A discrete Reeb graph approach for the segmentation of human body scans

Segmentation of 3D human body (HB) scan is a very challenging problem in applications exploiting human scan data. To tackle this problem, we propose a topological approach based on discrete Reeb graph (DRG) which is an extension of the classical Reeb graph to unorganized cloud of 3D points. The essence of the approach is detecting critical nodes in the DRG thus permitting the extraction of branches that represent the body parts. Because the human body shape representation is built upon global topological features that are preserved so long as the whole structure of the human body does not change, our approach is quite robust against noise, holes, irregular sampling, moderate reference change and posture variation. Experimental results performed on real scan data demonstrate the validity of our method

Semantic Segmentation of Human Model Using Heat Kernel and Geodesic Distance

A novel approach of 3D human model segmentation is proposed, which is based on heat kernel signature and geodesic distance. Through calculating the heat kernel signature of the point clouds of human body model, the local maxima of thermal energy distribution of the model is found, and the set of feature points of the model is obtained. Heat kernel signature has affine invariability which can be used to extract the correct feature points of the human model in different postures. We adopt the method of geodesic distance to realize the hierarchical segmentation of human model after obtaining the semantic feature points of human model. The experimental results show that the method can overcome the defect of geodesic distance feature extraction. The human body models with different postures can be obtained with the model segmentation results of human semantic characteristics

Development of Image Based Model for Basic Standing Yoga Poses that Control Type-2 Diabetes

Yoga is one of the ancient practices originated in India that helps in balancing mind and body of human. For the past few decades it has got wide spread throughout the world. Many are practicing it in the presence of yoga tutor or following some online modes. But improper practice may cause major harm to muscles and ligaments of the human body. There are different asanas proposed in the Patanjali Yoga Sutra that can cure different diseases. This paper, proposes a mathematical model for a set of yoga asanas that can help cure Type -2 Diabetes. A noninvasive analysis has been implemented using Kinect Sensor and LabVIEW software to analyze the performance of the practitioner. The joints are subjected to the flexibility of the practitioner without any overstress

Articulated Whole-Body Atlases for Small Animal Image Analysis: Construction and Applications

Bone and mineral researc

Sensor architectures and technologies for upper limb 3d surface reconstruction: A review

3D digital models of the upper limb anatomy represent the starting point for the design process of bespoke devices, such as orthoses and prostheses, which can be modeled on the actual patient’s anatomy by using CAD (Computer Aided Design) tools. The ongoing research on optical scanning methodologies has allowed the development of technologies that allow the surface reconstruction of the upper limb anatomy through procedures characterized by minimum discomfort for the patient. However, the 3D optical scanning of upper limbs is a complex task that requires solving problematic aspects, such as the difficulty of keeping the hand in a stable position and the presence of artefacts due to involuntary movements. Scientific literature, indeed, investigated different approaches in this regard by either integrating commercial devices, to create customized sensor architectures, or by developing innovative 3D acquisition techniques. The present work is aimed at presenting an overview of the state of the art of optical technologies and sensor architectures for the surface acquisition of upper limb anatomies. The review analyzes the working principles at the basis of existing devices and proposes a categorization of the approaches based on handling, pre/post-processing effort, and potentialities in real-time scanning. An in-depth analysis of strengths and weaknesses of the approaches proposed by the research community is also provided to give valuable support in selecting the most appropriate solution for the specific application to be addressed

3-D measurement of body tissues based on ultrasound images with 3-D spatial information

2005-2006 > Academic research: refereed > Publication in refereed journalAccepted ManuscriptPublishe

Numerical Study of Laryngeal Control of Phonation using Realistic Finite Element Models of a Canine Larynx

