Three-dimensional Head Research Articles

Dynamic modulation of social gaze by sex and familiarity in marmoset dyads.

Social communication relies on the ability to perceive and interpret the direction of others' attention, and is commonly conveyed through head orientation and gaze direction in humans and nonhuman primates. However, traditional social gaze experiments in nonhuman primates require restraining head movements, significantly limiting their natural behavioral repertoire. Here, we developed a novel framework for accurately tracking facial features and three-dimensional head gaze orientations of multiple freely moving common marmosets ( Callithrix jacchus ). By combining deep learning-based computer vision tools with triangulation algorithms, we were able to track the facial features of marmoset dyads within an arena. This method effectively generates dynamic 3D geometrical facial frames while overcoming common challenges like occlusion. To detect the head gaze direction, we constructed a virtual cone, oriented perpendicular to the facial frame. Using this pipeline, we quantified different types of interactive social gaze events, including partner-directed gaze and joint gaze to a shared spatial location. We observed clear effects of sex and familiarity on both interpersonal distance and gaze dynamics in marmoset dyads. Unfamiliar pairs exhibited more stereotyped patterns of arena occupancy, more sustained levels of social gaze across social distance, and increased social gaze monitoring. On the other hand, familiar pairs exhibited higher levels of joint gazes. Moreover, males displayed significantly elevated levels of gazes toward females' faces and the surrounding regions, irrespective of familiarity. Our study reveals the importance of two key social factors in driving the gaze behaviors of a prosocial primate species and lays the groundwork for a rigorous quantification of primate behaviors in naturalistic settings.

A pyritized Ordovician leanchoiliid arthropod.

The "short-great-appendage" arthropods (Megacheira), such as Leanchoilia, have featured heavily in discussions of arthropod evolution, particularly related to the head and its appendages.1,2,3,4 Megacheirans are subject to competing interpretations, either as a clade4 or a grade,5 in the stem group of Euarthropoda6 or, alternatively, Chelicerata.4 They are most diverse in Cambrian Burgess-Shale-type deposits, where the family Leanchoiliidae is represented by six genera,7,8,9,10,11,12 characterized by the presence of three distal flagella on the great appendage with a presumed sensory function. We describe the first post-Cambrian member of this family, Lomankus edgecombei gen. et sp. nov, from the Upper Ordovician (Katian) Beecher's Trilobite Bed site of New York State-the first post-Cambrian megacheiran with the exception of the Silurian and Devonian Enaliktidae. Micro-computed tomography (micro-CT) scanning reveals the morphology of the short great appendage with elongate flagella, four biramous cephalic limbs, 11 trunk segments with biramous limbs and dorsal tergites, and an elongate telson unique within Leanchoiliidae. The great appendage is also unique: the long endites that bear the flagella in other leanchoiliids are absent (or at least greatly reduced) and each flagellum appears to attach directly to an individual podomere, suggesting a sensory rather than a raptorial function. The remarkable preservation of a well-developed ventral plate (epistome-labrum complex) anterior of the mouth reinforces a deutocerebral origin2,13 of the short great appendages. Lomankus edgecombei unveils the three-dimensional (3D) head morphology of leanchoiliids in unparalleled detail and demonstrates that these iconic fossil arthropods ranged into dysaerobic environments in the Ordovician, where Lomankus occupied a deposit-feeding niche.

Creating anatomically-derived, standardized, customizable, and three-dimensional printable head caps for functional neuroimaging.

