Landmark Positions Research Articles

The Pillars of the Nose-Crura Shortening for Over Projected Nose.

BACKGROUND:The over projected nose, commonly referred to as the “Pinocchio” nose is a significant challenge to the rhinoplasty surgeon. Firstly, we speak about a very large nose, and secondly, we speak about the correction of nasal cartilages (alar and triangular). Surgical correction of the over projected nose is the most difficult and least predictable component of rhinoplasty surgery.AIM:By performing rhinoseptoplasty we aimed to achieve an ideal landmarks position according to concepts of nasal projection as well as by making preoperative analyses to determine the ideal position for the nasal tip after having understood and defined the ideal position for the nasion.METHODS:We performed a retrospective study of patients who were admitted to ENT University Clinic, University Campus “St. Mother Theresa” Skopje, the Republic of Macedonia in the period 2011-2019. A total of 70 patients were enrolled in the study; 46 women (33%) and 24 men (33%). Operative technique rhinoseptoplasty was realised in 70 patients. All of the 70 (100%) patients underwent preoperative and postoperative evaluation during this period regularly to record the effects of various approaches on nasal projection, rotation, need for revision, and patient satisfaction.RESULTS:All patients used one or more of the preferred methods to treat over projection. Patients who had undergone 2 previous rhino/septoplasty procedures were excluded from the study, and hence, a total of 70 patients were evaluated. Full-transfixion incisions were made in all patients. From 2011 to 2019, in 72 cases, 1 or more of the preferred methods were used to treat over projection.CONCLUSION:The crural anatomy of the nasal tip relates to the size and shape of the lower lateral cartilages (LLC) and their relationship with the caudal septum and upper lateral cartilages (ULC). Modification of nasal tip rotation and projection should attempt to preserve or reconstruct major tip mechanisms.

Angle of approach to the superior rotator cuff of arthroscopic instruments depends on the acromial morphology: an experimental study in 3D printed human shoulders

BackgroundPortal placement is a key factor for the success of arthroscopic procedures, particularly in rotator cuff repair. We hypothesize that the acromial anatomy may strongly determine the position of the shoulder bony landmarks and limit the surgeon’s freedom to position the arthroscopic approaches in direction towards the acromion. The purpose of this study was to analyze the relation between different acromial shapes and the freedom of movement of arthroscopic instruments relative to the rotator cuff from standardized arthroscopic portals in a laboratory study on 3D shoulder models.Methods3D models of shoulders with a broad range of different acromial shapes were printed using CT and MRI scans. Angles from the portals to defined points on the rotator cuff and the supraglenoid tubercle were measured. In conventional radiographs, the critical shoulder angle, the scapular body acromial angle, and the glenoid acromial angle were measured and compared with the measured angles to the rotator cuff.ResultsThere was a large variation of angles of approach of instruments to the rotator cuff between the seven shoulders for each portal. From the joint line portal and the posterior edge portal, the biggest angles were measured to the posterior cuff. From the intermediate portal, the angles were largest to the intermediate rotator cuff and from the anterior portals to the anterior cuff. To the supraglenoid tubercle, best access was from anterior. For all portals, there was a big correlation between the glenoid acromial angle and the scapular body acromial angle with the angles of approach to the tendon and especially to the supraglenoid tubercle.ConclusionThe access to the rotator cuff from almost every portal is influenced by the acromial shape. As hypothesized, a small (small GAA) and flat (big SBAA) acromion provide an easier approach to the rotator cuff from almost every portal. Therefore, it may severely influence the instruments maneuverability.

Technique of Choice to Anesthetize Mandibular Nerve in Case of Maxillofacial Fractures

Achieving optimum pain control and anesthesia in maxillofacial fracture trauma individuals will be difficult in some scenarios because of change in position of landmarks due to fracture, trismus, and noncompliant nature of patient due to pain. We did a comparative evaluation of efficiency of inferior alveolar nerve block (IANB) and Vazirani-Akinosi closed mouth nerve block technique to anesthetize the inferior alveolar nerve in trauma patients with trismus and concluded that IANB is superior to Vazirani-Akinosi in terms of onset and efficacy but its application in trauma patients with reduced mouth opening is limited and Vazirani-Akinosi will be the technique of choice in case of such scenarios.

