Images Of Body Parts Research Articles

Distributed network flows generate localized category selectivity in human visual cortex.

A central goal of neuroscience is to understand how function-relevant brain activations are generated. Here we test the hypothesis that function-relevant brain activations are generated primarily by distributed network flows. We focused on visual processing in human cortex, given the long-standing literature supporting the functional relevance of brain activations in visual cortex regions exhibiting visual category selectivity. We began by using fMRI data from N = 352 human participants to identify category-specific responses in visual cortex for images of faces, places, body parts, and tools. We then systematically tested the hypothesis that distributed network flows can generate these localized visual category selective responses. This was accomplished using a recently developed approach for simulating - in a highly empirically constrained manner - the generation of task-evoked brain activations by modeling activity flowing over intrinsic brain connections. We next tested refinements to our hypothesis, focusing on how stimulus-driven network interactions initialized in V1 generate downstream visual category selectivity. We found evidence that network flows directly from V1 were sufficient for generating visual category selectivity, but that additional, globally distributed (whole-cortex) network flows increased category selectivity further. Using null network architectures we also found that each region's unique intrinsic "connectivity fingerprint" was key to the generation of category selectivity. These results generalized across regions associated with all four visual categories tested (bodies, faces, places, and tools), and provide evidence that the human brain's intrinsic network organization plays a prominent role in the generation of functionally relevant, localized responses.

Relative efficacy of cigarillo warning statements in text and pictorial formats: An experimental study among a sample of US young adults.

Health warning labels (HWLs) communicate the health risks of cigar use and can decrease use when on cigar packages. This study assessed the relative efficacy of six FDA-proposed individual warning statements in text and pictorial format. A sample of young adults (ages 18-29) were randomized to a text or pictorial warning condition on generic cigarillo packages. The warning statements were about lung cancer and heart disease; cancers of the mouth and throat; secondhand smoke; not a safe alternative; nicotine/addiction; and harm to baby. Negative emotional reactions, cognitive elaboration, and perceived message effectiveness (PME) were assessed for each warning using linear mixed models. Of the 661 participants, 47.3% reported ever cigarillo smoking, 32.7% current smoking, and 20% were susceptible. In the pictorial format, cancers of the mouth and throat elicited lower levels of anxiety compared to secondhand smoke, not a safe alternative, nicotine/addiction, and harm to baby (ps<0.001). Pictorial HWLs with human imagery induced high anxiety, sadness, fear, and guilt reactions (p<0.001) and higher PME (p=0.011) compared to pictorial HWLs with diseased body parts. Compared to the text HWL cancers of the mouth and throat, the text HWL harm to baby elicited higher anxiety (p=0.003), sadness (p=0.002) and PME (p<0.001). Pictorial HWLs depicting people or human imagery, rather than images of diseased organs or body parts, to represent health effects elicited the most negative emotional reactions, such as anxiety and guilt, and higher PME. Including such images and texts highlighting effects on vulnerable populations like babies can better communicate cigarillo health risks, aiming to curb cigarillo use among young people. The study suggests that pictorial health warning labels (HWLs) with human imagery significantly enhance the communication of cigarillo smoking risks compared to images of diseased organs. These HWLs evoke stronger emotional responses, particularly anxiety and guilt, and higher perceived message effectiveness by depicting a recognizable person. Furthermore, text-only warnings describing the smoking effect on vulnerable populations such as babies might have a higher impact on young adults. This evidence supports a strategic shift in FDA policies to include such impactful images and texts, which could potentially lead to a significant reduction in cigarillo use among young people. Our findings underscore the urgent need for continued research and implementation of these enhanced warning labels to improve public health outcomes.

A Study on GAN-Based Car Body Part Defect Detection Process and Comparative Analysis of YOLO v7 and YOLO v8 Object Detection Performance

The main purpose of this study is to generate defect images of body parts using a GAN (generative adversarial network) and compare and analyze the performance of the YOLO (You Only Look Once) v7 and v8 object detection models. The goal is to accurately judge good and defective products. Quality control is very important in the automobile industry, and defects in body parts directly affect vehicle safety, so the development of highly accurate defect detection technology is essential. This study ensures data diversity by generating defect images of car body parts using a GAN and through this, compares and analyzes the object detection performance of the YOLO v7 and v8 models to present an optimal solution for detecting defects in car parts. Through experiments, the dataset was expanded by adding fake defect images generated by the GAN. The performance experiments of the YOLO v7 and v8 models based on the data obtained through this approach demonstrated that YOLO v8 effectively identifies objects even with a smaller amount of data. It was confirmed that defects could be detected. The readout of the detection system can be improved through software calibration.