Consistent and accurate probe placement is a crucial step towards enhancing the reproducibility of longitudinal and group-based functional neuroimaging studies. While the selection of headgear is central to these efforts, there does not currently exist a standardized design that can accommodate diverse probe configurations and experimental procedures. We aim to provide the community with an open-source software pipeline for conveniently creating low-cost, 3-D printable neuroimaging head caps with anatomically significant landmarks integrated into the structure of the cap. We utilize our advanced 3-D head mesh generation toolbox and 10-20 head landmark calculations to quickly convert a subject's anatomical scan or an atlas into a 3-D printable head cap model. The 3-D modeling environment of the open-source Blender platform permits advanced mesh processing features to customize the cap. The design process is streamlined into a Blender add-on named "NeuroCaptain". Using the intuitive user interface, we create various head cap models using brain atlases, and share those with the community. The resulting mesh-based head cap designs are readily 3-D printable using off-the-shelf printers and filaments while accurately preserving the head topology and landmarks. The methods developed in this work result in a widely accessible tool for community members to design, customize and fabricate caps that incorporate anatomically derived landmarks. This not only permits personalized head cap designs to achieve improved accuracy, but also offers an open platform for the community to propose standardizable head caps to facilitate multi-centered data collection and sharing.

Alternate conformational trajectories in ribosome translocation.

Translocation in protein synthesis entails the efficient and accurate movement of the mRNA-[tRNA]2 substrate through the ribosome after peptide bond formation. An essential conformational change during this process is the swiveling of the small subunit head domain about two rRNA 'hinge' elements. Using iterative selection and molecular dynamics simulations, we derive alternate hinge elements capable of translocation in vitro and in vivo and describe their effects on the conformational trajectory of the EF-G-bound, translocating ribosome. In these alternate conformational pathways, we observe a diversity of swivel kinetics, hinge motions, three-dimensional head domain trajectories and tRNA dynamics. By finding alternate conformational pathways of translocation, we identify motions and intermediates that are essential or malleable in this process. These findings highlight the plasticity of protein synthesis and provide a more thorough understanding of the available sequence and conformational landscape of a central biological process.

Research on Intelligent Wheelchair Multimode Human–Computer Interaction and Assisted Driving Technology

The traditional wheelchair focuses on the “human-chair” motor function interaction to ensure the elderly and people with disabilities’ basic travel. For people with visual, hearing, physical disabilities, etc., the current wheelchairs show shortcomings in terms of accessibility and independent travel for this group. Therefore, this paper develops an intelligent wheelchair with multimodal human–computer interaction and autonomous navigation technology. Firstly, it researches the multimodal human–computer interaction technology of occupant gesture recognition, speech recognition, and head posture recognition and proposes a wheelchair control method of three-dimensional head posture mapping the two-dimensional plane. After testing, the average accuracy of the gesture, head posture and voice control modes of the motorized wheelchair proposed in this study reaches more than 95 percent. Secondly, the LiDAR-based smart wheelchair indoor autonomous navigation technology is investigated to realize the autonomous navigation of the wheelchair by constructing an environment map, using A* and DWA algorithms for global and local path planning, and adaptive Monte Carlo simulation algorithms for real-time localization. Experiments show that the position error of the wheelchair is within 10 cm, and the heading angle error is less than 5° during the autonomous navigation. The multimode human–computer interaction and assisted driving technology proposed in this study can partially compensate and replace the functional deficiencies of the disabled population and improve the quality of life of the elderly and disabled population.

Using a three-dimensional natural head position precise recording and transferring device to translate the natural head position into a 3-dimensional virtual patient: A dental technique

As computer-assisted surgical design becomes increasingly popular in maxillofacial surgery, the integration of the natural head position (NHP) of a 3-dimensional virtual patient has become a primary problem that orthognathic surgeons have to solve during virtual surgical planning. The present technique describes a way of transferring the horizon orientation of the NHP into a computer-aided design software program with a recently developed NHP recording and transferring device (Patent No. ZL202110992198.6 China). The device can record NHP using 5 marked points which can be visualized radiographically.

An Antenna Array Based on Radar Operation With High Detection Capability and Implementability for Three-Dimensional Head Imaging

An Antenna Array Based on Radar Operation With High Detection Capability and Implementability for Three-Dimensional Head Imaging

Learning capabilities to resolve tilt-translation ambiguity in goldfish.