Automatic landmarking as a convenient prerequisite for geometric morphometrics. Validation on cone beam computed tomography (CBCT)- based shape analysis of the nasal complex

Manual landmarking is used in several manual and semi-automated prediction guidelines for approximation of the nose. The manual placement of landmarks may, however, render the analysis less repeatable due to observer subjectivity and, consequently, have an impact on the accuracy of the human facial approximation. In order to address this subjectivity and thereby improve facial approximations, we are developing an automated three-dimensional (3D) method based on an automatic dense landmarking procedure using non-rigid surface registration. The aim of this study was to validate the automatic landmarking method by comparing the intra-observer errors (INTRA-OE) and inter-observer errors (INTER-OE) between automatic and manual landmarking.Cone beam computed tomography (CBCT) scans of adult South Africans were selected from the Oral and Dental Hospital, University of Pretoria, South Africa. In this study, the validation of the automatic landmarking was performed on 20 3D surfaces. INTRA-OE and INTER-OE were analyzed by registering 41 craniometric landmarks from 10 hard-tissue surfaces and 21 capulometric landmarks from 10 soft-tissue surfaces of the same individuals. Absolute precision of the landmark positioning (both on the samples as well as the template) was assessed by calculating the measurement error (ME) for each landmark over different observers. Systematic error (bias) and relative random error (precision) was further quantified through repeated measures ANOVA (ANOVA-RM).The analysis showed that the random component of the ME in landmark positioning between the automatic observations were on average on par with the manual observations, except for the soft-tissue landmarks where automatic landmarking showed lower ME compared to manual landmarking. No bias was observed within the craniometric landmarking methods, but some bias was observed for capulometric landmarking.In conclusion, this research provides a first validation of the precision and accuracy of the automatic placement of landmarks on 3D hard- and soft-tissue surfaces and demonstrates its utilization as a convenient prerequisite for geometric morphometrics based shape analysis of the nasal complex.

A Hierarchical Curve-Based Approach to the Analysis of Manifold Data.

One of the data structures generated by medical imaging technology is high resolution point clouds representing anatomical surfaces. Stereophotogrammetry and laser scanning are two widely available sources of this kind of data. A standardised surface representation is required to provide a meaningful correspondence across different images as a basis for statistical analysis. Point locations with anatomical definitions, referred to as landmarks, have been the traditional approach. Landmarks can also be taken as the starting point for more general surface representations, often using templates which are warped on to an observed surface by matching landmark positions and subsequent local adjustment of the surface. The aim of the present paper is to provide a new approach which places anatomical curves at the heart of the surface representation and its analysis. Curves provide intermediate structures which capture the principal features of the manifold (surface) of interest through its ridges and valleys. As landmarks are often available these are used as anchoring points, but surface curvature information is the principal guide in estimating the curve locations. The surface patches between these curves are relatively flat and can be represented in a standardised manner by appropriate surface transects to give a complete surface model. This new approach does not require the use of a template, reference sample or any external information to guide the method and, when compared with a surface based approach, the estimation of curves is shown to have improved performance. In addition, examples involving applications to mussel shells and human faces show that the analysis of curve information can deliver more targeted and effective insight than the use of full surface information.

Exploring the midline soft tissue surface changes from 12 to 15 years of age in three distinct country population cohorts.