Lesions Causing Alice in Wonderland Syndrome Map to a Common Brain Network Linking Body and Size Perception

ObjectiveAlice in Wonderland syndrome (AIWS) profoundly affects human perception of size and scale, particularly regarding one's own body and the environment. Its neuroanatomical basis has remained elusive, partly because brain lesions causing AIWS can occur in different brain regions. Here, we aimed to determine if brain lesions causing AIWS map to a distributed brain network.MethodsA retrospective case–control study analyzing 37 cases of lesion‐induced AIWS identified through systematic literature review was conducted. Using resting‐state functional connectome data from 1,000 healthy individuals, the whole‐brain connections of each lesion were estimated and contrasted with those from a control dataset comprising 1,073 lesions associated with 25 other neuropsychiatric syndromes. Additionally, connectivity findings from lesion‐induced AIWS cases were compared with functional neuroimaging results from 5 non‐lesional AIWS cases.ResultsAIWS‐associated lesions were located in various brain regions with minimal overlap (≤33%). However, the majority of lesions (≥85%) demonstrated shared connectivity to the right extrastriate body area, known to be selectively activated by viewing body part images, and the inferior parietal cortex, involved in size and scale judgements. This pattern was uniquely characteristic of AIWS when compared with other neuropsychiatric disorders (family‐wise error‐corrected p &lt; 0.05) and consistent with functional neuroimaging observations in AIWS due to nonlesional causes (median correlation r = 0.56, interquartile range 0.24).InterpretationAIWS‐related perceptual distortions map to one common brain network, encompassing regions critical for body representation and size‐scale processing. These findings lend insight into the neuroanatomical localization of higher‐order perceptual functions, and may inform future therapeutic strategies for perceptual disorders. ANN NEUROL 2024;96:662–674

Natural scenes reveal diverse representations of 2D and 3D body pose in the human brain

Human pose, defined as the spatial relationships between body parts, carries instrumental information supporting the understanding of motion and action of a person. A substantial body of previous work has identified cortical areas responsive to images of bodies and different body parts. However, the neural basis underlying the visual perception of body part relationships has received less attention. To broaden our understanding of body perception, we analyzed high-resolution fMRI responses to a wide range of poses from over 4,000 complex natural scenes. Using ground-truth annotations and an application of three-dimensional (3D) pose reconstruction algorithms, we compared similarity patterns of cortical activity with similarity patterns built from human pose models with different levels of depth availability and viewpoint dependency. Targeting the challenge of explaining variance in complex natural image responses with interpretable models, we achieved statistically significant correlations between pose models and cortical activity patterns (though performance levels are substantially lower than the noise ceiling). We found that the 3D view-independent pose model, compared with two-dimensional models, better captures the activation from distinct cortical areas, including the right posterior superior temporal sulcus (pSTS). These areas, together with other pose-selective regions in the LOTC, form a broader, distributed cortical network with greater view-tolerance in more anterior patches. We interpret these findings in light of the computational complexity of natural body images, the wide range of visual tasks supported by pose structures, and possible shared principles for view-invariant processing between articulated objects and ordinary, rigid objects.

Simple Hybrid Camera-Based System Using Two Views for Three-Dimensional Body Measurements

