sub>Off</sub>); 3) the fluorescence lifetime ratio between on- and off-states (τ<sub>On</sub>/τ<sub>Off</sub>); 4) the temperature threshold to switch on fluorophores (T<sub>th</sub>); and 5) the temperature transition bandwidth (T<sub>BW</sub>). We mainly investigated fluorescence intensity and lifetime changes of four environment-sensitive dyes [7-(2-Aminoethylamino)-N,N-dimethyl-4-benzofurazansulfonamide (DBD-ED), St633, Sq660, and St700] as a function of temperature, while the dye was attached to poly(N-isopropylacrylamide) linear polymers or encapsulated in nanoparticles. Six fluorescence resonance energy transfer systems were invented in which both the donor (DBD-ED or ST425) and the acceptor (Sq660) were adopted. Our results indicate that three Förster resonance energy transfer systems, where both I<sub>On</sub>/I<sub>Off</sub> and τ<sub>On</sub>/τ<sub>Off</sub> are larger than 2.5, are promising for application in future surface tissue bioimaging by the USF technique.
Linear phase paraunitary filter bank with filters of different lengths and its application in image compression

In this paper, the theory, structure, design, and implementation of a new class of linear-phase paraunitary filter banks (LPPUFBs) are investigated. The novel filter banks with filters of different lengths can be viewed as the generalized lapped orthogonal transforms (GenLOTs) with variable-length basis functions. Our main motivation is the application in block-transform-based image coding. Besides having all of the attractive properties of other lapped orthogonal transforms, the new transform takes advantage of its long, overlapping basis functions to represent smooth signals in order to reduce blocking artifacts, whereas it reserves short basis functions for high-frequency signal components like edges and texture, thereby limiting ringing artifacts. Two design methods are presented, each with its own set of advantages: the first is based on a direct lattice factorization, and the second enforces certain relationships between the lattice coefficients to obtain variable length filters. Various necessary conditions for the existence of meaningful solutions are derived and discussed in both cases. Finally, several design and image coding examples are presented to confirm the validity of the theory.
A Deconvolution Method for LCD Motion Blur Reduction

Liquid crystal displays (LCD) have shown great promise in the consumer market for their use as both computer and television displays. Despite their many advantages, the inherent nature of LCD image formation results in a phenomenon known as motion blur. LCDs emit light and aim to hold it constant during the entire frame time. In this paper we develop a method for motion blur reduction using the Richardson-Lucy deconvolution algorithm in concert with motion vector information from the scene. In addition, we derive a general lower bound on the performance of the deconvolution algorithm. Perceptual tests indicate that our algorithm is indeed effective at reducing the amount of motion blur on LCDs.
Vision based ground object tracking using AR.Drone quadrotor

This paper presents an approach to the ground object tracking problem of the low cost AR.Drone quadrotor via its integrated vision systems. It consists of three major components: (1) on-board vision based object detection and localization, (2) comprehensive empirical models of X-Y coordinate motion of the quad rotor and (3) closed-loop PD controllers on the ground station to generate steering commands via Wifi connection. The developed platform has been extensively validated in various testing environments, demonstrating its effectiveness.
A new algorithm for time-frequency spread coders using multirate filters

Filter banks have been shown to be efficient in several emerging signal communication applications. A new class of time-frequency spread coders for transmultiplexer systems using multirate filter banks is presented. As compared with conventional filter banks designed with stopband attenuation and passband flatness criteria, the user coders with the new algorithms are designed with time and frequency spread criteria. In new the algorithms, the filters are achieved through a cascade of lattice structures and delay chains. Along with the time-frequency property and the reconstruction property, the intercode/intracode correlation property are included in the design algorithms to be optimized. The designed coders are used in the application of digital watermarking of images and demonstrate good performance in JPEG encoding at different qualities.
On M-channel linear phase FIR filter banks and application in image compression

