In vivo imaging reveals a synchronized correlation among neurotransmitter dynamics during propofol and sevoflurane anesthesia

General anesthesia is widely applied in clinical practice.However,the precise mechanism of loss of consciousness induced by general anesthetics remains unknown.Here,we measured the dynamics of five neurotransmitters,includingγ-aminobutyric acid,glutamate,norepinephrine,acetylcholine,and dopamine,in the medial prefrontal cortex and primary visual cortex of C57BL/6 mice through in vivo fiber photometry and genetically encoded neurotransmitter sensors under anesthesia to reveal the mechanism of general anesthesia from a neurotransmitter perspective.Results revealed that the concentrations of γ-aminobutyric acid,glutamate,norepinephrine,and acetylcholine increased in the cortex during propofol-induced loss of consciousness.Dopamine levels did not change following the hypnotic dose of propofol but increased significantly following surgical doses of propofol anesthesia.Notably,the concentrations of the five neurotransmitters generally decreased during sevoflurane-induced loss of consciousness.Furthermore,the neurotransmitter dynamic networks were not synchronized in the non-anesthesia groups but were highly synchronized in the anesthetic groups.These findings suggest that neurotransmitter dynamic network synchronization may cause anesthetic-induced loss of consciousness.

Magnetic resonance diffusion tensor imaging and diffusion tensor tractography of human visual pathway

AIM: To investigate the visual pathway in normal subjects and patients with lesion involved by diffusion tensor imaging (DTI) and diffusion tensor tractography (DTT). METHODS: Thirty normal volunteers, 3 subjects with orbital tumors involved the optic nerve (ON) and 33 subjects with occipital lobe tumors involved the optic radiation (OR) (10 gliomas, 6 meningiomas and 17 cerebral metastases) undertook routine cranium magnetic resonance imaging (MRI), DTI and DTT. Visual pathway fibers were analyzed by DTI and DTT images. Test fractional anisotropy (FA) and mean diffusivity (MD) values in different part of the visual pathway. RESULTS: The whole visual pathway but optic chiasm manifested as hyperintensity in FA maps and homogenous green signal in the direction encoded color maps. The optic chiasm did not display clearly. There was no significant difference between the bilateral FA values and MD values of normal visual pathway but optic chiasm, which the FA values tested were much too low (all P>0.05). The ONs of subjects with orbital tumors were compressed and displaced. Only one subject had lower FA values and higher MD values. OR of 9 gliomas subjects were infiltrated, with displacement in 2 and disruption in 7 subjects. All OR in 6 meniongiomas subjects were displaced. OR in 17 cerebral metastases subjects all developed displacement while 7 of them had disruption also. CONCLUSION: MR-DTI is highly sensitive in manifesting visual pathway. Visual pathway can be analyzed quantitatively in FA and MD values. DTT supplies accurate three dimensional conformations of visual pathway. But optic chiasm's manifestation still needs to improve.

A Concise and Varied Visual Features-Based Image Captioning Model with Visual Selection

Image captioning has gained increasing attention in recent years.Visual characteristics found in input images play a crucial role in generating high-quality captions.Prior studies have used visual attention mechanisms to dynamically focus on localized regions of the input image,improving the effectiveness of identifying relevant image regions at each step of caption generation.However,providing image captioning models with the capability of selecting the most relevant visual features from the input image and attending to them can significantly improve the utilization of these features.Consequently,this leads to enhanced captioning network performance.In light of this,we present an image captioning framework that efficiently exploits the extracted representations of the image.Our framework comprises three key components:the Visual Feature Detector module(VFD),the Visual Feature Visual Attention module(VFVA),and the language model.The VFD module is responsible for detecting a subset of the most pertinent features from the local visual features,creating an updated visual features matrix.Subsequently,the VFVA directs its attention to the visual features matrix generated by the VFD,resulting in an updated context vector employed by the language model to generate an informative description.Integrating the VFD and VFVA modules introduces an additional layer of processing for the visual features,thereby contributing to enhancing the image captioning model’s performance.Using the MS-COCO dataset,our experiments show that the proposed framework competes well with state-of-the-art methods,effectively leveraging visual representations to improve performance.The implementation code can be found here:https://github.com/althobhani/VFDICM(accessed on 30 July 2024).

