Visual Research Articles

Vision Evaluation Processes Described by Pediatric Occupational Therapists: A Qualitative Study

ABSTRACT Vision deficits can impact areas of occupation and limit one’s ability to function academically and socially, making it essential for assessing and treating children with developmental delays and acquired brain injuries. This qualitative study describes the occupational therapist’s process when completing vision evaluations in pediatric settings such as schools and early intervention, where data was analyzed utilizing thematic analysis. Twenty-one occupational therapists with at least one year of experience in pediatrics and vision evaluations who completed structured interviews were included in the study. Purposive sampling and snowball recruitment were used. Common symptoms seen with children who display visual deficits indicated by participants include headaches, double vision, and clumsiness. Common difficulties shown by children with visual deficits indicated by participants were reading, handwriting, and difficulty copying. Two themes were created based on the data analysis: exploring how OTs benefited from the partnership with optometrists when treating visual deficits and the significance of how the visual system plays in a child’s overall functioning. Pediatric OTs can be among the first team members to note concerns impacting their occupational performance. With this knowledge, OTs can help children progress academically and become more independent.

System for medical image visualization: SYFANMI

System for medical image visualization: SYFANMI

The role of surgery for optic pathway gliomas in the era of precision medicine.

Optic pathway gliomas (OPGs) represent a unique subset of brain tumours that primarily affect the paediatric population. Traditionally, these tumours are managed conservatively due to their location to and association with vital structures. This article explores the evolving role of surgery in the management of OPGs, particularly in the context of advancements in precision medicine. The advent of targeted therapy, especially for tumours with specific genetic alterations, such as BRAF V600E mutations, has revolutionized the treatment landscape, offering new avenues for patient-specific therapy. However, surgery still plays a crucial role, especially for debulking in cases of hydrocephalus or when standard therapies are ineffective. Advances in surgical techniques, including neuronavigation, endoscopic approaches, and intraoperative neurophysiological monitoring, have enhanced the safety and efficacy of operative interventions. Despite these developments, the complexity of OPGs necessitates a multidisciplinary approach, focusing on long-term outcomes and quality of life. Future research is needed to further elucidate the role of surgery in an era increasingly dominated by molecular genetics and targeted therapies.

Nonuniform and pathway-specific laminar processing of spatial frequencies in the primary visual cortex of primates

The neocortex comprises six cortical layers that play a crucial role in information processing; however, it remains unclear whether laminar processing is consistent across all regions within a single cortex. In this study, we demonstrate diverse laminar response patterns in the primary visual cortex (V1) of three male macaque monkeys when exposed to visual stimuli at different spatial frequencies (SFs). These response patterns can be categorized into two groups. One group exhibit suppressed responses in the output layers for all SFs, while the other type shows amplified responses specifically at high SFs. Further analysis suggests that both magnocellular (M) and parvocellular (P) pathways contribute to the suppressive effect through feedforward mechanisms, whereas amplification is specific to local recurrent mechanisms within the parvocellular pathway. These findings highlight the non-uniform distribution of neural mechanisms involved in laminar processing and emphasize how pathway-specific amplification selectively enhances representations of high-SF information in primate V1.

The Time-Course of Food Representation in the Human Brain.

Humans make decisions about food every day. The visual system provides important information that forms a basis for these food decisions. Although previous research has focused on visual object and category representations in the brain, it is still unclear how visually presented food is encoded by the brain. Here, we investigate the time-course of food representations in the brain. We used time-resolved multivariate analyses of electroencephalography (EEG) data, obtained from human participants (both sexes), to determine which food features are represented in the brain, and whether focused attention is needed for this. We recorded EEG while participants engaged in one of two tasks. In one task the stimuli were task relevant, whereas in the other task the stimuli were not task relevant. Our findings indicate that the brain can differentiate between food and non-food items from approximately 112 milliseconds after stimulus onset. The neural signal at later latencies contained information about food naturalness, how much the food was transformed, as well as the perceived caloric content. This information was present regardless of the task. Information about whether food is immediately ready to eat, however, was only present when the food was task relevant and presented at a slow presentation rate. Furthermore, the recorded brain activity correlated with the behavioural responses in an odd-item-out task. The fast representation of these food features, along with the finding that this information is used to guide food categorisation decision-making, suggests that these features are important dimensions along which the representation of foods is organised.Significance statement The visual domain forms an important basis for food decisions. This study sheds light on how the human brain processes food. Our results provide evidence for factors such as food naturalness, transformation level, and perceived caloric content as key organising principles in the representational structure of foods. These factors are represented rapidly in the brain and are used by participants to make food categorisation decisions. Finally, this study highlights the potential of multivariate EEG analysis as a tool for investigating food processing in the human brain.