Several studies have highlighted differences in the facial features in a White European population. Genetics appear to have a major influence on normal facial variation, and environmental factors are likely to have minor influences on face shape directly or through epigenetic mechanisms. The aim of this longitudinal cohort study is to determine the rate of change in midline facial landmarks in three distinct homogenous population groups (Finnish, Latvian, and Welsh) from 12.8 to 15.3 years of age. This age range covers the pubertal growth period for the majority of boys and girls. A cohort of children aged 12 were monitored for facial growth in three countries [Finland (n = 60), Latvia (n = 107), and Wales (n = 96)]. Three-dimensional facial surface images were acquired (using either laser or photogrammetric methods) at regular intervals (6-12 months) for 4 years. Ethical approval was granted in each country. Nine midline landmarks were identified and the relative spatial positions of these surface landmarks were measured relative to the mid-endocanthion (men) over a 4-year period. This study reports the children who attended 95 per cent of all scanning sessions (Finland 48 out of 60; Latvia 104 out of 107; Wales 50 out of 96). Considerable facial variation is seen for all countries and sexes. There are clear patterns of growth that show different magnitudes at different age groups for the different country groups, sexes, and facial parameters. The greatest single yearly growth rate (5.4 mm) was seen for Welsh males for men-pogonion distance at 13.6 years of age. Males exhibit greater rates of growth compared to females. These variations in magnitude and timings are likely to be influenced by genetic ancestry as a result of population migration. The midline points are a simple and valid method to assess the relative spatial positions of facial surface landmarks. This study confirms previous reports on the subtle differences in facial shapes and sizes of male and female children in different populations and also highlights the magnitudes and timings of growth for various midline landmark distances to the men point.

Abstract 392: Use of a Low Resource Model for Group Cardiopulmonary Resuscitation Training: Knowledge Gains and Attitude Changes

Introduction: CPR training and regular skills practice is often limited by the availability of a high resource device such as a manikin torso. We investigated the knowledge gains and attitude changes in student participants of group hands-only CPR training (20-50 participants) using a low resource device, a bed pillow, to practice skills. Methods: Hands-only CPR trainings, utilizing a bed pillow for skills practice, were conducted for groups of college students. Using a one-group pre-test post-test design, participants (n=360) completed a questionnaire which included demographic information, prior history of CPR training, and multiple-choice questions to evaluate knowledge. Five-point Likert scale questions were used to assess attitudes specific to willingness to perform CPR, confidence in ability to perform CPR and likeliness to practice skills in the next year. The survey was completed prior to training. The participants then watched a demonstration followed by interactive skills practice on a pillow. A specially designed printed pillow case was used to show hand position landmarks and review information. The post training survey was then completed and each participant was provided a printed pillow case for future skills practice and review. Results: 129 participants (36%) had no prior CPR training, there were more females 273 (76%) than males, and the average age of participants was 20 years old. Correct knowledge regarding depth of compressions increased by 47% (47 to 94) while speed of compression knowledge increased by 52% (40 to 92). In a paired analysis, there were significant differences (p<.0001) in all attitude measures from pre-to-post training. Willingness to perform CPR increased 31% (gain=0.94, pre test=3.01), confidence to perform CPR, 45% (gain=1.18, pre test=2.64) and likeliness to practice skills in the next year, 20% (gain=0.59, pre test=2.97). Conclusions: Participation in group hands-only CPR training using a low resource device for skills practice resulted in significant knowledge gains and improved attitudes in the areas of willingness to perform CPR, confidence to perform CPR and skills practice likeliness. This training method can provide an accessible and cost-effective means for providing group CPR training.

Depth camera based statistical shape fitting approach for the creation of an individualized lower body biomechanical model: validity and reliability

Systems for instrumented motion analysis depend on an accurate biomechanical model. In this work an existing statistical shape fitting approach was adapted to register a parametrized human surface model with annotated anatomical landmarks to a point cloud obtained from one frontal depth camera view. Based on the obtained landmark positions joint centers, segment lengths and segment orientations of the lower body were calculated. The outcome was validated among two groups of healthy and impaired subjects, using a marker-based optical motion capture system. The results reveal a valid and reliable approach for obtaining an individualized lower body biomechanical model with minimum effort.

A Revisiting Method Using a Covariance Traveling Salesman Problem Algorithm for Landmark-Based Simultaneous Localization and Mapping.

