Relevant bibliographies by topics / Skeleton segmentation

Contents

  1. Journal articles
  2. Dissertations / Theses
  3. Books
  4. Book chapters
  5. Conference papers

Academic literature on the topic 'Skeleton segmentation'

Author: Grafiati
Published: 25 June 2021
Last updated: 17 February 2022

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Journal articles on the topic "Skeleton segmentation"

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TAKUMA, Naoki, Koichiro DEGUCHI, and Iwao MORISHITA. "Image Figure Segmentation Using Morphological Skeleton." Transactions of the Society of Instrument and Control Engineers 29, no. 11 (1993): 1361–68. http://dx.doi.org/10.9746/sicetr1965.29.1361.

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Lee, Jonha, Dong-Wook Kim, Chee Won, and Seung-Won Jung. "Graph Cut-Based Human Body Segmentation in Color Images Using Skeleton Information from the Depth Sensor." Sensors 19, no. 2 (January 18, 2019): 393. http://dx.doi.org/10.3390/s19020393.

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Segmentation of human bodies in images is useful for a variety of applications, including background substitution, human activity recognition, security, and video surveillance applications. However, human body segmentation has been a challenging problem, due to the complicated shape and motion of a non-rigid human body. Meanwhile, depth sensors with advanced pattern recognition algorithms provide human body skeletons in real time with reasonable accuracy. In this study, we propose an algorithm that projects the human body skeleton from a depth image to a color image, where the human body region is segmented in the color image by using the projected skeleton as a segmentation cue. Experimental results using the Kinect sensor demonstrate that the proposed method provides high quality segmentation results and outperforms the conventional methods.
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Moreno-Avendano, Santiago, Daniel Mejia-Parra, and Oscar Ruiz-Salguero. "Triangle mesh skeletonization using non-deterministic voxel thinning and graph spectrum segmentation." MATEC Web of Conferences 336 (2021): 02030. http://dx.doi.org/10.1051/matecconf/202133602030.

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In the context of shape processing, the estimation of the medial axis is relevant for the simplification and re-parameterization of 3D bodies. The currently used methods are based on (1) General fields, (2) Geometric methods and (3) voxel-based thinning. They present shortcomings such as (1) overrepresentation and non-smoothness of the medial axis due to high frequency nodes and (2) biased-skeletons due to skewed thinning. To partially overcome these limitations, this article presents a non-deterministic algorithm for the estimation of the 1D skeleton of triangular B-Reps or voxel-based body representations. Our method articulates (1) a novel randomized thinning algorithm that avoids possible skewings in the final skeletonization, (2) spectral-based segmentation that eliminates short dead-end branches, and (3) a maximal excursion method for reduction of high frequencies. The test results show that the randomized order in the removal of the instantaneous skin of the solid region eliminates bias of the skeleton, thus respecting features of the initial solid. An Alpha Shape-based inversion of the skeleton encoding results in triangular boundary Representations of the original body, which present reasonable quality for fast non-minute scenes. Future work is needed to (a) tune the spectral filtering of high frequencies off the basic skeleton and (b) extend the algorithm to solid regions whose skeletons mix 1D and 2D entities.
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Grun, Tobias B., and James H. Nebelsick. "Structural design of the minute clypeasteroid echinoid Echinocyamus pusillus." Royal Society Open Science 5, no. 5 (May 2018): 171323. http://dx.doi.org/10.1098/rsos.171323.

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The clypeasteroid echinoid skeleton is a multi-plated, light-weight shell construction produced by biomineralization processes. In shell constructions, joints between individual elements are considered as weak points, yet these echinoid skeletons show an extensive preservation potential in both Recent and fossil environments. The remarkable strength of the test is achieved by skeletal reinforcement structures and their constructional layouts. Micro-computed tomography and scanning electron microscopy are used for microstructural and volumetric analyses of the echinoid's skeleton. It is shown that strengthening mechanisms act on different hierarchical levels from the overall shape of the skeleton to skeletal interlocking. The tight-fitting and interlocking plate joints lead to a shell considered to behave as a monolithic structure. The plate's architecture features distinct regions interpreted as a significant load-transferring system. The internal support system follows the segmentation of the remaining skeleton, where sutural layout and stereom distribution are designed for effective load transfer. The structural analysis of the multi-plated, yet monolithic skeleton of Echinocyamus pusillus reveals new aspects of the micro-morphology and its structural relevance for the load-bearing behaviour. The analysed structural principles allow E. pusillus to be considered as a role model for the development of multi-element, light-weight shell constructions.
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Sun, Xiaopeng, J. Pan, and Xiaopeng Wei. "3D mesh skeleton extraction using prominent segmentation." Computer Science and Information Systems 7, no. 1 (2010): 63–74. http://dx.doi.org/10.2298/csis1001063s.