Spatial orientation refers to the perception of relative location and self-motion in space. The accurate formation of spatial orientation is essential for animals to survive and interact safely with their environment. The formation of spatial orientation involves the integration of sensory inputs from the vestibular, visual, and proprioceptive systems. Vestibular organs function as specialized head motion sensors, providing information regarding angular velocity and linear acceleration via the semicircular canals and otoliths, respectively. However, because forces arising from the linear acceleration (translation) and inclination relative to the gravitational axis (tilt) are equivalent, they are indistinguishable by accelerometers, including otoliths. This is commonly referred to as the tilt - translation ambiguity, which can occasionally lead to the misinterpretation of translation as a tilt. The major theoretical frameworks addressing this issue have proposed that the interpretation of tilt versus translation may be contingent on an animal's previous experiences of motion. However, empirical confirmation of this hypothesis is lacking. In this study, we conducted a behavioral experiment using goldfish to investigate how an animal's motion experience influences its interpretation of tilt vs. translation. We examined a reflexive eye movement called the vestibulo-ocular reflex (VOR), which compensatory-rotates the eyes in response to head motion and is known to reflect an animal's three-dimensional head motion estimate. We demonstrated that the VORs of naïve goldfish do not differentiate between translation and tilt at 0.5 Hz. However, following prolonged visual-translation training, which provided appropriate visual stimulation in conjunction with translational head motion, the VORs were capable of distinguishing between the two types of head motion within 3 h. These results were replicated using the Kalman filter model of spatial orientation, which incorporated the variable variance of process noise corresponding to the accumulated motion experience. Based on these experimental and computational findings, we discuss the neural mechanism underlying the resolution of tilt-translation ambiguity within a context analogous to, yet distinct from, previous cross-axis VOR adaptations.

Parasite escape mechanisms drive morphological diversification in avian lice.

Organisms that have repeatedly evolved similar morphologies owing to the same selective pressures provide excellent cases in which to examine specific morphological changes and their relevance to the ecology and evolution of taxa. Hosts of permanent parasites act as an independent evolutionary experiment, as parasites on these hosts are thought to be undergoing similar selective pressures. Parasitic feather lice have repeatedly diversified into convergent ecomorphs in different microhabitats on their avian hosts. We quantified specific morphological characters to determine (i) which traits are associated with each ecomorph, (ii) the quantitative differences between these ecomorphs, and (iii) if there is evidence of displacement among co-occurring lice as might be expected under louse-louse competition on the host. We used nano-computed tomography scan data of 89 specimens, belonging to four repeatedly evolved ecomorphs, to examine their mandibular muscle volume, limb length and three-dimensional head shape data. Here, we find evidence that lice repeatedly evolve similar morphologies as a mechanism to escape host defences, but also diverge into different ecomorphs related to the way they escape these defences. Lice that co-occur with other genera on a host exhibit greater morphological divergence, indicating a potential role of competition in evolutionary divergence.

Matrix stiffness-induced piezo1 activation promotes metastatic potential in three-dimensional head and neck cancer spheroids

Matrix stiffness-induced piezo1 activation promotes metastatic potential in three-dimensional head and neck cancer spheroids

Deep Learning Detection of Aneurysm Clips for Magnetic Resonance Imaging Safety.

Flagging the presence of metal devices before a head MRI scan is essential to allow appropriate safety checks. There is an unmet need for an automated system which can flag aneurysm clips prior to MRI appointments. We assess the accuracy with which a machine learning model can classify the presence or absence of an aneurysm clip on CT images. A total of 280 CT head scans were collected, 140 with aneurysm clips visible and 140 without. The data were used to retrain a pre-trained image classification neural network to classify CT localizer images. Models were developed using fivefold cross-validation and then tested on a holdout test set. A mean sensitivity of 100% and a mean accuracy of 82% were achieved. Predictions were explained using SHapley Additive exPlanations (SHAP), which highlighted that appropriate regions of interest were informing the models. Models were also trained from scratch to classify three-dimensional CT head scans. These did not exceed the sensitivity of the localizer models. This work illustrates an application of computer vision image classification to enhance current processes and improve patient safety.