This paper presents an efficient revisiting algorithm for landmark-based simultaneous localization and mapping (SLAM). To reduce SLAM uncertainty in terms of a robot’s pose and landmark positions, the method autonomously evaluates valuable landmarks for the data associations in the SLAM algorithm and selects positions to revisit by considering both landmark visibility and sensor measurement uncertainty. The optimal path among the selected positions is obtained by applying the traveling salesman problem (TSP) algorithm. To plan a path that reduces overall uncertainty, the cost matrix associated with the change in covariance between all selected positions of all pairs is applied for the TSP algorithm. From simulations, it is verified that the proposed method efficiently reduces and maintains SLAM uncertainty at the low level compared to the backtracking method.

Cranial growth in isolated sagittal craniosynostosis compared with normal growth in the first 6 months of age.

Sagittal craniosynostosis (SCS), the most common type of premature perinatal cranial suture fusion, results in abnormal head shape that requires extensive surgery to correct. It is important to find objective and repeatable measures of severity and surgical outcome to examine the effect of timing and technique on different SCS surgeries. The purpose of this study was to develop statistical models of infant (0-6months old) skull growth in both normative and SCS subjects (prior to surgery). Our goal was to apply these models to the assessment of differences between these two groups in overall post-natal growth patterns and sutural growth rates as a first step to develop methods for predictive models of surgical outcome. We identified 81 patients with isolated, non-syndromic SCS from Seattle Children's Craniofacial Center patient database who had a preoperative CT exam before the age of 6months. As a control group, we identified 117 CT exams without any craniofacial abnormalities or bone fractures in the same age group. We first created population-level templates from the CT images of the SCS and normal groups. All CT images from both groups, as well as the canonical templates of both cohorts, were annotated with anatomical landmarks, which were used in a growth model that predicted the locations of these landmarks at a given age based on each population. Using the template images and the landmark positions predicted by the growth models, we created 3D meshes for each week of age up to 6months for both populations. To analyze the growth patterns at the suture sites, we annotated both templates with additional semi-landmarks equally spaced along the metopic, coronal, sagittal and lambdoidal cranial sutures. By transferring these semi-landmarks to meshes produced from the growth model, we measured the displacement of the bone borders and suture closure rates. We found that the growth at the metopic and coronal sutures were more rapid in the SCS cohort than in the normal cohort. The antero-posterior displacement of the semi-landmarks also indicated a more rapid growth in the sagittal plane in the SCS model than in the normal model. Statistical templates and geometric morphometrics are promising tools for understanding the growth patterns in normal and synostotic populations and to produce objective and reproducible measurements of severity and outcome. Our study is the first of its kind to quantify the bone growth for the first 6months of life in both normal and sagittal synostosis patients.

Effective Landmark Placement for Robot Indoor Localization With Position Uncertainty Constraints

A well-known, crucial problem for indoor positioning of mobile agents (e.g., robots) equipped with exteroceptive sensors is related to the need to deploy reference landmarks in a given environment. Normally, anytime a landmark is detected, an agent estimates its own location and attitude with respect to landmark position and/or orientation in the chosen reference frame. When instead no landmark is recognized, other sensors (e.g., odometers in the case of wheeled robots) can be used to track the agent position and orientation from the last detected landmark. At the moment, landmark placement is usually based just on common-sense criteria, which are not formalized properly. As a result, positioning uncertainty tends to grow unpredictably. On the contrary, the purpose of this paper is to minimize the number of landmarks, while ensuring that localization uncertainty is kept within wanted boundaries. The developed approach relies on the following key features: a dynamic model describing agents’ motion, a model predicting the agents’ paths within a given environment and, finally, a conjunctive normal form formalization of the optimization problem, which can be efficiently (although approximately) solved by a greedy algorithm. The effectiveness of the proposed landmark placement technique is first demonstrated through simulations in a variety of conditions and then it is validated through experiments on the field, by using non-Bayesian and Bayesian position tracking algorithms.