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Skeleton of 3D mesh is a fundamental shape feature, and is useful for shape description and other many applications in 3D Digital Geometry Processing. This paper presents a novel skeleton extraction algorithm based on feature point and core extraction by the Multidimensional scaling (MDS) transformation. The algorithm first straights the folded prominent branch up, as well as the prominent shape feature points of mesh are computed, a meaningful segmentation is applied under the direction of feature points. The Node-ring of all segmented components is defined by discrete geodesic path on mesh surface, and then the skeleton of every segmented component is defined as the link of the Node-ring's center. As to the core component without prominent feature points, principal curve is used to fit its skeleton. Our algorithm is simple, and invariant both to the pose of the mesh and to the different proportions of model's components.
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CHENG, JIN-CHANG, and HON-SON DON. "SEGMENTATION OF BILEVEL IMAGES USING MATHEMATICAL MORPHOLOGY." International Journal of Pattern Recognition and Artificial Intelligence 06, no. 04 (October 1992): 595–628. http://dx.doi.org/10.1142/s0218001492000321.

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This paper presents the results of a study on the use of morphological skeleton transformation to segment gray-scale images into bilevel images. When a bilevel image (such as printed texts and machine tools) is digitized, the result is a gray-scale image due to the point spread function of digitizer, non-uniform illumination and noise. Our method can recover the original bilevel image from the gray-scale image. The theoretical basis of the algorithm is the physical structure of the skeleton set. A connectivity property of the gray-scale skeleton transformation is used to separate and remove the background terrain. The object pixels can then be obtained by applying a global threshold. Experimental results are given.
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Li Renzhong, 李仁忠, 刘哲闻 Liu Zhewen, and 刘阳阳 Liu Yangyang. "Segmentation Algorithm Based on Point Cloud Skeleton." Laser & Optoelectronics Progress 56, no. 22 (2019): 221102. http://dx.doi.org/10.3788/lop56.221102.

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Singh, M., and J. Feldman. "Skeleton-based segmentation of shapes into parts." Journal of Vision 8, no. 6 (March 29, 2010): 719. http://dx.doi.org/10.1167/8.6.719.

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Grosgeorge, Damien, Caroline Petitjean, Bernard Dubray, and Su Ruan. "Esophagus Segmentation from 3D CT Data Using Skeleton Prior-Based Graph Cut." Computational and Mathematical Methods in Medicine 2013 (2013): 1–6. http://dx.doi.org/10.1155/2013/547897.

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The segmentation of organs at risk in CT volumes is a prerequisite for radiotherapy treatment planning. In this paper, we focus on esophagus segmentation, a challenging application since the wall of the esophagus, made of muscle tissue, has very low contrast in CT images. We propose in this paper an original method to segment in thoracic CT scans the 3D esophagus using a skeleton-shape model to guide the segmentation. Our method is composed of two steps: a 3D segmentation by graph cut with skeleton prior, followed by a 2D propagation. Our method yields encouraging results over 6 patients.
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Kontges, G., and A. Lumsden. "Rhombencephalic neural crest segmentation is preserved throughout craniofacial ontogeny." Development 122, no. 10 (October 1, 1996): 3229–42. http://dx.doi.org/10.1242/dev.122.10.3229.