A retrospective prognostic evaluation using unsupervised learning in the treatment of COVID-19 patients with hypertension treated with ACEI/ARB drugs

Introduction This study aimed to evaluate the prognosis of patients with COVID-19 and hypertension who were treated with angiotensin-converting enzyme inhibitor (ACEI)/angiotensin receptor B (ARB) drugs and to identify key features affecting patient prognosis using an unsupervised learning method. Methods A large-scale clinical dataset, including patient information, medical history, and laboratory test results, was collected. Two hundred patients with COVID-19 and hypertension were included. After cluster analysis, patients were divided into good and poor prognosis groups. The unsupervised learning method was used to evaluate clinical characteristics and prognosis, and patients were divided into different prognosis groups. The improved wild dog optimization algorithm (IDOA) was used for feature selection and cluster analysis, followed by the IDOA-k-means algorithm. The impact of ACEI/ARB drugs on patient prognosis and key characteristics affecting patient prognosis were also analysed. Results Key features related to prognosis included baseline information and laboratory test results, while clinical symptoms and imaging results had low predictive power. The top six important features were age, hypertension grade, MuLBSTA, ACEI/ARB, NT-proBNP, and high-sensitivity troponin I. These features were consistent with the results of the unsupervised prediction model. A visualization system was developed based on these key features. Conclusion Using unsupervised learning and the improved k-means algorithm, this study accurately analysed the prognosis of patients with COVID-19 and hypertension. The use of ACEI/ARB drugs was found to be a protective factor for poor clinical prognosis. Unsupervised learning methods can be used to differentiate patient populations and assess treatment effects. This study identified important features affecting patient prognosis and developed a visualization system with clinical significance for prognosis assessment and treatment decision-making.

SLM-SLAM: A Visual SLAM System Based on Segmented Large-Scale Model in Dynamic Scenes and Zero-shot Conditions

Abstract In the real world, the presence of various dynamic objects can impact the localization accuracy of the majority of typical Visual Simultaneous Localization and Mapping (VSLAM) systems. Simultaneously, many dynamic VSLAM systems based on neural networks require pre-training for specific application scenarios. We present SLM-SLAM, the first VSLAM system that implements zero-shot processing of dynamic scenes. It achieves the capability to handle various dynamic objects without the necessity for pre-training, enabling straightforward adaptation to different application scenarios. Firstly, we designed an open-world semantic segmentation module based on a segmented large-scale model to acquire semantic information in the scene. Subsequently, we devised a label-based strategy for selecting feature points, jointly optimizing poses with the weighted labels provided by both semantic and geometric information. Finally, we refined the keyframe selection strategy of ORB-SLAM3 to prevent matching errors caused by an insufficient number of remaining static feature points in the scene. We conducted experiments on the TUM dataset, the KITTI dataset, and real world scenarios. The results indicate that in dynamic scenes, our SLM-SLAM significantly improves localization accuracy compared to ORB-SLAM3, and its performance is comparable to state-of-the-art dynamic VSLAM systems.

Selection drives divergence of eye morphology in sympatric Heliconius butterflies.

When populations experience different sensory conditions, natural selection may favor sensory system divergence, affecting peripheral structures and/or downstream neural pathways. We characterized the outer eye morphology of sympatric Heliconius species from different forest types and their first-generation reciprocal hybrids to test for adaptive visual system divergence and hybrid disruption. In Panama, Heliconius cydno occurs in closed forests, whereas Heliconius melpomene resides at the forest edge. Among wild individuals, H. cydno has larger eyes than H. melpomene, and there are heritable, habitat-associated differences in the visual brain structures that exceed neutral divergence expectations. Notably, hybrids have intermediate neural phenotypes, suggesting disruption. To test for similar effects in the visual periphery, we reared both species and their hybrids in common garden conditions. We confirm that H. cydno has larger eyes and provide new evidence that this is driven by selection. Hybrid eye morphology is more H. melpomene-like despite body size being intermediate, contrasting with neural trait intermediacy. Overall, our results suggest that eye morphology differences between H. cydno and H. melpomene are adaptive, and that hybrids may suffer fitness costs due to a mismatch between the peripheral visual structures and previously described neural traits that could affect visual performance.