Using a single RGB camera to obtain accurate body dimensions, rather than measuring these manually or via more complex multicamera systems or more expensive 3D scanners, has a high application potential for the apparel industry. We present a system that estimates upper human body measurements using a hybrid set of techniques from both classic computer vision and recent machine learning. The main steps involve (1) using a camera to obtain two views (frontal and side); (2) isolating in the image pair a set of main body parts; (3) improving the image quality; (4) extracting body contours and features from the images of body parts; (5) indicating markers on these images; (6) performing a calibration step; and (7) producing refined final 3D measurements. We favour a unique geometric shape, that of an ellipse, to approximate human body main horizontal cross-sections. We focus on the more challenging parts of the body, i.e., the upper body from the head to the hips, which, we show, can be well represented by varying an ellipse’s eccentricity for each individual. Then, evaluating each fitted ellipse’s perimeter allows us to obtain better results than the current state-of-the-art methods for use in the fashion and online retail industry. In our study, we selected a set of two equations, out of many other possible choices, to best estimate upper human body section circumferences. We experimented with the system on a diverse sample of 78 female participants. The results for the upper human body measurements in comparison to the traditional manual method of tape measurements, when used as a reference, show ±1 cm average differences, which are sufficient for many applications, including online retail.

(Re)sounding Audre Lorde: Queer Crip Chorus in Lana Lin’s Experimental Documentary

This article discusses the artist, filmmaker, and writer Lana Lin’s “revisioning” of Audre Lorde’s The Cancer Journals (1980) to consider how the poetic encounter between two artists from different generations exemplifies the relational praxis that Lorde pursued throughout her life. In revealing the ways in which Lorde opens acoustic sensory spaces for contemporary readers and listeners of her work, I specifically focus on the political and aesthetic dynamic of recitation in Lin’s experimental documentary The Cancer Journals Revisited (2018). I trace how recitation becomes a coalitional practice of feminist chorus through which readers and listeners embody the sonorous space they co-create through and with Lorde. The article further looks into the ways Lin pairs recitation performance with visceral images of body parts on the screen to argue that the film’s visuals dwell in and extend the form of the chorus; which is to say, the film expands the meaning and practice of chorus beyond the realm of the sonic. The bodies on the screen extend the chorus, immersing the audience in a participatory rethinking of the experience of cancer (particularly breast cancer) not merely as an individual misfortune or an aesthetic concern. In adjoining textual, visual, and acoustic elements, Lin’s film provides a powerful transformative sensory environment, reverberating through the reciters and the audience.

Identification and relative depth estimation in natural images of single human body parts

Identification and relative depth estimation in natural images of single human body parts

Body Correlation Network for Person Re-Identifications

&lt;p&gt;Visual information accounts for approximately 80 to 85 percent of the information available daily in modern cities. As such, person re-identification, an instance-level image retrieval task, has become an important research topic in computer vision, machine learning, and other fields in recent years. Traditional person re-identification methods based on convolutional neural networks only extract the global feature information of people. Thus, when external factors such as changes in occlusion and illumination disturb people, the recognition performance of these methods substantially decreases. We therefore develop body correlation network (BC-Net), which takes full advantage of images of body parts and the correlations between them. Specifically, BC-Net uses body part feature information and correlation feature information as nodes and edges, respectively, and then uses graph convolutions to learn the overall topology of people. To improve use of crucial feature information, we also design a unique method of propagation between nodes and edges. We conduct extensive comparative experiments on the Market-1501 and DukeMTMC-reID datasets, and the results demonstrate that BC-Net outperforms other state-of-the-art techniques.&lt;/p&gt; &lt;p&gt;&amp;nbsp;&lt;/p&gt;

Eight new species of the genus Nesamblyops Jeannel (Anillini: Carabidae: Coleoptera) from New Zealand with notes about dispersal of the genus to the North Island

Species of flightless litter ground beetles of the tribe Anillini, genus Nesamblyops, from the North Island and from the north-eastern part of the South Island are revised. Eight new species are described and one previously known species, Nesamblyops oreobius (Broun), is re-described. Nesamblyops oreobius, the only hitherto recorded species from the North Island, is most similar to the group of two new species from the South Island, N. confusus n. sp. (type locality: New Zealand, Marlborough Sounds, Mount Stokes) and N. lescheni n. sp. (type locality: New Zealand, Marlborough Sounds, D'Urville Island), based on the structure of the male genitalia. The second species of the genus known from the North Island, N. tararua n. sp. (type locality: New Zealand, Wellington, Tararua Range) represents another lineage, based on the structure of the male genitalia, and is closely related to a group of three new species from the South Island, N. brouni n. sp. (type locality: New Zealand, Canterbury, Southern Alps, Lewis Pass), N. distinctus n. sp. (type locality: New Zealand, Marlborough, Richmond Range, Fabians Valley), and N. townsendi n. sp. (type locality: New Zealand, Marlborough Sounds, Tennyson Inlet). Nesamblyops carltoni n. sp. (type locality: New Zealand, Nelson, Richmond Range, Dun Mountain) and N. parvulus n. sp. (type locality: New Zealand, Marlborough Sounds, Mount Stokes), both from the South Island occupy an isolated position among the examined species. All species are illustrated with digital images of habitus, body parts, and drawings of genitalia. Distribution maps for all species are also provided. Geographical evidence of Nesamblyops dispersal to the North Island is discussed, based on distributional data.