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To investigate the influence of hindbrain segmentation on craniofacial patterning we have studied the long term fate of neural crest (NC) subpopulations of individual rhombomeres (r), using quail-chick chimeras. Mapping of all skeletal and muscle connective tissues developing from these small regions revealed several novel features of the cranial neural crest. First, the mandibular arch skeleton has a composite origin in which the proximal elements are r1+r2 derived, whereas more distal ones are exclusively midbrain derived. The most proximal region of the lower jaw is derived from second arch (r4) NC. Second, both the lower jaw and tongue skeleton display an organisation which precisely reflects the rostrocaudal order of segmental crest deployment from the embryonic hindbrain. Third, cryptic intraskeletal boundaries, which do not correspond to anatomical landmarks, form sharply defined interfaces between r1+r2, r4 and r6+r7 crest. Cells that survive the early apoptotic elimination of premigratory NC in r3 and r5 are restricted to tiny contributions within the 2nd arch (r4) skeleton. Fourth, a highly constrained pattern of cranial skeletomuscular connectivity was found that precisely respects the positional origin of its constitutive crest: each rhombomeric population remains coherent throughout ontogeny, forming both the connective tissues of specific muscles and their respective attachment sites onto the neuro- and viscerocranium. Finally, focal clusters of crest cells, confined to the attachment sites of branchial muscles, intrude into the otherwise mesodermal cranial base. In the viscerocranium, an equally strict, rhombomere-specific matching of muscle connective tissues and their attachment sites is found for all branchial and tongue (hypoglossal) muscles. This coherence of segmental crest populations explains how cranial skeletomuscular pattern can be implemented and conserved despite evolutionary changes in the shapes of skeletal elements.
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Dissertations / Theses on the topic "Skeleton segmentation"

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Hedström, Anders. "Automatic Segmentation of Skeleton in Whole-Body MR Images." Thesis, Uppsala universitet, Institutionen för informationsteknologi, 2013. http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-211221.

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Magnetic Resonance Imaging(MRI) has developed as a widespread technique to examine various body parts and diagnose a wide range of diseases. MRI can often be superior to other imaging techniques such as Computed Tomography(CT) since it does not use ionizing radiation and can give a clearer image of soft tissue. As MRI becomes a more important part in medicine the demands on software to analyse the images and extract useful information increases. Today medical image analysis can be used to localise tumours, measure brain substance and to isolate specific organs. Although much has happened in the field in recent years there is still little published about segmentation of skeleton in MRI images, this might be because cortical bonen either contains fat nor water and thus gives a weak signal in MRI images. Skeletal segmentation could still be useful to localise other body parts, to guide further analysis of whole body images and to do attenuation correction in PET/MRI systems. This work aims to increase the knowledge about skeletal segmentation in fat and water(FWI) MR images, and the goal is to produce a method that is flexible and robust enough to work on different MR machines with patients of various body types. This work implemented and evaluated two methods for skeletal segmentation in fat and water MR images. The first method divided the body into different regions and segmented each region with a region-specific algorithm and the other method consisted of a filter that detect patterns in the proximity of bone.The evaluation used reference segmentations performed with the program SmartPaint, and overlap with the automatic method was measured. Subjects used in this work originated from two studies, one on small patients and one on larger patients, thus giving an indication of how well the methods work on a population with large variance. Results show that the filter method produce a more accurate result than the body division method. The body division method had an average dice coefficient of 0.836, over segmentation ratio of 0.225 and under segmentation ratio of 0.120. The filter method had a dice coefficient of 0.944 and over and under segmentation rates were both 0.055. Both methods needed post processing in order to get a result that minimised the over segmentation in order to achieve an acceptable result. Neither of the methods allows accurate assessment of bone volume, but an approximation might be possible with the filter method. This project has shown that it is possible to segment skeleton in whole body MRimages with a decent result without using either registration or deformable models. More advanced methods will most likely be needed to minimise the over segmentation and increase segmentation accuracy.
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Lidayová, Kristína. "Fast Methods for Vascular Segmentation Based on Approximate Skeleton Detection." Doctoral thesis, Uppsala universitet, Avdelningen för visuell information och interaktion, 2017. http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-318796.

