Reconstruction of pulse noisy images via stochastic resonance.
Ontology highlight
ABSTRACT:
SUBMITTER: Han J
PROVIDER: S-EPMC4464402 | biostudies-other | 2015
REPOSITORIES: biostudies-other
Similar Datasets
Project description:We propose a novel scheme for restoring pulse and high noisy images using stochastic resonance, which is based on the modulation instability and provides a cross-correlation gain higher than 8. As opposed to previously reported designs, this unique approach employs a continuous noise and pulse signal for the generation of modulation instability. The visibility and quality of output images can be improved by appropriately adjusting the system parameters. This provides a simple and feasible method for detecting low-level or hidden pulse images in various imaging applications.
| S-EPMC4632024 | biostudies-other
Project description:Analysis of microscopy images can provide insight into many biological processes. One particularly challenging problem is cellular nuclear segmentation in highly anisotropic and noisy 3D image data. Manually localizing and segmenting each and every cellular nucleus is very time-consuming, which remains a bottleneck in large-scale biological experiments. In this work, we present a tool for automated segmentation of cellular nuclei from 3D fluorescent microscopic data. Our tool is based on state-of-the-art image processing and machine learning techniques and provides a user-friendly graphical user interface. We show that our tool is as accurate as manual annotation and greatly reduces the time for the registration.
| S-EPMC4389647 | biostudies-literature
Project description:Stochastic resonance (SR) is the enhanced representation of a weak input signal by the addition of an optimal level of broadband noise to a nonlinear (threshold) system. Since its discovery in the 1980s the domain of input signals shown to be applicable to SR has greatly expanded, from strictly periodic inputs to now nearly any aperiodic forcing function. The perturbations (noise) used to generate SR have also expanded, from white noise to now colored noise or vibrational forcing. This study demonstrates that a new class of perturbations can achieve SR, namely, series of stochastically generated biphasic pulse trains. Using these pulse trains as 'noise' we show that a Hodgkin Huxley model neuron exhibits SR behavior when detecting weak input signals. This result is of particular interest to neuroscience because nearly all artificial neural stimulation is implemented with square current or voltage pulses rather than broadband noise, and this new method may facilitate the translation of the performance gains achievable through SR to neural prosthetics.
| S-EPMC4297574 | biostudies-literature
Project description:Noisy galvanic vestibular stimulation (nGVS) at imperceptible levels has been shown to reduce body sway. This reduction was commonly attributed to the mechanism of stochastic resonance (SR). However, it has never been explicitly tested whether nGVS-induced effects on body sway consistently follow a SR-like bell-shaped performance curve with maximal reductions in a particular range of noise intensities. To test this, body sway in 21 young healthy participants was measured during varying nGVS amplitudes while standing with eyes closed in 3 conditions (quiet stance, sway referencing, sinusoidal platform tilts). Presence of SR-like response dynamics in each trial was assessed (1) by a goodness-of-fit analysis using an established SR-curve model and (2) by ratings from 3 human experts. In accordance to theory, we found reductions of body sway at one nGVS amplitude in most trials (75-95%). However, only few trials exhibited SR-like bell-shaped performance curves with increasing noise amplitudes (10-33%). Instead, body sway measures rather fluctuated randomly across nGVS amplitudes. This implies that, at least in young healthy adults, nGVS effects on body sway are incompatible with SR. Thus, previously reported reductions of body sway at particular nGVS intensities more likely result from inherent variations of the performance metric or by other yet unknown mechanisms.
| S-EPMC8192540 | biostudies-literature
Project description:We target the problem of estimating the center of mass of objects in noisy two-dimensional images. We assume that the noise dominates the image, and thus many standard approaches are vulnerable to estimation errors, e.g., the direct computation of the center of mass and the geometric median which is a robust alternative to the center of mass. In this paper, we define a novel surrogate function to the center of mass. We present a mathematical and numerical analysis of our method and show that it outperforms existing methods for estimating the center of mass of an object in various realistic scenarios. As a case study, we apply our centering method to data from single-particle cryo-electron microscopy (cryo-EM), where the goal is to reconstruct the three-dimensional structure of macromolecules. We show how to apply our approach for a better translational alignment of molecule images picked from experimental data. In this way, we facilitate the succeeding steps of reconstruction and streamline the entire cryo-EM pipeline, saving computational time and supporting resolution enhancement.
| S-EPMC8813033 | biostudies-literature
Project description:In the last years, technological advancements for the analysis of electroencephalography (EEG) recordings have permitted to investigate neural activity and connectivity in the human brain with unprecedented precision and reliability. A crucial element for accurate EEG source reconstruction is the construction of a realistic head model, incorporating information on electrode positions and head tissue distribution. In this paper, we introduce MR-TIM, a toolbox for head tissue modelling from structural magnetic resonance (MR) images. The toolbox consists of three modules: 1) image pre-processing - the raw MR image is denoised and prepared for further analyses; 2) tissue probability mapping - template tissue probability maps (TPMs) in individual space are generated from the MR image; 3) tissue segmentation - information from all the TPMs is integrated such that each voxel in the MR image is assigned to a specific tissue. MR-TIM generates highly realistic 3D masks, five of which are associated with brain structures (brain and cerebellar grey matter, brain and cerebellar white matter, and brainstem) and the remaining seven with other head tissues (cerebrospinal fluid, spongy and compact bones, eyes, muscle, fat and skin). Our validation, conducted on MR images collected in healthy volunteers and patients as well as an MR template image from an open-source repository, demonstrates that MR-TIM is more accurate than alternative approaches for whole-head tissue segmentation. We hope that MR-TIM, by yielding an increased precision in head modelling, will contribute to a more widespread use of EEG as a brain imaging technique.
