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Validation and use of a finite element model of C-2 for determination of stress and fracture patterns of anterior odontoid loads.

OBJECT: The finite element (FE) method is a powerful tool for the analysis of stress patterns of anatomical structures. In this study a highly refined FE model of C-2 was created and validated. The model was then used to characterize stress patterns, predicted fracture patterns, and transitions between Type II and Type III odontoid fractures. METHODS: An anatomically accurate three-dimensional model of C-2 was created from computerized tomography data obtained from the Visible Human Project. The C-2 model was broken down into an FE mesh consisting of 32,815 elements and 40,969 nodes. For validation, the FE model was constrained and loaded to simulate that used in previous biomechanical studies. The validated model was then loaded in an iterative fashion, varying the orientation of the load within the validated range. A matrix of stress plots was created for comparative analysis. Results of the validation testing closely correlated with those obtained in previous biomechanical testing. Pure extension loading produced a Type III stress pattern with maximum stress of 134 MPa. Loading at 45 degrees produced a Type II stress distribution with a maximum stress of 123 MPa. These stresses are within 3% and 11%, respectively, of the reported yield stress of cortical bone (138 MPa). In the second portion of the study, systematic variation in the orientation of the load vector revealed that higher stresses were associated with increased lateral angulation and increasing upward inclination of the load vectors. A transition from a Type III to Type II pattern occurred with lateral orientations greater than 15 degrees and with compressive loads of 45 degrees. CONCLUSIONS: The validated C-2 FE model described in this study both qualitatively and quantitatively was able to simulate the behavior of the C-2 vertebra in biomechanical testing. In this study the authors demonstrate the utility of the FE method when used in conjunction with traditional biomechanical testing.

Algorithms↗

The landscape of pruning for large language models: A systematic review and unified taxonomy.

Confronting the inherent tension between the exceptional capabilities and the immense computational costs of Large Language Models (LLMs), pruning has become a crucial technique for achieving efficient deployment. However, a systematic analytical framework dedicated specifically to LLM pruning remains absent. In this paper, we aim to bridge this gap. We first elucidate the theoretical foundations that underpin the effectiveness of pruning, namely overparameterization and redundancy, and then propose a multidimensional taxonomy that organizes existing approaches along the axes of granularity, timing, and criteria. Building upon this unified perspective, we further analyze performance recovery mechanisms and the broader evaluation ecosystem, while also exploring forward-looking challenges such as interpretability, automation, and hardware-algorithm co-design. Through this comprehensive synthesis, we seek to provide an integrated and coherent analytical lens for advancing both research and practice in LLM pruning.

Large Language Models↗

Reconstruction of sculpture from its profiles with unknown camera positions.

Profiles of a sculpture provide rich information about its geometry, and can be used for shape recovery under known camera motion. By exploiting correspondences induced by epipolar tangents on the profiles, a successful solution to motion estimation from profiles has been developed in the special case of circular motion. The main drawbacks of using circular motion alone, namely the difficulty in adding new views and part of the object always being invisible, can be overcome by incorporating arbitrary general views of the object and registering its new profiles with the set of profiles resulted from the circular motion. In this paper, we describe a complete and practical system for producing a three-dimensional (3-D) model from uncalibrated images of an arbitrary object using its profiles alone. Experimental results on various objects are presented, demonstrating the quality of the reconstructions using the estimated motion.

Algorithms↗

High-accuracy 3-D modeling of cultural heritage: the digitizing of Donatello's "Maddalena".

Three-dimensional digital modeling of Heritage works of art through optical scanners, has been demonstrated in recent years with results of exceptional interest. However, the routine application of three-dimensional (3-D) modeling to Heritage conservation still requires the systematic investigation of a number of technical problems. In this paper, the acquisition process of the 3-D digital model of the Maddalena by Donatello, a wooden statue representing one of the major masterpieces of the Italian Renaissance which was swept away by the Florence flood of 1966 and successively restored, is described. The paper reports all the steps of the acquisition procedure, from the project planning to the solution of the various problems due to range camera calibration and to material non optically cooperative. Since the scientific focus is centered on the 3-D model overall dimensional accuracy, a methodology for its quality control is described. Such control has demonstrated how, in some situations, the ICP-based alignment can lead to incorrect results. To circumvent this difficulty we propose an alignment technique based on the fusion of ICP with close-range digital photogrammetry and a non-invasive procedure in order to generate a final accurate model. In the end detailed results are presented, demonstrating the improvement of the final model, and how the proposed sensor fusion ensure a pre-specified level of accuracy.