Liveness Detection Based on Human eye Blinking for Photo Attacks

Auto face recognition mainly implemented to avoid the replication of identity to demonstrate through security check. This rage of face verification has brought intensive interest about facial biometric towards attacks of spoofing, in which a person’s mask or photo can be produced to be authorized. So, we propose a liveness detection based on eye blinking, where eyes are extracted from human face. The method of face recognition was applied by utilizing OpenCV classifier and dlib library, and a concept of edge detection and calculation of structure to extract the portion of the eye and to observe and make note of variation in the attributes of the eyes over a time period was employed. The landmarks are plotted accurately enough to derive the state of eye if it is closed or opened. A scalar quantity EAR (eye aspect ratio) is derived from landmark positions defined by the algorithm to identify a blink corresponding to every frame. The set of EAR values of successive frames are detected as a eye blink by a OpenCV classifier displayed on a small window when person is in front of camera. Finally, it gives the accuracy result whether it is human being or spoof attack.

Using three-dimensional craniofacial images to construct horizontal reference plane

To compare four different three-dimensional horizontal planes and detect anatomical landmarks so as to provide theoretical reference for horizontal reference plane constructed by three-dimensional cephalometry. The subjects of this study were 32 facial symmetry patients (menton from midsagittal plane ≤2 mm). Cone-beam computed tomography (CBCT) was obtained before orthodontic treatment, and the data were imported into Dolphin imaging soft in DICOM format. The sagittal plane was passing through the Nasion, Sella and Dent. Four horizontal reference planes were constructed by three points of bilateral porion and bilateral orbitale. Plane 1: horizontal reference plane constructed by right porion and bilateral orbitale. Plane 2: horizontal reference plane constructed by left porion and bilateral orbitale. Plane 3: horizontal reference plane constructed by bilateral porion and right orbitale. Plane 4: horizontal reference plane constructed by bilateral porion and left orbitale. Pitch, yaw, roll for four planes were measured three dimensionally. All the samples were measured two times by one judge at an interval of two weeks. The two times measuring results were evaluated with Intraclass correlation coefficient (ICC) for verifying reliability. The multiple sets of repeated measurement analysis were used to compare the four different planes. Based on ages, the samples were divided into two groups (group 1: ages 13 to 17, group 2: over 18 years), the mean and standard deviation of landmark coordinates measured with Dent as the origin point, the circumference formula was applied to calculate the change of landmark position generated by head rotation. No significant differences of pitch, yaw and roll among the four planes (P=0.196, 0.314, and 0.341). One degree of pitch rotation made changes of porion and orbitale approximate 0.5 mm, and 1.6 mm, respectively. One degree of yaw rotation made changes of porion and orbitale approximate 1.1 mm, and 1.5 mm, respectively. One degree of roll rotation made changes of porion and orbitale approximate 1.2 mm, and 0.7 mm, respectively. There was no significant difference among the four horizontal planes constructed by any three points of bilateral orbitales and bilateral porions. It has the highest concordance using bilateral orbitales and one porion to construct horizontal plane in this study, probably the best option in clinical practice. Different head rotation generated different distance changes of anatomical landmarks.

Quantification of Visual Fixation Behavior and Spatial Orientation Memory in Drosophila melanogaster.

Drosophila Melanogaster has been shown to exhibit short-term orientation memory by fixating on orientations toward previously displayed visual landmarks. However, the fixation behavior varies and is often mixed with other types of movement. Therefore, carefully designed statistical measures are required in order to properly describe the characteristics of the fixation behavior and to quantify the orientation memory exhibited by the fruit flies. To this end, we propose a set of analytical methods. First, we defined the deviation angle which is used to quantify the deviation of the fruit fly's heading from the landmark positions. The deviation angle is defined based on the fruit fly's perspective and is able to reveal more task-relevant movement patterns than the commonly used definition which is based on the “observer's perspective.” We further introduce a temporal deviation angle plot which visually presents the complex movement pattern as a function of time. Next, we define the fixation index which tolerates fluctuation in the movement and performs better in quantifying the level of fixation behavior, or the orientation memory, than the conventional method.