Enhancing visual security: An image encryption scheme based on parallel compressive sensing and edge detection embedding

A novel image encryption scheme based on parallel compressive sensing and edge detection embedding technology is proposed to improve visual security. Firstly, the plain image is sparsely represented using the discrete wavelet transform.Then, the coefficient matrix is scrambled and compressed to obtain a size-reduced image using the Fisher–Yates shuffle and parallel compressive sensing. Subsequently, to increase the security of the proposed algorithm, the compressed image is re-encrypted through permutation and diffusion to obtain a noise-like secret image. Finally, an adaptive embedding method based on edge detection for different carrier images is proposed to generate a visually meaningful cipher image. To improve the plaintext sensitivity of the algorithm, the counter mode is combined with the hash function to generate keys for chaotic systems. Additionally, an effective permutation method is designed to scramble the pixels of the compressed image in the re-encryption stage. The simulation results and analyses demonstrate that the proposed algorithm performs well in terms of visual security and decryption quality.

Importance-aware 3D volume visualization for medical content-based image retrieval-a preliminary study

Background A medical content-based image retrieval(CBIR)system is designed to retrieve images from large imaging repositories that are visually similar to a user′s query image.CBIR is widely used in evidence-based diagnosis,teaching,and research.Although the retrieval accuracy has largely improved,there has been limited development toward visualizing important image features that indicate the similarity of retrieved images.Despite the prevalence of 3D volumetric data in medical imaging such as computed tomography(CT),current CBIR systems still rely on 2D cross-sectional views for the visualization of retrieved images.Such 2D visualization requires users to browse through the image stacks to confirm the similarity of the retrieved images and often involves mental reconstruction of 3D information,including the size,shape,and spatial relations of multiple structures.This process is time-consuming and reliant on users'experience.Methods In this study,we proposed an importance-aware 3D volume visualization method.The rendering parameters were automatically optimized to maximize the visibility of important structures that were detected and prioritized in the retrieval process.We then integrated the proposed visualization into a CBIR system,thereby complementing the 2D cross-sectional views for relevance feedback and further analyses.Results Our preliminary results demonstrate that 3D visualization can provide additional information using multimodal positron emission tomography and computed tomography(PETCT)images of a non-small cell lung cancer dataset.

A visualization pipeline for in vivo two-photon volumetric astrocytic calcium imaging

Astrocytes,the multi-functional glial cells with the most abundant population in the brain,integrate information across their territories to regulate neuronal synaptic and cerebrovascular activities.Astrocytic calcium(Ca^(2+))signaling is the major readout of cellular functional state of astrocytes.The conventional two-photon in vivo imaging usually focuses on a single horizontal focal plane to capture the astrocytic Ca^(2+)signals,which leaves>80%spatial information undetected.To fully probe the Ca^(2+)activity across the whole astrocytic territory,we developed a pipeline for imaging and visualizing volumetric astrocytic Ca^(2+)time-lapse images.With the pipeline,we discovered a new signal distribution pattern from three-dimensional(3D)astrocytic Ca^(2+)imaging data of mice under isoflurane anesthetic states.The tools developed in this study enable a better understanding of the spatiotemporal patterns of astrocytic activity in 3D space.

A Visual Indoor Localization Method Based on Efficient Image Retrieval

The task of indoor visual localization, utilizing camera visual information for user pose calculation, was a core component of Augmented Reality (AR) and Simultaneous Localization and Mapping (SLAM). Existing indoor localization technologies generally used scene-specific 3D representations or were trained on specific datasets, making it challenging to balance accuracy and cost when applied to new scenes. Addressing this issue, this paper proposed a universal indoor visual localization method based on efficient image retrieval. Initially, a Multi-Layer Perceptron (MLP) was employed to aggregate features from intermediate layers of a convolutional neural network, obtaining a global representation of the image. This approach ensured accurate and rapid retrieval of reference images. Subsequently, a new mechanism using Random Sample Consensus (RANSAC) was designed to resolve relative pose ambiguity caused by the essential matrix decomposition based on the five-point method. Finally, the absolute pose of the queried user image was computed, thereby achieving indoor user pose estimation. The proposed indoor localization method was characterized by its simplicity, flexibility, and excellent cross-scene generalization. Experimental results demonstrated a positioning error of 0.09 m and 2.14° on the 7Scenes dataset, and 0.15 m and 6.37° on the 12Scenes dataset. These results convincingly illustrated the outstanding performance of the proposed indoor localization method.