Algorithms↗

An analysis of the efficiency of different SNR-scalable strategies for video coders.

In this paper, we analyze the efficiency of three signal-to-noise scalable strategies for video coders using single-loop motion-compensated prediction (MCP). In our analysis, we assume the video sequences have uniform and constant translational motion and we model MCP as a stochastic filter. We also assume an exponential model for the distortion-rate function of the intraframe coding. The analysis is divided into two parts: the steady-state analysis and the transient analysis. In the first part, only the steady-state response of the coders is taken into account, and, thus, this analysis allows us to asses approximately the efficiency of coders with long input sequences. The transitory analysis considers both the transient and the steady-state responses of the coders, which makes it appropriate to analyze coders using periodic intraframes or with short input sequences. To validate our analysis, theoretical results have been compared to results from encodings of real video sequences using the scalable adaptive motion compensated wavelet video coder. We show that our theoretical analysis effectively describes qualitatively the main trends of every video coding strategy.

Algorithms↗

Reducing video-quality fluctuations for streaming scalable video using unequal error protection, retransmission, and interleaving.

Forward error correction based multiple description (MD-FEC) transcoding for transmitting embedded bitstream over the packet erasure networks has been extensively studied in the past. In the existing work, a single embedded source bitstream, e.g., the bitstream of a group of pictures (GOP) encoded using three-dimensional set partitioning in hierarchical trees is optimally protected unequal error protection (UEP) in the rate-distortion sense. However, most of the previous work on transmitting embedded video using MD-FEC assumed that one GOP is transmitted only once, and did not consider the chance of retransmission. This may lead to noticeable video quality variations due to varying channel conditions. In this paper, a novel window-based packetization scheme is proposed, which combats bursty packet loss by combining the following three techniques: UEP, retransmission, and GOP-level interleaving. In particular, two retransmission mechanisms, namely segment-wise retransmission and byte-wise retransmission, are proposed based on different types of receiver feedback. Moreover, two levels of rate allocations are introduced: intra-GOP rate allocation minimizes the distortion of individual GOP; while inter-GOP rate allocation intends to reduce video quality fluctuations by adaptively allocating bandwidth according to video signal characteristics and client buffer status. In this way, more consistent video quality can be achieved under various packet loss probabilities, as demonstrated by our experimental results.

Algorithms↗

A cross-layer diversity technique for multicarrier OFDM multimedia networks.

Diversity can be used to combat multipath fading and improve the performance of wireless multimedia communication systems. In this work, by considering transmission of an embedded bitstream over an orthogonal frequency division multiplexing (OFDM) system in a slowly varying Rayleigh faded environment, we develop a cross-layer diversity technique which takes advantage of both multiple description coding and frequency diversity techniques. More specifically, assuming a frequency-selective channel, we study the packet loss behavior of an OFDM system and construct multiple independent descriptions using an FEC-based strategy. We provide some analysis of this cross-layer approach and demonstrate its superior performance using the set partitioning in hierarchical trees image coder.

Algorithms↗

Joint source-channel coding for wireless object-based video communications utilizing data hiding.

In recent years, joint source-channel coding for multimedia communications has gained increased popularity. However, very limited work has been conducted to address the problem of joint source-channel coding for object-based video. In this paper, we propose a data hiding scheme that improves the error resilience of object-based video by adaptively embedding the shape and motion information into the texture data. Within a rate-distortion theoretical framework, the source coding, channel coding, data embedding, and decoder error concealment are jointly optimized based on knowledge of the transmission channel conditions. Our goal is to achieve the best video quality as expressed by the minimum total expected distortion. The optimization problem is solved using Lagrangian relaxation and dynamic programming. The performance of the proposed scheme is tested using simulations of a Rayleigh-fading wireless channel, and the algorithm is implemented based on the MPEG-4 verification model. Experimental results indicate that the proposed hybrid source-channel coding scheme significantly outperforms methods without data hiding or unequal error protection.

Algorithms↗

Curved wavelet transform for image coding.