Suspicious Object Detection for Millimeter-Wave Images with Multi-View Fusion Siamese Network.

Millimeter-wave (MMW) imaging techniques have been widely used in the public security industries for their under-controlled privacy concerns and no health hazards. However, since MMW images are low resolution and most objects are small, reflection-weak, diverse, suspicious object detection in the MMW images is a very challenging task. This paper develops a robust suspicious object detector for the MMW images based on the Siamese network integrated with the pose estimation and image segmentation, which estimates the coordinates of human joints and segments the complete human images into symmetrical body part images. Unlike most existing detectors, which detect and recognize suspicious objects in MMW images and require a complete training set with correct annotations, our proposed model aims to learn the similarity between two symmetrical human body part images segmented from the complete MMW images. Furthermore, to decrease the misdetection caused by the restricted field of view, we further fuse the multi-view MMW images observed from the same person by designing a decision-level fusion strategy and feature-level fusion strategy based on the attention mechanism. Experimental results on the measured MMW images show that our proposed models have favorable detection accuracy and speed in practical application and thus prove their effectiveness.

Increased insula and amygdala activity during selective attention for negatively valenced body parts in binge eating disorder.

Previous studies indicate that participants with eating disorders show an attentional bias for the negatively valenced body parts of their own body. However, the neural basis underlying these processes has not been investigated. We conducted a preregistered combined functional MRI (fMRI)/eye tracking study and presented 35 women with binge eating disorder (BED) and 24 weight-matched control subjects (CG) with body part images of their own body and a weight-matched unknown body. After the fMRI examination, participants rated the attractiveness of the presented body parts. As expected, women with BED responded with significantly higher insula and amygdala activity when viewing the negatively valenced body parts of their own body (compared to all other combinations). However, individuals with BED did not deviate from the CG in the processing of these stimuli in the ventromedial prefrontal cortex, the extrastriate body area or the fusiform body area. Our results indicate that the negative valued body parts carry a particularly strong emotional valence in individuals with BED. These results further emphasize the relevance of processing bias for negatively valenced body parts in the pathology of BED. (PsycInfo Database Record (c) 2022 APA, all rights reserved).

Incorporating deep learning into capacitive images for smartphone user authentication

We incorporate deep learning techniques into capacitive images of body parts (ear, four fingers, and thumb) to improve the performance of user authentication in smartphones. Use of a capacitive touchscreen as an image sensor has several advantages, such as it is less sensitive to poor illumination conditions, occlusions, and pose variations. Also, it does not need an additional hardware like iris or fingerprint scanner. Use of capacitive images for user authentication is not new. However, the performance, specially, false reject rates (FRRs) of the state-of-the-art capacitive image-based systems are poor. In this paper, we focus on improving the performance and leverage deep learning. Deep learning techniques demonstrated spectacular performance in previous physical biometrics-based research. However, to our knowledge, effectiveness of deep learning is still unexplored in capacitive touchscreen-based user authentication. In order to bridge this research gap, we devise a multi-modal deep learning model, namely UASNet, and compare its performance with a large set of uni- and multi-modal baselines. Using the UASNet, we achieve an accuracy of 99.77%, an EER of 0.48%, and an FRR of 1.19% at FAR of 0.06%.