| S-EPMC8566646 | biostudies-literature
Project description:Analytical electron microscopy plays a key role in the development of novel nanomaterials. Electron energy-loss spectroscopy (EELS) and energy-dispersive X-ray spectroscopy (EDX) datasets are typically processed to isolate the background-subtracted elemental signal. Multivariate tools have emerged as powerful methods to blindly map the components, which addresses some of the shortcomings of the traditional methods. Here, we demonstrate the superior performance of a new multivariate optimization method using a challenging EELS and EDX dataset. The dataset was recorded from a spectrum image P-type metal-oxide-semiconductor stack with 7 components exhibiting heavy spectral overlap and a low signal-to-noise ratio. Compared to peak integration, independent component analysis, Baysian Linear Unmixing and Non-negative matrix factorization, the method proposed was the only one to identify the EELS spectra of all 7 components with the corresponding abundance profiles. Using the abundance of each component, it was possible to retrieve the EDX spectra of all the components, which were otherwise impossible to isolate, regardless of the method used. We expect that this robust method will bring a significant improvement for the chemical analysis of nanomaterials, especially for weak signals, dose-sensitive specimen or signals suffering heavy spectral overlap.
| S-EPMC6906416 | biostudies-literature
Project description:Gene regulatory circuits can use dynamic, and even stochastic, strategies to respond to environmental conditions. We examined activation of the general stress response mediated by the alternative sigma factor, ?(B), in individual Bacillus subtilis cells. We observed that energy stress activates ?(B) in discrete stochastic pulses, with increasing levels of stress leading to higher pulse frequencies. By perturbing and rewiring the endogenous system, we found that this behavior results from three key features of the ?(B) circuit: an ultrasensitive phosphorylation switch; stochasticity ("noise"), which activates that switch; and a mixed (positive and negative) transcriptional feedback, which can both amplify a pulse and switch it off. Together, these results show how prokaryotes encode signals using stochastic pulse frequency modulation through a compact regulatory architecture.
| S-EPMC4100694 | biostudies-literature
Project description:In this paper, we present a novel technique, based on compressive sensing principles, for reconstruction and enhancement of multi-dimensional image data. Our method is a major improvement and generalization of the multi-scale sparsity based tomographic denoising (MSBTD) algorithm we recently introduced for reducing speckle noise. Our new technique exhibits several advantages over MSBTD, including its capability to simultaneously reduce noise and interpolate missing data. Unlike MSBTD, our new method does not require an a priori high-quality image from the target imaging subject and thus offers the potential to shorten clinical imaging sessions. This novel image restoration method, which we termed sparsity based simultaneous denoising and interpolation (SBSDI), utilizes sparse representation dictionaries constructed from previously collected datasets. We tested the SBSDI algorithm on retinal spectral domain optical coherence tomography images captured in the clinic. Experiments showed that the SBSDI algorithm qualitatively and quantitatively outperforms other state-of-the-art methods.
| S-EPMC4000559 | biostudies-literature
Project description:Background and purposeStroke rehabilitation does not often integrate both sensory and motor recovery. While subthreshold noise was shown to enhance sensory signal detection at the site of noise application, having a noise-generating device at the fingertip to enhance fingertip sensation and potentially enhance dexterity for stroke survivors is impractical, since the device would interfere with object manipulation. This study determined if remote application of subthreshold vibrotactile noise (away from the fingertips) improves fingertip tactile sensation with potential to enhance dexterity for stroke survivors.MethodsIndex finger and thumb pad sensation was measured for ten stroke survivors with fingertip sensory deficit using the Semmes-Weinstein Monofilament and Two-Point Discrimination Tests. Sensation scores were measured with noise applied at one of three intensities (40%, 60%, 80% of the sensory threshold) to one of four locations of the paretic upper extremity (dorsal hand proximal to the index finger knuckle, dorsal hand proximal to the thumb knuckle, dorsal wrist, volar wrist) in a random order, as well as without noise at beginning (Pre) and end (Post) of the testing session.ResultsVibrotactile noise of all intensities and locations instantaneously and significantly improved Monofilament scores of the index fingertip and thumb tip (p < .01). No significant effect of the noise was seen for the Two-Point Discrimination Test scores.ConclusionsRemote application of subthreshold (imperceptible) vibrotactile noise at the wrist and dorsal hand instantaneously improved stroke survivors' light touch sensation, independent of noise location and intensity. Vibrotactile noise at the wrist and dorsal hand may have enhanced the fingertips' light touch sensation via stochastic resonance and interneuronal connections. While long-term benefits of noise in stroke patients warrants further investigation, this result demonstrates potential that a wearable device applying vibrotactile noise at the wrist could enhance sensation and grip ability without interfering with object manipulation in everyday tasks.
| S-EPMC3852405 | biostudies-literature