Functional magnetic resonance imaging evaluation of visual cortex activation in patients with anterior visual pathway lesions

The aim of this study was to examine the secondary visual cortex functional disorder in patients with glaucoma and large pituitary adenoma by functional magnetic resonance imaging, and to determine the correlation between visual field defect and primary visual cortex activation. Results showed that single eye stimulation resulted in bilateral visual cortex activation in patients with glaucoma or large pituitary adenoma. Compared with the normal control group, the extent and intensity of visual cortex activation was decreased after left and right eye stimulation, and functional magnetic resonance imaging revealed a correlation between visual field defects and visual cortex activation in patients with glaucoma and large pituitary adenoma. These functional magnetic resonance imaging data suggest that anterior optic pathway lesions can cause secondary functional disorder of the visual cortex, and that visual defects are correlated with visual cortex activation.

Makeup Activates Brain Activity in Visually Impaired Persons: Evaluation by Functional Magnetic Resonance Imaging

Cosmetics are used to improve physical appearance, but the benefits may be limited to people without visual impairment. The importance of attractiveness among blind persons has not been assessed. We investigated the influence of makeup on brain activity of blind persons using functional magnetic resonance imaging (fMRI). Participants were 7 blind females (BFs) who learned to fully apply makeup and 9 mostly age-matched normally sighted females (NSFs). Brain activity was measured using fMRI before and after application of makeup and during a makeup image task in each state. In the default mode network at rest, there was no difference between the BFs and NSFs. However, a lateral visual network to the opposite side was observed in the NSFs, whereas no such network was noted in the BFs. A weak network was noted in the BFs in the occipital fusiform gyrus and temporal occipital fusiform cortex, and an extensive visual area network defect was noted. Also, activity after makeup application was significantly higher in the nucleus accumbens, pallidum, and hippocampus. Activity in the right middle cingulate gyrus, right cerebral white matter, and right anterior cingulate gyrus was higher before makeup in both BFs and NSFs, and the activity was significantly higher and more extensive in the BFs. In conclusion, applying makeup is a personally rewarding activity, even for BFs, as it strongly activates the reward system and the reward/memory system network, even in the absence of a visual area network.

AB010. The effect of visual conditioning on cortical map plasticity:a wide-field calcium imaging study

Background:Visual conditioning can refine the response of neurons in the visual cortex and higher visual and cognitive processing of a presented stimulus.This process results in increased sensitivity for that stimulus.The development of new optical imaging technology in the field of neuroscience has led to important advances,notably to better define the functional organization and plasticity of visual areas.The objective of this project is to determine the effect of daily visual conditioning with an oblique sinusoidal grating on the distribution and amplitude of cortical responses.For this,we use wide-field calcium imaging on awake mice,allowing for the observation of responses to a stimulus throughout the entire cortex in real time.Methods:C57BL/6 mice,expressing the GCaMP6s calcium reporter gene,are used to longitudinally measure neuronal activity via wide-field calcium imaging.Spontaneous activity at rest,as well as cortical responses to visual stimuli consisting of sinusoidal networks with orientation(0,30°,60°and 90°),spatial frequency(0.03,0.12,0.24 and 0.48 cpd)and contrast(100%,75%and 50%)variables are recorded to establish cortical maps,as well as tuning curves.Subsequently,the baseline function of the cortex,as well as the cortical representation of visual stimulation(30°or 90°,0.03 cpd and a contrast of 50%,75%and 100%)are studied in the animal before,during,and after daily monocular conditioning,consisting of a specific sinusoidal network(30°,0.03 cpd and 100%)over a period of 7 days.The variations in intensity and activation specificity of various visual cortical areas are calculated according to the visual conditioning and compared to an orientation stimulus for which the animal has not been conditioned(90°).Results:The cortical activation curves show a greater sensitivity of response for stimuli having horizontal or vertical gratings(0 and 90°)than for oblique gratings(30°and 60°)at low spatial frequencies(0,0.3 and 0.12 cpd).However,this trend does not occur with high spatial frequencies(0.24 and 0.48 cpd).Finally,although the intensity of activation varies in a way that is not proportional to the contrast of the stimulation,it would have no influence on the perception of the orientation of the stimuli.Conditioning at a 30°stimulus results in greater activation of the primary visual cortex and some extra-striate visual areas,as well as greater amplification of the ipsilateral cortical responses to the presentation of the visual stimuli.Conclusions:In conclusion,the results demonstrate that visual conditioning would allow for plasticity and consolidation of higher visual pathways.