Accuracy of virtual surgical planning-assisted management for maxillary hypoplasia in adult patients with cleft lip and palate

Management of maxillary hypoplasia in patients with cleft lip and palate (CLP) remains a significant clinical challenge. The objective of this retrospective study is to evaluate the accuracy of virtual surgical planning (VSP) with different maxillary advancement techniques. Ninety adult patients with cleft-related maxillary hypoplasia between April 2010 and April 2016 were enrolled in our study. Various surgical techniques including conventional orthognathic surgery, total maxillary distraction osteogenesis, and anterior maxillary segmental distraction were used according to the characteristics of patients. All the cases were aided with VSP and three-dimensional (3D)-printed surgical splints. The virtual surgical plan was compared with the postoperative surgical results by analyzing the positions of several landmarks and planes relative to reference planes. Both the profile and occlusion were improved significantly in all the cases. VSP was successfully transferred to actual surgery with the help of 3D-printed surgical splints in different surgical techniques. Management of cleft-related maxillary hypoplasia requires both comprehensive surgical planning and accurate execution. VSP serves as a viable alternative to conventional model surgery with high accuracy in patients with adult CLP.

The face of art

Facial Landmark detection in natural images is a very active research domain. Impressive progress has been made in recent years, with the rise of neural-network based methods and large-scale datasets. However, it is still a challenging and largely unexplored problem in the artistic portraits domain. Compared to natural face images, artistic portraits are much more diverse. They contain a much wider style variation in both geometry and texture and are more complex to analyze. Moreover, datasets that are necessary to train neural networks are unavailable. We propose a method for artistic augmentation of natural face images that enables training deep neural networks for landmark detection in artistic portraits. We utilize conventional facial landmarks datasets, and transform their content from natural images into "artistic face" images. In addition, we use a feature-based landmark correction step, to reduce the dependency between the different facial features, which is necessary due to position and shape variations of facial landmarks in artworks. To evaluate our landmark detection framework, we created an "Artistic-Faces" dataset, containing 160 artworks of various art genres, artists and styles, with a large variation in both geometry and texture. Using our method, we can detect facial features in artistic portraits and analyze their geometric style. This allows the definition of signatures for artistic styles of artworks and artists, that encode both the geometry and the texture style. It also allows us to present a geometric-aware style transfer method for portraits.

Comparison of Unsupervised Learning Methods for Natural Image Processing

For computer vision based appraoches such as image classification (Krizhevsky et al. 2012), object detection (Ren et al. 2015) or pixel-wise weed classification (Milioto et al. 2017) machine learning is used for both feature extraction and processing (e.g. classification or regression). Historically, feature extraction (e.g. PCA; Ch. 12.1. in Bishop 2006) and processing were sequential and independent tasks (Wöber et al. 2013). Since the rise of convolutional neuronal networks (LeCun et al. 1989), a deep machine learning approach optimized for images, in 2012 (Krizhevsky et al. 2012), feature extraction for image analysis became an automated procedure. A convolutional neuronal net uses a deep architecture of artificial neurons (Goodfellow 2016) for both feature extraction and processing. Based on prior information such as image classes and supervised learning procedures, parameters of the neuronal nets are adjusted. This is known as the learning process. Simultaneously, geometric morphometrics (Tibihika et al. 2018, Cadrin and Friedland 1999) are used in biodiversity research for association analysis. Those approaches use deterministic two-dimensional locations on digital images (landmarks; Mitteroecker et al. 2013), where each position corresponds to biologically relevant regions of interest. Since this methodology is based on scientific results and compresses image content into deterministic landmarks, no uncertainty regarding those landmark positions is taken into account, which leads to information loss (Pearl 1988). Both, the reduction of this loss and novel knowledge detection, can be done using machine learning. Supervised learning methods (e.g., neuronal nets or support vector machines (Ch. 5 and 6. in Bishop 2006)) map data on prior information (e.g. labels). This increases the performance of classification or regression but affects the latent representation of the data itself. Unsupervised learning (e.g. latent variable models) uses assumptions concerning data structures to extract latent representations without prior information. Those representations does not have to be useful for data processing such as classification and due to that, the use of supervised and unsupervised machine learning and combinations of both, needs to be chosen carefully, according to the application and data. In this work, we discuss unsupervised learning algorithms in terms of explainability, performance and theoretical restrictions in context of known deep learning restrictions (Marcus 2018, Szegedy et al. 2014, Su et al. 2017). We analyse extracted features based on multiple image datasets and discuss shortcomings and performance for processing (e.g. reconstruction error or complexity measurement (Pincus 1997)) using the principal component analysis (Wöber et al. 2013), independent component analysis (Stone 2004), deep neuronal nets (auto encoders; Ch. 14 in Goodfellow 2016) and Gaussian process latent variable models (Titsias and Lawrence 2010, Lawrence 2005).