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Modern medical imaging techniques have revolutionized health care over the last decades, providing clinicians with high-resolution 3D images of the inside of the patient's body without the need for invasive procedures. Detailed images of the vascular anatomy can be captured by angiography, providing a valuable source of information when deciding whether a vascular intervention is needed, for planning treatment, and for analyzing the success of therapy. However, increasing level of detail in the images, together with a wide availability of imaging devices, lead to an urgent need for automated techniques for image segmentation and analysis in order to assist the clinicians in performing a fast and accurate examination. To reduce the need for user interaction and increase the speed of vascular segmentation,  we propose a fast and fully automatic vascular skeleton extraction algorithm. This algorithm first analyzes the volume's intensity histogram in order to automatically adapt the internal parameters to each patient and then it produces an approximate skeleton of the patient's vasculature. The skeleton can serve as a seed region for subsequent surface extraction algorithms. Further improvements of the skeleton extraction algorithm include the expansion to detect the skeleton of diseased arteries and the design of a convolutional neural network classifier that reduces false positive detections of vascular cross-sections. In addition to the complete skeleton extraction algorithm, the thesis presents a segmentation algorithm based on modified onion-kernel region growing. It initiates the growing from the previously extracted skeleton and provides a rapid binary segmentation of tubular structures. To provide the possibility of extracting precise measurements from this segmentation we introduce a method for obtaining a segmentation with subpixel precision out of the binary segmentation and the original image. This method is especially suited for thin and elongated structures, such as vessels, since it does not shrink the long protrusions. The method supports both 2D and 3D image data. The methods were validated on real computed tomography datasets and are primarily intended for applications in vascular segmentation, however, they are robust enough to work with other anatomical tree structures after adequate parameter adjustment, which was demonstrated on an airway-tree segmentation.
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Pérez, Rocha Ana Laura. "Segmentation and Line Filling of 2D Shapes." Thèse, Université d'Ottawa / University of Ottawa, 2013. http://hdl.handle.net/10393/23676.

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The evolution of technology in the textile industry reached the design of embroidery patterns for machine embroidery. In order to create quality designs the shapes to be embroidered need to be segmented into regions that define different parts. One of the objectives of our research is to develop a method to automatically segment the shapes and by doing so making the process faster and easier. Shape analysis is necessary to find a suitable method for this purpose. It includes the study of different ways to represent shapes. In this thesis we focus on shape representation through its skeleton. We make use of a shape's skeleton and the shape's boundary through the so-called feature transform to decide how to segment a shape and where to place the segment boundaries. The direction of stitches is another important specification in an embroidery design. We develop a technique to select the stitch orientation by defining direction lines using the skeleton curves and information from the boundary. We compute the intersections of segment boundaries and direction lines with the shape boundary for the final definition of the direction line segments. We demonstrate that our shape segmentation technique and the automatic placement of direction lines produce sufficient constrains for automated embroidery designs. We show examples for lettering, basic shapes, as well as simple and complex logos.
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HE, LEI. "A COMPARISON OF DEFORMABLE CONTOUR METHODS AND MODEL BASED APPROACH USING SKELETON FOR SHAPE RECOVERY FROM IMAGES." University of Cincinnati / OhioLINK, 2003. http://rave.ohiolink.edu/etdc/view?acc_num=ucin1059746287.

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Belbaisi, Adham. "Deep Learning-Based Skeleton Segmentation for Analysis of Bone Marrow and Cortical Bone in Water-Fat Magnetic Resonance Imaging." Thesis, KTH, Skolan för kemi, bioteknologi och hälsa (CBH), 2021. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-297528.

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A major health concern for subjects with diabetes is weaker bones and increased fracture risk. Current clinical assessment of the bone strength is performed by measuring Bone Mineral Density (BMD), where low BMD-values are associated with an increased risk of fracture. However, subjects with Type 2 Diabetes (T2D) have been shown to have normal or higher BMD-levels compared to healthy controls, which does not reflect the recognized bone fragility among diabetics. Thus, there is need for more research about diabetes-related bone fragility to find other factors of impaired bone health. One potential biomarker that has recently been studied is Bone Marrow Fat (BMF). The data in this project consisted of whole-body water-fat Magnetic Resonance Imaging (MRI) volumes from the UK Biobank Imaging study (UKBB). Each subject in this data has a water volume and a fat volume, allowing for a quantitative assessment of water and fat content in the body. To analyze and perform quantitative measurements of the bones specifically, a Deep Learning (DL) model was trained, validated, and tested for performing fully automated and objective skeleton segmentation, where six different bones were segmented: spine, femur, pelvis, scapula, clavicle and humerus. The model was trained and validated on 120 subjects with 6-fold cross-validation and tested on eight subjects. All ground-truth segmentations of the training and test data were generated using two semi-automatic pipelines. The model was evaluated for each bone separately as well as the overall skeleton segmentation and achieved varying accuracy, performing better on larger bones than on smaller ones. The final trained model was applied on a larger dataset of 9562 subjects (16% type 2 diabetics) and the BMF, as well as bone marrow volume (BMV) and cortical bone volume (CBV), were measured in the segmented bones of each subject. The results of the quantified biomarkers were compared between T2D and healthy subjects. The comparison revealed possible differences between healthy and diabetic subjects, suggesting a potential for new findings related to diabetes and associated bone fragility.
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Limkhaitir, Mohamed Mahmoud. "Modélisation des formes volumiques à partir d'images tomographiques 3D : application à la Caractérisation de l'espace poral du sol." Thesis, Paris 6, 2014. http://www.theses.fr/2014PA066556.