Recognition of Human Body Members and Movements For Kindergarten Kids Based on Android

&lt;p&gt;&lt;em&gt;Learning media needs to be used as a supporter of material delivery to reduce failure in communication and maximize the ongoing process of teaching and learning. Early Childhood Education is in dire need of learning media. With android technology based on android smartphones, learning media becomes more interesting, easier and not boring to learn anywhere and anytime. Learning media in android smartphones are better known as learning applications. The MDLC method is an appropriate method in designing and developing a multimedia application which is a combination of image, sound, video, animation and other media. The MDLC method has six stages as follows: Concept, Design, Material Collecting, Assembly, Testing and Distribution. Recognition of Human Body Members and Movements for Kindergarten Children Based on Android. This application is made using the Android Studio programming language as a medium for making and other supporting software to create images of human body parts. The results of developing educational applications as learning media for early childhood can help in understanding and studying each member of their body.&lt;/em&gt;&lt;strong&gt;&lt;/strong&gt;&lt;/p&gt;

Objects with motor valence affect the visual processing of human body parts: Evidence from behavioural and ERP studies

Recent findings indicate that the mental representation of an object contains crucial information about the motor interactions relevant for its intended functional use, suggesting a possible action-specific link with body effectors. For example, in the visual system, the extrastriate body area (EBA) responds to full body and body part images according to a functional/semantic organizational principle. However, the pliancy of the relationship between objects and body parts remains under-investigated. The present study aims to i) investigate this relationship more directly by assessing whether recognition of specific body parts can be facilitated by a brief exposure to functionally-related objects (Experiment 1) and ii) whether the functional relationship between objects and body parts modulates a posterior body-sensitive ERP waveform, peaking around 200 msec, and the more centro-parietal P300, linked to item categorization processes and visual awareness (Experiment 2). Participants were asked to quickly recognize targets (pictures of hands or feet) preceded by a functionally related (e.g., drum for hand target), unrelated (e.g., drum for foot target), or neutral (e.g., unknown object for both targets) prime. Findings showed that participants’ performance was significantly more accurate with related than unrelated primes and that ERP amplitudes were modulated by the relationship between the prime and the target. These findings confirm the existence of action-specific links between objects and body parts and expand on recent findings on categorical organization of neural responses to human effectors in the visual system.

Description of ticks species from Rattus tiomanicus in Mangrove Forests through scanning electron microscopy

Ticks are ill-famed vectors of many pathogenic organisms which can cause various diseases and life-threatening illnesses to animals and humans. Each tick’s species and its life stages have distinct morphological features that can permit them to be accurately identified. However, the use of conventional stereo microscopes limits the accuracy of species identification. The taxonomy of ticks, in general, is not much understood and existing information is based on sparse morphology data. Thus, this study aims to examine and describe the morphological characteristics of different species of ticks collected on rodents in mangrove forests using scanning electron microscopy (SEM). This method renders high-quality images of body parts of ticks. Five different morphospecies of ticks from one host species (Rattus tiomanicus) were examined under SEM, followed by the PCR technique using mitochondrial 16S rDNA gene for species validation. This study revealed that the ticks belong to five species: Dermacentor auratus, Ixodes granulatus, Haemaphysalis hystricis, D. atrosignatus and Amblyomma cordiferum. The combination of stereomicroscopic and SEM methods has improved our understanding of the morphological characteristics of different tick species, hence establishing up-to-date taxonomic keys for these species. Moreover, due to the lack of taxonomic keys on the immature stage of ticks, the SEM method is essential in characterising the morphological features of these stages in detail, subsequently helpful in revising the taxonomic keys for certain ticks species.

P 3 Mental rotation performance in patients with focal dystonia is associated with their cognitive state