Adaptive display white point under various ambient conditions

AbstractDisplay technologies have been developed to adjust the display brightness and color under different viewing conditions, providing better viewing experiences to users. Solutions have been proposed to adjust the display white point according to the ambient light condition, which roots into the underlying chromatic adaptation mechanism in the human visual system. This study was carefully designed to reveal the necessity to consider the ambient light level and display luminance together, which affects the viewing mode, when adjusting the adaptive display white point. The results clearly suggested that when the display luminance was greater than the ambient light diffuse white luminance, the display was viewed in the self‐luminous mode and the display white point was not significantly affected by the ambient light chromaticities. In contrast, when the display luminance was lower than the ambient light diffuse white luminance, the display was viewed in the surface mode and the ambient light chromaticities had a significant effect on the display white point, especially when the surround ratio was high.

ADVANCED SHOPLIFTING PREVENTION AND ALERT STSYEM

Detecting human beings accurately in a visual surveillance system is crucial for diverse application areas including abnormal event detection, human gait characterization, congestion analysis, person identification, gender classification and fall detection for elderly people. The first step of the detection process is to detect an object which is in motion. Object detection could be performed using YOLOv7, optical flow and spatio-temporal filtering techniques. Once detected, a moving object could be classified as a human being using shape-based, texture-based or motion-based features. A comprehensive review with comparisons on available techniques for detecting human beings in surveillance videos is presented in this paper. The characteristics of few benchmark datasets as well as the future research directions on human detection have also been discussed. We can use camera for Human Motion Detection. The Camera is used to catch the live images of the area in which it is being implemented, if any object is moving. The captured images are stored for further work. If motion is found in this video, the computer will start recording, buzz an alarm and send SMS to people listed in its database. In this way the system will provide the security against any misdeed. Keywords: YOLOv7, SMS, E-mail, CCTV, SMTP, RFID

Blind Quality Assessment of Dense 3D Point Clouds with Structure Guided Resampling

Objective quality assessment of 3D point clouds is essential for the development of immersive multimedia systems in real-world applications. Despite the success of perceptual quality evaluation for 2D images and videos, blind/no-reference metrics are still scarce for 3D point clouds with large-scale irregularly distributed 3D points. Therefore, in this paper, we propose an objective point cloud quality index with Structure Guided Resampling (SGR) to automatically evaluate the perceptually visual quality of dense 3D point clouds. The proposed SGR is a general-purpose blind quality assessment method without the assistance of any reference information. Specifically, considering that the human visual system (HVS) is highly sensitive to structure information, we first exploit the unique normal vectors of point clouds to execute regional pre-processing which consists of keypoint resampling and local region construction. Then, we extract three groups of quality-related features, including: 1) geometry density features; 2) color naturalness features; 3) angular consistency features. Both the cognitive peculiarities of the human brain and naturalness regularity are involved in the designed quality-aware features that can capture the most vital aspects of distorted 3D point clouds. Extensive experiments on several publicly available subjective point cloud quality databases validate that our proposed SGR can compete with state-of-the-art full-reference, reduced-reference, and no-reference quality assessment algorithms.

Heads-up 3-Dimensional Visualization to Enhance Video Endoscopy During Vitreoretinal Surgery

Purpose: To describe 2 cases in which video endoscopy was combined with heads-up 3-dimensional (3D) visualization. Methods: The imaging modalities of the heads-up 3D visualization system and video endoscopy were combined by converting the endoscope’s S-Video output into a high-definition multimedia interface. The technique was used in 2 cases that included lens dislocation and endophthalmitis. Results: In the 2 cases, the heads-up split-screen view simplified the surgical setup. Simultaneously viewing the endoscopic image and widefield 3D image anecdotally appeared to improve ergonomics, help keep the probe oriented, and assist in guiding surgical movements endoscopically. Conclusions: These cases show the advantages of a heads-up 3D system to simultaneously view endoscopic and widefield images during ophthalmic endoscopy in vitreoretinal surgery.