Clinical validity and precision of deep learning-based cone-beam computed tomography automatic landmarking algorithm.

This study was performed to assess the clinical validity and accuracy of a deep learning-based automatic landmarking algorithm for cone-beam computed tomography (CBCT). Three-dimensional (3D) CBCT head measurements obtained through manual and automatic landmarking were compared. A total of 80 CBCT scans were divided into 3 groups: non-surgical (39 cases); surgical without hardware, namely surgical plates and mini-screws (9 cases); and surgical with hardware (32 cases). Each CBCT scan was analyzed to obtain 53 measurements, comprising 27 lengths, 21 angles, and 5 ratios, which were determined based on 65 landmarks identified using either a manual or a 3D automatic landmark detection method. In comparing measurement values derived from manual and artificial intelligence landmarking, 6 items displayed significant differences: R U6CP-L U6CP, R L3CP-L L3CP, S-N, Or_R-R U3CP, L1L to Me-GoL, and GoR-Gn/S-N (P<0.05). Of the 3 groups, the surgical scans without hardware exhibited the lowest error, reflecting the smallest difference in measurements between human- and artificial intelligence-based landmarking. The time required to identify 65 landmarks was approximately 40-60 minutes per CBCT volume when done manually, compared to 10.9 seconds for the artificial intelligence method (PC specifications: GeForce 2080Ti, 64GB RAM, and an Intel i7 CPU at 3.6 GHz). Measurements obtained with a deep learning-based CBCT automatic landmarking algorithm were similar in accuracy to values derived from manually determined points. By decreasing the time required to calculate these measurements, the efficiency of diagnosis and treatment may be improved.

Magnetic Resonance Electrical Properties Tomography Based on Modified Physics-Informed Neural Network and Multiconstraints.

This paper presents a novel method based on leveraging physics-informed neural networks for magnetic resonance electrical property tomography (MREPT). MREPT is a noninvasive technique that can retrieve the spatial distribution of electrical properties (EPs) of scanned tissues from measured transmit radiofrequency (RF) in magnetic resonance imaging (MRI) systems. The reconstruction of EP values in MREPT is achieved by solving a partial differential equation derived from Maxwell's equations that lacks a direct solution. Most conventional MREPT methods suffer from artifacts caused by the invalidation of the assumption applied for simplification of the problem and numerical errors caused by numerical differentiation. Existing deep learning-based (DL-based) MREPT methods comprise data-driven methods that need to collect massive datasets for training or model-driven methods that are only validated in trivial cases. Hence we proposed a model-driven method that learns mapping from a measured RF, its spatial gradient and Laplacian to EPs using fully connected networks (FCNNs). The spatial gradient of EP can be computed through the automatic differentiation of FCNNs and the chain rule. FCNNs are optimized using the residual of the central physical equation of convection-reaction MREPT as the loss function (L). To alleviate the ill condition of the problem, we added multiconstraints, including the similarity constraint between permittivity and conductivity and the ℓ1 norm of spatial gradients of permittivity and conductivity, to the L. We demonstrate the proposed method with a three-dimensional realistic head model, a digital phantom simulation, and a practical phantom experiment at a 9.4T animal MRI system.

Self-Isolated Dual-Mode High-Pass Birdcage RF Coil for Proton and Sodium MR Imaging at 7 T MRI