Visual Basic.NET环境下存取数据库的Image字段数据

本文主要讲解在Visual Basic．NET中对数据库中特殊数据处理的一般方法，以帮助大家了解Imag字段的存取步骤和常用控件。

Visual Basic中处理SQL Server 2005的image型数据的方法

SQL Server 2005的image型数据不能通过INSERT和UPDATE等语句进行插入和更新,这给处理image型数据带来十分不便。讨论了在Visual Basic中处理SQL Server 2005的image型数据的一般方法,即利用ADO数据对象的Fields集合的AppendChunk方法和GetChunk方法及ADO Data控件进行数据的填充和读取。

Four-dimensional flow magnetic resonance imaging incirrhosis

Since its introduction in the 1970’s,magnetic resonance imaging(MRI)has become a standard imaging modality.With its broad and standardized application,it is firmly established in the clinical routine and an essential element in cardiovascular and abdominal imaging.In addition to sonography and computer tomography,MRI is a valuable tool for diagnosing cardiovascular and abdominal diseases,for determining disease severity,and for assessing therapeutic success.MRI techniques have improved over the last few decades,revealing not just morphologic information,but functional information about perfusion,diffusion and hemodynamics as well.Four-dimensional(4D)flow MRI,a time-resolved phase contrast-MRI with three-dimensional(3D)anatomic coverage and velocity encoding along all three flow directions has been used to comprehensively assess complex cardiovascular hemodynamics in multiple regions of the body.The technique enables visualization of 3D blood flow patterns and retrospective quantification of blood flow parameters in a region of interest.Over the last few years,4D flow MRI has been increasingly performed in the abdominal region.By applying different acceleration techniques,taking 4D flow MRI measurements has dropped to a reasonable scanning time of 8 to 12 min.These new developments have encouraged a growing number of patient studies in the literature validating the technique’s potential for enhanced evaluation of blood flow parameters within the liver’s complex vascular system.The purpose of this review article is to broaden our understanding of 4D flow MRI for the assessment of liver hemodynamics by providing insights into acquisition,data analysis,visualization and quantification.Furthermore,in this article we highlight its development,focussing on the clinical application of the technique.

Tolerability of magnifying narrow band imaging endoscopy for esophageal cancer screening

AIM:To compare the tolerability of magnifying narrow band imaging endoscopy for esophageal cancer screening with that of lugol chromoendoscopy.METHODS:We prospectively enrolled and analyzed 51 patients who were at high risk for esophageal cancer.All patients were divided into two groups:a magnifying narrow band imaging group,and a lugol chromoendoscopy group,for comparison of adverse symptoms.Esophageal cancer screening was performed on withdrawal of the endoscope.The primary endpoint was a score on a visual analogue scale for heartburn after the examination.The secondary endpoints were scale scores for retrosternal pain and dyspnea after the examinations,change in vital signs,total procedure time,and esophageal observation time.RESULTS:The scores for heartburn and retrosternal pain in the magnifying narrow band imaging group were significantly better than those in the lugol chromoendoscopy group(P =0.004,0.024,respectively,ANOVA for repeated measures).The increase in heart rate after the procedure was significantly greater in the lugol chromoendoscopy group.There was no significant difference between the two groups with respect to othervital sign.The total procedure time and esophageal observation time in the magnifying narrow band imaging group were significantly shorter than those in the lugol chromoendoscopy group(450 ± 116 vs 565 ± 174,P =0.004,44 ± 26 vs 151 ± 72,P < 0.001,respectively).CONCLUSION:Magnifying narrow band imaging endoscopy reduced the adverse symptoms compared with lugol chromoendoscopy.Narrow band imaging endoscopy is useful and suitable for esophageal cancer screening periodically.

Optic radiation injury in patients with aneurismal subarachnoid hemorrhage: a preliminary diffusion tensor imaging report

Visual field defect is one of the various clinical manifestations in patients with subarachnoid hemorrhage（SAH）. Little is known about the pathogenic mechanism of visual field defect in SAH. In the current study,we investigated the diffusion tensor imaging （DTI） finding of the optic radiation in patients with SAH followingrupture of a cerebral artery aneurysm. We recruited 21 patients with aneurismal SAH （12 males, 9 females, mean age, 52.67 years; range, 41–68 years） who showed no definite lesion along the visual pathway.Twenty-one age-and sex-matched normal control subjects were also recruited. DTI data were acquired at an average of 5.9 weeks （range： 3–12 weeks） after onset and reconstruction of the optic radiation was performed using DTI-Studio software. The fractional anisotropy value, apparent diffusion coefficient value,and fiber number of the optic radiation were measured. The fractional anisotropy value of the optic radiation was significantly decreased, and the apparent diffusion coefficient value was significantly increased, in patients with aneurismal SAH than in normal control subjects. However, there was no significant difference in the fiber number of the optic radiation between patients with aneurismal SAH and normal control subjects. The decrement of fractional anisotropy value and increment of apparent diffusion coefficient value of the optic radiation in patients with aneurismal SAH suggest optic radiation injury. Therefore, we recommend a thorough evaluation for optic radiation injury in patient with aneurismal SAH.