Uncommon opsin’s retinal isomer is involved in mammalian sperm thermotaxis

In recent years it became apparent that, in mammals, rhodopsin and other opsins, known to act as photosensors in the visual system, are also present in spermatozoa, where they function as highly sensitive thermosensors for thermotaxis. The intriguing question how a well-conserved protein functions as a photosensor in one type of cells and as a thermosensor in another type of cells is unresolved. Since the moiety that confers photosensitivity on opsins is the chromophore retinal, we examined whether retinal is substituted in spermatozoa with a thermosensitive molecule. We found by both functional assays and mass spectrometry that retinal is present in spermatozoa and required for thermotaxis. Thus, starvation of mice for vitamin A (a precursor of retinal) resulted in loss of sperm thermotaxis, without affecting motility and the physiological state of the spermatozoa. Thermotaxis was restored after replenishment of vitamin A. Using reversed-phase ultra-performance liquid chromatography mass spectrometry, we detected the presence of retinal in extracts of mouse and human spermatozoa. By employing UltraPerformance convergence chromatography, we identified a unique retinal isomer in the sperm extracts—tri-cis retinal, different from the photosensitive 11-cis isomer in the visual system. The facts (a) that opsins are thermosensors for sperm thermotaxis, (b) that retinal is essential for thermotaxis, and (c) that tri-cis retinal isomer uniquely resides in spermatozoa and is relatively thermally unstable, suggest that tri-cis retinal is involved in the thermosensing activity of spermatozoa.

Bio-inspired foveal super-resolution method for multi-focal-length images based on local gradient constraints

Most existing super-resolution (SR) imaging systems, inspired by the bionic compound eye, utilize image registration and reconstruction algorithms to overcome the angular resolution limitations of individual imaging systems. This article introduces a multi-aperture multi-focal-length imaging system and a multi-focal-length image super-resolution algorithm, mimicking the foveal imaging of the human eye. Experimental results demonstrate that with the proposed imaging system and an SR imaging algorithm inspired by the human visual system, the proposed method can enhance the spatial resolution of the foveal region by up to 4 × compared to the original acquired image. These findings validate the effectiveness of the proposed imaging system and computational imaging algorithm in enhancing image texture and spatial resolution.

Spatial–Temporal Analysis-Based Video Quality Assessment: A Two-Stream Convolutional Network Approach

In system processing, video inevitably suffers from distortion, which leads to quality degradation and affects the user experience. Therefore, it is of great importance to design an accurate and effective objective video quality assessment (VQA) method. In this paper, by considering the multi-dimensional characteristics for video and visual perceptual mechanism, a two-stream convolutional network for VQA is proposed based on spatial–temporal analysis, named TSCNN-VQA. Specifically, for feature extraction, TSCNN-VQA first extracts spatial and temporal features by two different convolutional neural network branches, respectively. After that, the spatial–temporal joint feature fusion is constructed to obtain the joint spatial–temporal features. Meanwhile, the TSCNN-VQA also integrates an attention module to guarantee that the process conforms to the mechanism that the visual system perceives video information. Finally, the overall quality is obtained by non-linear regression. The experimental results in both the LIVE and CSIQ VQA datasets show that the performance indicators obtained by TSCNN-VQA are higher than those of existing VQA methods, which demonstrates that TSCNN-VQA can accurately evaluate video quality and has better consistency with the human visual system.

The Development of Socially Directed Attention: An Functional Magnetic Resonance Imaging Study in Infant Monkeys.