This study presents the feasibility of a dual-mode high-pass birdcage RF coil to acquire MR images at both 1H and 23Na frequencies at ultra-high-field MR scanner, 7 T. A dual-mode circuit (DMC) in the dual-mode birdcage (DMBC) RF coil operates at two frequencies, addressing the limitations of sensitivity reduction and isolation between two frequencies as in traditional dual-tuned RF coil. Finite-difference time-domain (FDTD) based electromagnetic (EM) simulations were performed to verify the RF coil at each frequency on the three-dimensional human head model. The DMBC RF coil resonated at proton (1H) and sodium (23Na) frequencies, and also single-tuned high-pass birdcage RF coils were constructed for both 1H and 23Na frequencies. The bench test performance of the RF coils was evaluated using network analysis parameters, including the measurement of scattering parameters (S-parameters) and quality factors (Q-factors). Q-factor of the DMBC coil at 1H port was 10.2% lower than that of 1H single-tuned birdcage (STBC) coil, with a modest SNR reduction of 6.5%. Similarly, the Q-factor for the DMBC coil at 23Na port was 12.3% less than that of 23Na STBC coil, and the SNR showed a minimal reduction of 5.4%. Utilizing the DMBC coil, promising 1H and 23Na MR images were acquired compared to those by using STBC coils. In conclusion, deploying a DMBC 1H/23Na coil has been demonstrated to overcome traditional constraints associated with dual-tuned RF coils, achieving this with only nominal signal attenuation across both nuclei operational frequencies.

Object Detection for Aircraft Turnover Milestone based on Modified

In the target detection task of aircraft turnaround milestone in foggy scenario, there are some problems such as unstable location of prediction frame boundary, high error detection rate and poor detection effect of small target. A new target detection method BTM-YOLO (Broad-sighted upsample and three-dimensional attention multiple detection head YOLO) is proposed, which is based on YOLOv7 network. Add a small target detection head to improve the ability of small target detection; The up-sampling module OVRAFE is introduced to reduce the information loss in the up-sampling process. Replace CIoU with Median Wise IoU (MWIoU) to suppress the problem of poor sample swelling in data sets. The improved model makes up for the performance shortcomings of small target detection in foggy days, and the average detection accuracy on the real foggy day test set is 76.2%, which is 3.32% higher than that of the original model, basically meeting the task requirements.

VALIDATION OF A THREE-DIMENSIONAL HEAD PHANTOM FOR IMAGING DATA

This paper presents the research results on the design of a three-dimensional head phantom for cone beam projection. The head model is based on a Shepp-Logan mathematical head model, which is used to simulate the operation of the CT scanner. The model is then compared with the reference data for structural similarity, reasoning, and shape. The geometric parameters of the obtained images are investigated. The reconstructed image is analyzed using the FDK method. The results show that the geometric parameters directly correlate with the number of projections. A mathematical framework of cone beam 3d reconstruction via the first derivative of the radon transform is presented.

Fast simulation of 3D elastic response for wheel–rail contact loading using Proper Generalized Decomposition

To increase computational efficiency, we adopt Proper Generalized Decomposition (PGD) to solve a reduced-order problem of the displacement field for a three-dimensional rail head exposed to different contact scenarios. The three-dimensional solid rail head is modeled as a two-dimensional cross-section, with the coordinate along the rail being treated as a parameter in the PGD approximation. A novel feature is that this allows us to solve the full three-dimensional model with a nearly two-dimensional computational effort. Additionally, we incorporate the distributed contact load predicted from dynamic vehicle–track simulations as extra coordinates in the PGD formulation, using a semi-Hertzian contact model. The problem is formulated in two ways; one general ansatz which considers the treatment of numerous parameters, some of which exhibit a linear influence, and a linear ansatz where multiple PGD solutions are solved for. In particular, situations where certain parameters become invariant are handled. We assess the accuracy and efficiency of the proposed strategy through a series of verification examples. It is shown that the PGD solution converges toward the FE solution with reduced computational cost. Furthermore, solving for the PGD approximation based on load parameterization in an offline stage allows expedient handling of the wheel–rail contact problem online.

Revisiting the Cephalic Index: The Origin, Purpose, and Current Applicability—A Narrative Review