Realizing precision pulse TIG welding with arc length control and visual image sensing based weld detection

Methods of arc length control and visual image based weld detection for precision pulse TIG welding were investigated. With a particular all hardware circuit, arc voltage during peak current stage is sampled and integrated to indicate arc length, deviation of arc length and adjusting parameters are calculated and output to drive a step motor directly. According to the features of welding image grabbed with CCD camera, a special algorithm was developed to detect the central line of weld fast and accurately. Then an application system were established, whose static arc length error is ±0.1 mm with 20 A average current and 1 mm given arc length, static detection precision of weld is 0.01 mm , processing time of each image is less than 120 ms . Precision pulse TIG welding of some given thin stainless steel components with complicated curved surface was successfully realized.

Adaptive image enhancement algorithm based on fuzzy entropy and human visual characteristics

To overcome the shortcomings of the Lee image enhancement algorithm and its improvement based on the logarithmic image processing(LIP) model, this paper proposes what we believe to be an effective image enhancement algorithm. This algorithm introduces fuzzy entropy, makes full use of neighborhood information, fuzzy information and human visual characteristics.To enhance an image, this paper first carries out the reasonable fuzzy-3 partition of its histogram into the dark region, intermediate region and bright region. It then extracts the statistical characteristics of the three regions and adaptively selects the parameter αaccording to the statistical characteristics of the image’s gray-scale values. It also adds a useful nonlinear transform, thus increasing the ubiquity of the algorithm. Finally, the causes for the gray-scale value overcorrection that occurs in the traditional image enhancement algorithms are analyzed and their solutions are proposed.The simulation results show that our image enhancement algorithm can effectively suppress the noise of an image, enhance its contrast and visual effect, sharpen its edge and adjust its dynamic range.

A Visual Cryptography Based Digital Image Copyright Protection

A method for creating digital image copyright protection is proposed in this paper. The proposed method in this paper is based on visual cryptography defined by Noor and Shamir. The proposed method is working on selection of random pixels from the original digital image instead of specific selection of pixels. The new method proposed does not require that the watermark pattern to be embedded in to the original digital image. Instead of that, verification information is generated which will be used to verify the ownership of the image. This leaves the marked image equal to the original image. The method is based on the relationship between randomly selected pixels and their 8-neighbors’ pixels. This relationship keeps the marked image coherent against diverse attacks even if the most significant bits of randomly selected pixels have been changed by attacker as we will see later in this paper. Experimental results show the proposed method can recover the watermark pattern from the marked image even if major changes are made to the original digital image.

New algorithm for infrared small target image enhancement based on wavelet transform and human visual properties

The key to the wavelet based denoising teehniquea is how to manipulate the wavelet coefficients. By referring to the idea of Inclusive-OR in the design of circuits, this paper proposes a new algorithm called wavelet domain Inclusive-OR denoising algorithm（WDIDA）, which distinguishes the wavelet coefficients belonging to image or noise by considering their phases and modulus maxima simultaneously. Using this new algorithm, the denoising effects are improved and the computation time is reduced. Furthermore, in order to enhance the edges of the image but not magnify noise, a contrast nonlinear enhancing algorithm is presented according to human visual properties. Compared with traditional enhancing algorithms, the algorithm that we proposed has a better noise reducing performanee , preserving edges and improving the visual quality of images.

Dynamic Visual Image Modeling Based on Mobile RobotSelf- Organizing Network in Internetof Things Perception Layer

The dynamic multichannel binocular visual image modeling is studied based on Internet of Things (IoT) Perception Layer, using mobile robot self-organizing network. By employing multigroup mobile robots with binocular visual system, the real visual images of the object will be obtained. Then through the mobile self-organizing network, a three-dimensional model is rebuilt by synthesizing the returned images. On this basis, we formalize a novel algorithm for multichannel binocular visual three-dimensional images based on fast three-dimensional modeling. Compared with the method based on single binocular visual system, the new algorithm can improve the Integrity and accuracy of the dynamic three-dimensional object modeling. The simulation results show that the new method can effectively accelerate the modeling speed, improve the similarity and not increase the data size.