Socially guided visual attention, such as gaze following and joint attention, represents the building block of higher-level social cognition in primates, although their neurodevelopmental processes are still poorly understood. Atypical development of these social skills has served as early marker of autism spectrum disorder and Williams syndrome. In this study, we trace the developmental trajectories of four neural networks underlying visual and attentional social engagement in the translational rhesus monkey model. Resting-state fMRI (rs-fMRI) data and gaze following skills were collected in infant rhesus macaques from birth through 6 months of age. Developmental trajectories from subjects with both resting-state fMRI and eye-tracking data were used to explore brain-behavior relationships. Our findings indicate robust increases in functional connectivity (FC) between primary visual areas (primary visual cortex [V1] - extrastriate area 3 [V3] and V3 - middle temporal area, ventral motion areas middle temporal area - AST, as well as between TE and amygdala (AMY) as infants mature. Significant FC decreases were found in more rostral areas of the pathways, such as areas temporal area occipital part - TE in the ventral object pathway, V3 - lateral intraparietal (LIP) of the dorsal visual attention pathway and V3 - temporo-parietal area of the ventral attention pathway. No changes in FC were found between cortical areas LIP-FEF and temporo-parietal area - Area 12 of the dorsal and ventral attention pathways or between AST-AMY and AMY-insula. Developmental trajectory of gaze following revealed a period of dynamic changes with gradual increases from 1 to 2 months, followed by slight decreases from 3 to 6 months. Exploratory association findings across the 6-month period showed that infants with higher gaze following had lower FC between primary visual areas V1-V3, but higher FC in the dorsal attention areas V3-LIP, both in the right hemisphere. Together, the first 6 months of life in rhesus macaques represent a critical period for the emergence of gaze following skills associated with maturational changes in FC of socially guided attention pathways.

Calibration method for binocular vision system with large field of view based on small target image splicing

In vision measurement, camera calibration has a significant impact on measurement precision. The classical target-based calibration methods require the target to occupy more than one-third of the field of view. A small-size target that does not meet the requirements results in poor calibration accuracy, while an appropriate large-size target is difficult to manufacture and inconvenient to operate. In view of the above problem, we propose a flexible and accurate calibration method based on small target image splicing to calibrate the binocular vision system with a large field of view. The spliced images and virtual large targets are constructed to extend the target size, providing better flexibility for calibration. Moreover, an optimization objective function integrating two constraints in the imaging plane and measurement space is presented to improve the calibration accuracy during the parameter optimization process. The simulation experiments and actual experiments are carried out to test the performance of the proposed method. The results demonstrate that the calibration accuracy of the proposed method using a small target is equivalent to that of Zhang’s method using a large target. Additionally, when using a same-size target, the parameter error of the proposed method is less than that of Zhang’s method, and the proposed method reduces the distance measurement error from 1.169 mm to 0.208 mm compared to Zhang’s method.

A nasal chemosensation–dependent critical window for somatosensory development

Nasal chemosensation is considered the evolutionarily oldest mammalian sense and, together with somatosensation, is crucial for neonatal well-being before auditory and visual pathways start engaging the brain. Using anatomical and functional approaches in mice, we reveal that odor-driven activity propagates to a large part of the cortex during the first postnatal week and enhances whisker-evoked activation of primary whisker somatosensory cortex (wS1). This effect disappears in adult animals, in line with the loss of excitatory connectivity from olfactory cortex to wS1. By performing neonatal odor deprivation, followed by electrophysiological and behavioral work in adult animals, we identify a key transient regulation of nasal chemosensory information necessary for the development of wS1 sensory-driven dynamics and somatosensation. Our work uncovers a cross-modal critical window for nasal chemosensation–dependent somatosensory functional maturation.

Eye development influences horn size but not patterning in horned beetles.

Understanding the origin of novel morphological traits is a long-standing objective in evolutionary developmental biology. We explored the developmental genetic mechanisms that underpin the formation of a textbook example of evolutionary novelties, the cephalic horns of beetles. Previous work has implicated the gene regulatory networks associated with compound eye and ocellar development in horn formation and suggested that horns and compound eyes may influence each other's sizes. Therefore, we investigated the functional significance of genes central to visual system formation in the initiation, patterning, and size determination of head horns across three horned beetle species. We find that while the downregulation of canonical eye patterning genes reliably reduces or eliminates compound eye formation, it does not alter the position or shape of head horns yet does result in an increase in relative horn length. We discuss the implications of our results for our understanding of the genesis of cephalic horns in particular and evolutionary novelties in general.

Semantic scene segmentation for indoor autonomous vision systems: leveraging an enhanced and efficient U-NET architecture

Semantic scene segmentation for indoor autonomous vision systems: leveraging an enhanced and efficient U-NET architecture