Introduction: Mental rotation (MR) of body parts is based on the imagination of actual movements. It is assumed to require activation of brain areas responsible for planning and execution of movements. From previous studies with partly contradictory results, it is still unclear whether patients (pts) with idiopathic focal dystonia have an impairment of MR of body parts. We investigated MR of body parts and non-corporal objects in pts with cervical dystonia (CD) and blepharospasm (BS) and assessed potential confounders of MR performance like cognitive deficits. Patients and Methods: 23 pts with CD and 23 healthy subjects as well as 21 pts with BS and 19 pts with hemifacial spasm (HS) were compared. Matched groups did not differ significantly regarding gender distribution, age, or duration of schooling. Besides handedness, dexterity and general reaction time, cognitive status was assessed using the Montreal Cognitive Assessment (MoCA). Severity of diseases was evaluated by using the Toronto Western Spasmodic Torticollis Rating Scale, Blepharospasm severity scale, Blepharospasm disability index and Jancovic rating scale. In the MR test, photographs of body parts (head, hand, or foot) and other objects such as cars were presented on a screen. Images of the head had a black mark on either the right or left eye, the car had a black mark on either the right or left headlight. The images were presented at six different angles rotated around their own axis. Subjects were asked to select by keystroke whether the right or left hand/foot/headlight was marked. Both speed and correctness of responses were evaluated. For statistical analysis, mixed ANOVA and Spearman-Rho correlation coefficient were applied. Results: In the MR test, pts with CD showed a significantly longer reaction time (RT) compared to healthy controls for both body parts and non-corporal objects (p=0.003, p=0.027). There was no significant difference concerning accuracy except for cars (p=0.048). Furthermore, pts with CD achieved a significantly lower score in the MoCA test compared to controls (p<0.001). Negative correlations were found between MoCA results and RTs in the MR test for all items (hand: r=-0.434, p<0.001, foot: r=-0.419, p<0.001, head: r=-0.363, p=0.001, cars: r=-0.425, p<0.001), whereas there was no correlation between severity of diseases and RTs. No significant differences were observed between pts with B and HS. Conclusion: In our study, prolonged RTs in pts with CD in the MR task are not limited to images of body parts. Rather, we found a significant association of MR performance with cognitive fitness. However, it remains unclear whether increased RTs in pts result from cognitive deficits or from dystonia itself. The former would be supported by the lack of difference in the MR task between BS and HS, whose MoCA results did not differ. Future studies should investigate MR performance in dystonia pts and subjects with comparable cognitive state.

Features and Extra-Striate Body Area Representations of Diagnostic Body Parts in Anger and Fear Perception.

Social species perceive emotion via extracting diagnostic features of body movements. Although extensive studies have contributed to knowledge on how the entire body is used as context for decoding bodily expression, we know little about whether specific body parts (e.g., arms and legs) transmit enough information for body understanding. In this study, we performed behavioral experiments using the Bubbles paradigm on static body images to directly explore diagnostic body parts for categorizing angry, fearful and neutral expressions. Results showed that subjects recognized emotional bodies through diagnostic features from the torso with arms. We then conducted a follow-up functional magnetic resonance imaging (fMRI) experiment on body part images to examine whether diagnostic parts modulated body-related brain activity and corresponding neural representations. We found greater activations of the extra-striate body area (EBA) in response to both anger and fear than neutral for the torso and arms. Representational similarity analysis showed that neural patterns of the EBA distinguished different bodily expressions. Furthermore, the torso with arms and whole body had higher similarities in EBA representations relative to the legs and whole body, and to the head and whole body. Taken together, these results indicate that diagnostic body parts (i.e., torso with arms) can communicate bodily expression in a detectable manner.

Sparse reconstruction of magnetic resonance image combined with two-step iteration and adaptive shrinkage factor.

As an advanced technique, compressed sensing has been used for rapid magnetic resonance imaging in recent years, Two-step Iterative Shrinkage Thresholding Algorithm (TwIST) is a popular algorithm based on Iterative Thresholding Shrinkage Algorithm (ISTA) for fast MR image reconstruction. However TwIST algorithms cannot dynamically adjust shrinkage factor according to the degree of convergence. So it is difficult to balance speed and efficiency. In this paper, we proposed an algorithm which can dynamically adjust the shrinkage factor to rebalance the fidelity item and regular item during TwIST iterative process. The shrinkage factor adjusting is judged by the previous reconstructed results throughout the iteration cycle. It can greatly accelerate the iterative convergence while ensuring convergence accuracy. We used MR images with 2 body parts and different sampling rates to simulate, the results proved that the proposed algorithm have a faster convergence rate and better reconstruction performance. We also used 60 MR images of different body parts for further simulation, and the results proved the universal superiority of the proposed algorithm.

Review: The Florentine Codex: An Encyclopedia of the Nahua World in Sixteenth-Century Mexico, edited by Jeanette Favrot Peterson and Kevin Terraciano

Review: <i>The Florentine Codex: An Encyclopedia of the Nahua World in Sixteenth-Century Mexico</i>, edited by Jeanette Favrot Peterson and Kevin Terraciano