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Nous présentations dans ce travail une méthode de représentation des formes volumiques 3D complexes. Nous dé nissons une forme volumique 3D par un ensemble de voxels extrait d'un traitement d'images Tomographiques 3D. cet ensemble est définit par sa fonction indicatrice. Notre objectif est le calcul d'une approximation analytique continue par morceau, compact, stable et robuste de la forme initiale, qui conserve ses propriétés topologiques et géométriques. Nous proposons une description de la forme par un ensemble minimum de boules incluses dans la forme et recouvrant son squelette. Nous démontrons le fait que cela revient à chercher un ensemble minimum de boules maximales recouvrant le squelette de la forme. Notre nouvelle représentation de la forme volumique, que nous appellerons MISS, donne une description optimal des cavités de la forme. Nous proposons un algorithme basé sur la triangulation de Delaunay 3D pour le calcul de la représentation MISS d'une forme volumique décrite par un ensemble de voxels. De cette représentation primaire nous arriverons à fournir une approximation par des primitives plus sophistiquées : cylindres, cônes et cylindres généralisés. Ainsi, nous proposons un algorithme pour calculer ces primitives à partir d'un réseau de boules. Le résultat nal est une description robuste intrinsèque de la forme initiale à la fois par des boules, cylindres, cônes et cylindres généralisés. Nous appliquons notre algorithme sur des images tomographique 3D du sol a n de fournir une description géométrique intrinsèque et robuste de l'espace poral ; cette description peut être, ensuite, utilisée pour la simulation des dynamiques biologiques du sol
In this thesis we present a primary representation for complex 3D volume shape. We de fine a 3D volume shape by a set of voxels derived from a computed tomography volume image. In a theoretical point of view, this set of voxels defi nes its indicatrix function. The basic idea is to look for a compact, stable and robust piece wise analytic approximation of the shape which conserves its topological and geometrical properties. We propose to describe a volume shape by a minimal number of balls included within the shape and recovering the shape skeleton. We show that it is equivalent to find out a (fi nite) minimal set of "maximal balls" recovering the skeleton. In the case where the absolute values of the principal curvatures of the shape envelope are bounded above we prove that such a finite set does exist. Indeed, our new shape representation provides an optimal description of the shape cavities. We propose an algorithm based on Delaunay 3D triangulation to compute the MISS of a volume shape described by a set of voxels. Afterwards, this representation can be used to approximate the shape using more sophisticated primitives like cylinders, cones, generalized cylinders. We propose algorithms to provide optimal cylinders and cones from ball network. The final result is an intrinsic and robust description of the initial shape using both balls, cylinders, cones. This scheme can be extended by using also curved cylinders and curved cones. Finally, we apply our algorithm to 3D volume Computed Tomography soil data in order to provide intrinsic and robust geometrical description of pore space to be used for biological dynamics simulation and modeling
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Erdem, Mehmet Erkut. "Simultaneous Bottom-up/top-down Processing In Early And Mid Level Vision." Phd thesis, METU, 2008. http://etd.lib.metu.edu.tr/upload/12610167/index.pdf.