ABSTRACT Introduction Cephalometry is the measurement and study of the proportions of the head and face, and infant skull deformities have been the subject of many clinical studies over the last 30 years. Clinical protocols to document change are especially critical during periods of growth and development, but reference values and norms are lacking for infants, especially in the first year after birth. Discussion Key publications were reviewed by the authors to provide a narrative review of the 1) origin of the cephalic index (CI), 2) adaptations of the measure over time, 3) anatomical landmarks and alignments used, 4) clinical tools, 5) necessary considerations for different ethnic, sex, and cultural influences, 6) value and limitations of CI measurements, and 7) appropriate use of the CI in the documentation of infant skull deformities. The CI calculation has remained constant since the 1840s, although the cranial shape classifications have changed many times over the years. Conclusions Used in isolation, the two-dimensional (2D) and linear nature of the CI fails to describe the magnitude of the three-dimensional (3D) head deformity. However, the CI can and should be used in conjunction with other 2D and 3D measurements to provide a more detailed description and understanding of the entire cranial deformity. For today's cranial clinicians and allied health care professionals, the commonly referenced CI chart fails to reflect 1) the natural skull changes noted with supine sleeping infants, and 2) the cultural diversity of the infant population currently treated. Although the CI provides information about one of the most obvious features of the dysmorphology, clinicians must also document and report other distinct features such as frontal flattening or bossing, parietal shape or involvement, sloping, displacement, and/or posterior asymmetry. Clinical Relevance The CI should be used in conjunction with other 2D and 3D anthropometric measurements to provide a more detailed assessment of the entire cranial deformity. The CI results should be discussed with the medical team along with a complete review of other 2D and 3D measurements to determine the best course of action for orthotic treatment or nontreatment of the head shape.

Trigone point as an alternative location for ventricular shunt insertion

Link of Video Abstract: https://youtu.be/BtHvICeUONYBackground: Hydrocephalus is a condition in which cerebrospinal fluid (CSS) buildup in the ventricles is caused by excessive CSS production or disturbance of CSS circulation or absorption. Insertion of a shunt catheter into the lateral ventricle can be performed at the Kocher, Keen, Dandy, Frazier, Kaufmann, or Tubbs points. This study aims to evaluate the trigone point as an alternative location for ventricular shunt insertion Methods: This is a retrospective study. We performed a three-dimensional head CT scan reconstruction of hydrocephalus patients; then, we calculated the vertical and horizontal distances perpendicular to each other from the upper edge of the auricle that intersects the trigone point on the right and left sides of the patient. Data were analyzed using SPSS version 26.0 for Windows. Results: A total of 30 hydrocephalus patients at Kariadi Hospital Semarang from 2021 – 2022 were enrolled in this study. We got the averages of the vertical line is 25.05 mm and the horizontal is 33.00 mm for the right trigone point. In addition, the average vertical line is 25.78 mm and the horizontal line is 34.72 mm for the left trigone point. There was no significant difference between the vertical distance of the right and left trigone points (p=0.578) and the horizontal distance of the right and left trigone points (p=0.185). We found no significant difference between the location of the right and left trigone points. Conclusion: Trigone point can be an alternative location for ventricular shunt installation.

Molding Helmet Therapy for Severe Deformational Brachycephaly: Position of Eurion and Therapeutic Effect.

Molding helmet therapy is used routinely for moderate to severe deformational plagiocephaly. However, there have been few reports of its use for deformational brachycephaly (DB). The incidence and severity of DB are high in the Asian population, including Japanese people, but there are no reports of treatment for severe cases. The current study showed significant improvement even in severe DB with various deformities. The difference in improvement according to the morphologic classification was investigated. The study included 47 patients treated with helmet therapy for DB with a cephalic index of greater than 100%. Three-dimensional head scans were used for classification and measurement. DB was classified into four types according to the position of the eurion and the presence of deformational plagiocephaly. The therapeutic effect was determined by changes in cephalic index and cranial asymmetry. Patients exhibited a mean change of 8.0% in cephalic index and 6.4 mm in cranial asymmetry. An older age at initiation was associated with less change in both cephalic index and cranial asymmetry. A significant difference in the amount of cephalic index change was observed depending on the position of the eurion when the starting age was 6 months or older ( P < 0.05). Molding helmet therapy for severe DB results in significant morphological improvement. However, depending on the position of the eurion, the effect of treatment may be decreased if it is started too late. It is necessary to understand the difference in improvement depending on the morphology and to ensure early intervention. Risk, II.