The conventional two-dimensional wavelet transform used in existing image coders is usually performed through one-dimensional (1-D) filtering in the vertical and horizontal directions, which cannot efficiently represent edges and lines in images. The curved wavelet transform presented in this paper is carried out by applying 1-D filters along curves, rather than being restricted to vertical and horizontal straight lines. The curves are determined based on image content and are usually parallel to edges and lines in the image to be coded. The pixels along these curves can be well represented by a small number of wavelet coefficients. The curved wavelet transform is used to construct a new image coder. The code-stream syntax of the new coder is the same as that of JPEG2000, except that a new marker segment is added to the tile headers. Results of image coding and subjective quality assessment show that the new image coder performs better than, or as well as, JPEG2000. It is particularly efficient for images that contain sharp edges and can provide a PSNR gain of up to 1.67 dB for natural images compared with JPEG2000.

Algorithms↗

Halftone visual cryptography.

Visual cryptography encodes a secret binary image (SI) into n shares of random binary patterns. If the shares are xeroxed onto transparencies, the secret image can be visually decoded by superimposing a qualified subset of transparencies, but no secret information can be obtained from the superposition of a forbidden subset. The binary patterns of the n shares, however, have no visual meaning and hinder the objectives of visual cryptography. Extended visual cryptography [1] was proposed recently to construct meaningful binary images as shares using hypergraph colourings, but the visual quality is poor. In this paper, a novel technique named halftone visual cryptography is proposed to achieve visual cryptography via halftoning. Based on the blue-noise dithering principles, the proposed method utilizes the void and cluster algorithm [2] to encode a secret binary image into n halftone shares (images) carrying significant visual information. The simulation shows that the visual quality of the obtained halftone shares are observably better than that attained by any available visual cryptography method known to date.

Algorithms↗

Progressive transmission of images over fading channels using rate-compatible LDPC codes.

In this paper, we propose a combined source/channel coding scheme for transmission of images over fading channels. The proposed scheme employs rate-compatible low-density parity-check codes along with embedded image coders such as JPEG2000 and set partitioning in hierarchical trees (SPIHT). The assignment of channel coding rates to source packets is performed by a fast trellis-based algorithm. We examine the performance of the proposed scheme over correlated and uncorrelated Rayleigh flat-fading channels with and without side information. Simulation results for the expected peak signal-to-noise ratio of reconstructed images, which are within 1 dB of the capacity upper bound over a wide range of channel signal-to-noise ratios, show considerable improvement compared to existing results under similar conditions. We also study the sensitivity of the proposed scheme in the presence of channel estimation error at the transmitter and demonstrate that under most conditions our scheme is more robust compared to existing schemes.

Algorithms↗

Layered Wyner-Ziv video coding.

Following recent theoretical works on successive Wyner-Ziv coding (WZC), we propose a practical layered Wyner-Ziv video coder using the DCT, nested scalar quantization, and irregular LDPC code based Slepian-Wolf coding (or lossless source coding with side information at the decoder). Our main novelty is to use the base layer of a standard scalable video coder (e.g., MPEG-4/H.26L FGS or H.263+) as the decoder side information and perform layered WZC for quality enhancement. Similar to FGS coding, there is no performance difference between layered and monolithic WZC when the enhancement bitstream is generated in our proposed coder. Using an H.26L coded version as the base layer, experiments indicate that WZC gives slightly worse performance than FGS coding when the channel (for both the base and enhancement layers) is noiseless. However, when the channel is noisy, extensive simulations of video transmission over wireless networks conforming to the CDMA2000 1X standard show that H.26L base layer coding plus Wyner-Ziv enhancement layer coding are more robust against channel errors than H.26L FGS coding. These results demonstrate that layered Wyner-Ziv video coding is a promising new technique for video streaming over wireless networks.

Algorithms↗

A hybrid neural network model for noisy data regression.

A hybrid neural network model, based on the fusion of fuzzy adaptive resonance theory (FA ART) and the general regression neural network (GRNN), is proposed in this paper. Both FA and the GRNN are incremental learning systems and are very fast in network training. The proposed hybrid model, denoted as GRNNFA, is able to retain these advantages and, at the same time, to reduce the computational requirements in calculating and storing information of the kernels. A clustering version of the GRNN is designed with data compression by FA for noise removal. An adaptive gradient-based kernel width optimization algorithm has also been devised. Convergence of the gradient descent algorithm can be accelerated by the geometric incremental growth of the updating factor. A series of experiments with four benchmark datasets have been conducted to assess and compare effectiveness of GRNNFA with other approaches. The GRNNFA model is also employed in a novel application task for predicting the evacuation time of patrons at typical karaoke centers in Hong Kong in the event of fire. The results positively demonstrate the applicability of GRNNFA in noisy data regression problems.