Examining Cranial Morphology of Asian and Hispanic Populations Using Geometric Morphometrics for Ancestry Estimation

Poor classification trends of Hispanic individuals have been shown when using the statistical software Fordisc 3.1 (FD3), which is commonly used by practitioners to estimate ancestry for unidentified skeletal cases (Jantz & Ousley 2005; Ousley & Jantz 2012). Similarities in craniometric dimensions were identified between Asian and Hispanic groups when performing discriminant function and canonical variate analysis using FD3 (Dudzik & Jantz 2016; Jantz & Ousley 2005). Hispanic cases were shown to often classify as Asian and showed a particularly close relationship with Japanese individuals, as illustrated by small Mahalanobis distances. This study further explores these misclassification trend findings by comparing craniometric analyses with geometric morphometric approaches to better identify morphological overlap between Asian and Hispanic populations. Geometric morphometric analyses have become increasingly useful for studies of cranial shape, and inter-landmark distances have been shown to more accurately estimate population affinity than standard cranial measurements (Spradley & Jantz 2016). Based on this evidence, a more detailed analysis of the morphological similarities between Asian and Hispanic craniometrics is warranted using geometric morphometric approaches. Data sets used include coordinate data of a subset of the Hispanic sample included in FD3 as well as individuals from Japan, Thailand, Korea, and China. Results show that variation among samples can be better identified to describe which dimensions of the cranium exhibit the most overlap across populations. Specifically, comparisons between the Asian and Hispanic data showed that the position of landmarks mainly representing dimensions of the neurocranium are useful for accurately predicting group membership.

SINS/Landmark Integrated Navigation Based on Landmark Attitude Determination.

Based on the situation that the traditional SINS (strapdown inertial navigation system)/CNS (celestial navigation system) integrated navigation system fails to realize all-day and all-weather navigation, this paper proposes a SINS/Landmark integrated navigation method based on landmark attitude determination to solve this problem. This integrated navigation system takes SINS as the basic scheme and uses landmark navigation to correct the error of SINS. The way of the attitude determination is to use the landmark information photographed by the landmark camera to complete feature matching. The principle of the landmark navigation and the process of attitude determination are discussed, and the feasibility of landmark attitude determination is analyzed, including the orthogonality of the attitude transform matrix, as well as the influences of the factors such as quantity and geometric position of landmarks. On this basis, the paper constructs the equations of the SINS/Landmark integrated navigation system, testifies the effectiveness of landmark attitude determination on the integrated navigation by Kalman filter, and improves the navigation precision of the system.

The Effect of Landmark Variability on Automated PAP Mask Sizing.

We present a study of the effect of variability in manual facial landmarking annotation on image based positive airway pressure mask sizing. Employing 12 expert annotators to identify specific facial landmarks on two images, ANOVA analysis was used to investigate landmark variability attributed to the annotator, types of landmarks and images. We found that while there was agreement between annotators, variance in individual landmark positions resulted in an error of up to 13.59% in measurements defining mask size. A number of different options are presented for reducing errors from manual facial landmarking.