While many may take it for granted, the human voice is an incredible feat. An average person can produce a great variety of voices and change voice characteristics agilely even without formal training. Last several decades of research has established that the production of voice is largely a mechanical process: i.e., the sustained vibration of the vocal folds driven by the glottal air flow. Since one only has a single pair of vocal folds, the versatility comes with the ability to change the mechanical status of the vocal folds, including vocal fold length and thickness, tension, and level of adduction, through activation of the laryngeal muscles. However, the relationship between laryngeal muscle activity and the characteristics of voice is not well understood due to limitations in experimental observation and simplifications in modelling and simulations. The science is still far behind the art. The current research aims to investigate first the relationship between laryngeal muscle activation and the posture of the vocal folds and second the relationship between voice source characteristics and vocal fold mechanical status using more comprehensive numerical models and simulations, thus improving the understanding of the roles of each laryngeal muscle in voice control. To do so, (1) the mechanics involved in vocal fold posturing and vibration, especially muscle contraction; (2) the realistic anatomical structure of the larynx must be considered properly. To achieve this goal, a numerical model of the larynx as realistic as possible was built. The geometry of the laryngeal components was reconstructed from high resolution MRI (Magnetic Resonance Imaging) data of an excised canine larynx, which makes more accurate the representation of the muscles and their sub-compartments, cartilages, and other important anatomical features of the larynx. A previously proposed muscle activation model was implemented in a 3D finite element package and applied to the larynx model to simulate the action of laryngeal muscles. After validation of the numerical model against experimental data, extensive parametric studies involving different combination of muscle activations were conducted to investigate how the voice source is controlled with laryngeal muscles. In the course of this study, some work was done to couple the same finite element tool with a Genetic Algorithm program to inversely determine model parameters in biomechanical models. The method was applied in a collaborated study on shape changes of a fish fin during swimming. This study is presented as a separate chapter at the end of this thesis. The method has potential application in determining parameters in vocal fold models and optimizing clinical vocal fold procedures. This thesis is essentially an assembly of the papers published by the author during the doctoral study, with the addition of an introductory chapter. Chapter 1 reviews the overall principles of voice production, the biomechanical basis of voice control, and past studies on voice control with a focus on the fundamental frequency. Chapter 2 describes the major numerical methods employed in this research with an emphasis on the finite element method. The muscle activation model is also described in this chapter. Chapter 3 describes the building of the larynx model from MRI data and its partial validation. Chapter 4 presents the application of the larynx model to posturing studies, including parametric activation of muscle groups and specific topics related to vocal fold posturing. Chapter 5 describes the change of vocal fold vibration dynamics under the influence of the interaction of the cricothyroid muscle and the thyroarytenoid muscle. The Flow-structure interaction simulations was realized by coupling the larynx model to a simple Bernoulli flow model and a two-stage simulation technique. Chapter 6 concludes the current thesis study. Suggestions for future studies are proposed. Chapter 7 is an independent study that is not related to voice control. It describes a numerical framework that inversely determines and validates model parameters of biomechanical models. The application of the proposed framework to a finite element model of a fish fin is presented

Estimating Anthropometric Marker Locations from 3-D LADAR Point Clouds

An area of interest for improving the identification portion of the system is in extracting anthropometric markers from a Laser Detection and Ranging (LADAR) point cloud. Analyzing anthropometrics markers is a common means of studying how a human moves and has been shown to provide good results in determining certain demographic information about the subject. This research examines a marker extraction method utilizing principal component analysis (PCA), self-organizing maps (SOM), alpha hulls, and basic anthropometric knowledge. The performance of the extraction algorithm is tested by performing gender classification with the calculated markers

Amygdala subnuclei response and connectivity during emotional processing

The involvement of the human amygdala in emotion-related processing has been studied using functional magnetic resonance imaging (fMRI) for many years. However, despite the amygdala being comprised of several subnuclei, most studies investigated the role of the entire amygdala in processing of emotions. Here we combined a novel anatomical tracing protocol with event-related high-resolution fMRI acquisition to study the responsiveness of the amygdala subnuclei to negative emotional stimuli and to examine intra-amygdala functional connectivity. The greatest sensitivity to the negative emotional stimuli was observed in the centromedial amygdala, where the hemodynamic response amplitude elicited by the negative emotional stimuli was greater and peaked later than for neutral stimuli. Connectivity patterns converge with extant findings in animals, such that the centromedial amygdala was more connected with the nuclei of the basal amygdala than with the lateral amygdala. Current findings provide evidence of functional specialization within the human amygdala