Journal Article↗

Optimizing multicompression approaches to elasticity imaging.

Breast lesion visibility in static strain imaging ultimately is noise limited. When correlation and related techniques are applied to estimate local displacements between two echo frames recorded before and after a small deformation, target contrast increases linearly with the amount of deformation applied. However, above some deformation threshold, decorrelation noise increases more than contrast such that lesion visibility is severely reduced. Multicompression methods avoid this problem by accumulating displacements from many small deformations to provide the same net increase in lesion contrast as one large deformation but with minimal decorrelation noise. Unfortunately, multicompression approaches accumulate echo noise (electronic and sampling) with each deformation step as contrast builds so that lesion visibility can be reduced again if the applied deformation increment is too small. This paper uses signal models and analysis techniques to develop multicompression strategies that minimize strain image noise. The analysis predicts that displacement variance is minimal in elastically homogeneous media when the applied strain increment is 0.0035. Predictions are verified experimentally with gelatin phantoms. For in vivo breast imaging, a strain increment as low as 0.0015 is recommended for minimum noise because of the greater elastic heterogeneity of breast tissue.

Algorithms↗

Blind robust watermarking schemes for copyright protection of 3D mesh objects.

In this paper, two novel methods suitable for blind 3D mesh object watermarking applications are proposed. The first method is robust against 3D rotation, translation, and uniform scaling. The second one is robust against both geometric and mesh simplification attacks. A pseudorandom watermarking signal is cast in the 3D mesh object by deforming its vertices geometrically, without altering the vertex topology. Prior to watermark embedding and detection, the object is rotated and translated so that its center of mass and its principal component coincide with the origin and the z-axis of the Cartesian coordinate system. This geometrical transformation ensures watermark robustness to translation and rotation. Robustness to uniform scaling is achieved by restricting the vertex deformations to occur only along the r coordinate of the corresponding (r, theta, phi) spherical coordinate system. In the first method, a set of vertices that correspond to specific angles theta is used for watermark embedding. In the second method, the samples of the watermark sequence are embedded in a set of vertices that correspond to a range of angles in the theta domain in order to achieve robustness against mesh simplifications. Experimental results indicate the ability of the proposed method to deal with the aforementioned attacks.

Algorithms↗

Neurosurgical management of neuropathic pain.

Neuropathic pain is a very difficult problem with which the neurosurgeon frequently must deal. The neurosurgical methods to be considered are: (1) modulative, by using neurostimulation or implanted drug delivery systems, and (2) ablative, by making selective therapeutic lesions in well-defined and identified targets proven to sustain pain mechanisms (especially DREZotomy).

Algorithms↗

Automated electrocardiogram analysis: the state of the art.

The overwhelming number of electrocardiograms (ECGs) now recorded routinely has prompted the development of computer analysis which in turn has benefited electrocardiography with important technological advances. All automated ECG analysis systems adopt a similar approach: a measurement program and a program that interprets the clinical significance of these measurements along with a rhythm analysis algorithm. Measurement, selection and classification of parameters vary according to the program used. Data compression is applied to the signal to reduce processing time and allow long-term storage. Diagnostic accuracy, however, is not greatly improved over that of experienced cardiologists. Programs studied using a validated data bank provided by an international group of cardiologists show a variability not only in parameter measurement but also in diagnostic statement and in the way in which such statements are expressed. Recommendations for measurement standards have been made to fulfil the need for exchange of diagnostic criteria. No recommendations concerning the selection of parameters have been proposed, and so new parameters or combinations of parameters can be introduced with the ultimate aim of increased diagnostic performance.

Diagnosis, Computer-Assisted↗

Radiology of acute spinal trauma.

Radiologic diagnostic modalities utilized to evaluate acute spine trauma include plain films, tomography, computerized tomography (CT), myelography and CT-myelography, and magnetic resonance imaging. The initial evaluation is aimed at delineating the nature and extent of both boney and soft tissue injuries, with particular attention directed toward differentiating intrinsic cord damage from extrinsic spinal cord or nerve root compression that may respond to surgical intervention. The selection of the optimal radiologic diagnostic algorithm requires familiarization with the techniques and limitations of each diagnostic procedure.

Algorithms↗