This paper investigates the theory and structure of a large subclass of M-channel linear-phase perfect-reconstruction FIR filter banks-systems with analysis and synthesis filters of length L/sub i/=K/sub i/M+/spl beta/, where /spl beta/ is an arbitrary integer, 0/spl les//spl beta/<M, and K/sub i/ is any positive integer. For this subclass of systems, we first investigate the necessary conditions for the existence of linear-phase perfect-reconstruction filter banks (LPPRFBs). Next, we develop a complete and minimal factorization for all even-channel linear-phase paraunitary systems (the most general lapped orthogonal transforms to date). Finally, several design examples as well as comparisons with previous generalized lapped orthogonal transforms (GenLOTs) in image compression are presented to confirm the validity of the theory.
Designing self-feeding system for increasing independence of elders and Parkinson people

This paper describes a customized self-feeding system designed to increase the independence of a elder person or Parkinson patient who is unable to use his/her arm for self-feeding. Besides, the procedures of design and development of the system are also carried out, and other its tasks control manipulator to feed the food to patients based on nutrients management for patients. This system can help patients self-control his meal replacement for the care of a family member or care worker thereby saving a lot of time and effort of caregivers, and, nutritional management software of each meal will allow caregivers understand nutritional information of the patients in the diet which can not change to improve the quality of meals for patients. The self-feeding system is experienced and evaluated with several cases in nursing home to give suitable design. The experimental results show that this self-feeding system provides a viable alternative to assisting independence in self-feeding as measured by ingesting time and nutrition intake. The self-feeding system is operated autonomous by itself and sent food's data and relative information to monitoring computer based on Internet. Besides, the tool of management can analyze the data according to the nutritional standards, and controller control movements of manipulator and automation tray based on health situation and needs of patients.
Single Image Superresolution Based on Support Vector Regression

Support vector machine (SVM) regression is considered for a statistical method of single frame superresolution in both the spatial and discrete cosine transform (DCT) domains. As opposed to current classification techniques, regression allows considerably more freedom in the determination of missing high-resolution information. In addition, since SVM regression approaches the superresolution problem as an estimation problem with a criterion of image correctness rather than visual acceptableness, its optimization results have better mean-squared error. With the addition of structure in the DCT coefficients, DCT domain image superresolution is further improved
HDR Imaging From Differently Exposed Multiview Videos

A procedure for obtaining high dynamic range (HDR) videos from multiple differently exposed image sequences from a camera array is explored. It is observed that using information along both viewspace (camera) and temporal axes results in a good estimate of the HDR image sequence. Images captured at longer exposures are subject to motion blur. A novel motion deblurring scheme is proposed, prior to the actual HDR mapping process. This involves a multiscale directional structure preservation procedure which uses information from adjacent views along camera-space and frames along time. The proposed deblurring scheme works in spite of illumination variations between images.
The Shiftable Complex Directional Pyramid—Part I: Theoretical Aspects

This paper presents an over-complete multiscale decomposition by combining the Laplacian pyramid and the complex directional filter bank (DFB). The filter bank is constructed in such a way that each complex directional filter is analytical using the dual-tree structure of real fan filters. Necessary and sufficient conditions in order for the resulting multirate filter bank to be shift-invariant in energy sense (shiftability) are derived in terms of the magnitude and phase responses of these filters. Their connection to 2D Hilbert transform relationship is established. The proposed transform possesses several desirable properties including multiresolution, arbitrarily high directional resolution, low redundant ratio, and efficient implementation.
Crosstalk modeling in circularly polarized stereoscopic LCDS

Crosstalk is the most critical artifact in stereoscopic 3D displays. Circularly polarized (CP) 3D LCDs with passive glasses has the issue of crosstalk especially when the viewer moves vertically away from the screen center. In this work, a new display model for CP LCD is proposed which considers both the intrinsic optical system including the polarizer and the wave retarder, and the vertical misalignment (VM) of light between the liquid crystal (LC) and the patterned retarder (PR) as the two major factors causing crosstalk in CP LCDs. The optical modeling for the display uses Mueller calculus and the characterization of VM is realized by the proposed user-calibration method. The display model is proved to be accurate by both measuring and subjective test in predicting the crosstalk resulted from different viewing scenarios. Additionally, we proposed considering image texture for the estimation of crosstalk perception. The proposed estimation is shown to be consistent with the viewer's observation.