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The prevalent view in computer vision since Marr is that visual perception is a data-driven bottom-up process. In this view, image data is processed in a feed-forward fashion where a sequence of independent visual modules transforms simple low-level cues into more complex abstract perceptual units. Over the years, a variety of techniques has been developed using this paradigm. Yet an important realization is that low-level visual cues are generally so ambiguous that they could make purely bottom-up methods quite unsuccessful. These ambiguities cannot be resolved without taking account of high-level contextual information. In this thesis, we explore different ways of enriching early and mid-level computer vision modules with a capacity to extract and use contextual knowledge. Mainly, we integrate low-level image features with contextual information within uni&
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ed formulations where bottom-up and top-down processing take place simultaneously.
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Gopalan, Sowmya. "Estimating Columnar Grain Size in Steel-Weld Images using Image Processing Techniques." The Ohio State University, 2009. http://rave.ohiolink.edu/etdc/view?acc_num=osu1250621610.

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Essafi, Salma. "3D Knowledge-based Segmentation Using Sparse Hierarchical Models : contribution and Applications in Medical Imaging." Phd thesis, Ecole Centrale Paris, 2010. http://tel.archives-ouvertes.fr/tel-00534805.

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CETTE thèse est consacrée à la conception d'un système d'aide au diagnostic dédiéau muscle squelettique humain. Au cours du premier volet de ce manuscrit nousproposons une nouvelle représentation basée sur les modèles parcimonieux dans le cadrede la segmentation d'Images de Résonances Magnétiques (IRM) T1 du muscle squelettiquedu mollet. Notre méthode Sparse Shape Model/ Modèle de Formes Parcimonieux(MFP), apprend un modèle statistique de formes et de textures locales annoté et réussità en tirer une représentation réduite afin de reconstruire le mécanisme musculaire sur unexemple test. Dans la seconde partie du manuscrit, nous présentons une approche baséesur des ondelettes de diffusion pour la segmentation du muscle squelettique. Contrairementaux méthodes de l'état de l'art, notre approche au cours de la phase d'apprentissagepermet à optimiser les coefficients des ondelettes, ainsi que leur nombres et leur positions.Le modèle prend en charge aussi bien les hiérarchies dans l'espace de recherche,que l'encodage des dépendances géométriques complexes et photométriques de la structured'intérêt. Notre modélisation offre ainsi l'avantage de traiter des topologies arbitraires.L'évaluation expérimentale a été effectué sur un ensemble de mollets acquisespar un scanner IRM, ainsi qu'un ensemble d'images tomodensitométriques du ventriculegauche.
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Karlsson, Edlund Patrick. "Methods and models for 2D and 3D image analysis in microscopy, in particular for the study of muscle cells." Doctoral thesis, Uppsala : Acta Universitatis Upsaliensis, 2008. http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-9201.

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Books on the topic "Skeleton segmentation"

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F, Nielsen Poul M., Miller Karol, and SpringerLink (Online service), eds. Computational Biomechanics for Medicine: Soft Tissues and the Musculoskeletal System. New York, NY: Springer Science+Business Media, LLC, 2011.

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Burton, Derek, and Margaret Burton. The skeleton, support and movement. Oxford University Press, 2017. http://dx.doi.org/10.1093/oso/9780198785552.003.0003.

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Buoyancy largely supports fish, reducing the role of the skeleton, which functions as an attachment for muscle involved in movement and in protection, as exoskeleton (scales, scutes, bony plates) and as endoskeleton (vertebral column, skull). The general organization of fish skeletons and their component parts are described, as well as bone and cartilage. The interesting occurrence of acellular bone, additional to cellular bone, in teleosts is considered. Fish show metameric segmentation with myotomes on either side of the vertebral column, the latter acting as a compression strut, preventing shortening. Myotome muscle is organized into linear units named sarcomeres which contract by means of protein fibres, myosin and actin, sliding past each other. Usually fish body wall muscles occur as a thin outer layer of aerobic red muscle, with an inner thick region of anaerobic white muscle. Interspecific variability in the relative roles of myotomes and fin musculature in swimming is discussed.
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Book chapters on the topic "Skeleton segmentation"

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Gaillard, Mathieu, Chenyong Miao, James Schnable, and Bedrich Benes. "Sorghum Segmentation by Skeleton Extraction." In Computer Vision – ECCV 2020 Workshops, 296–311. Cham: Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-65414-6_21.

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Feng, Cong, Andrei C. Jalba, and Alexandru C. Telea. "Part-Based Segmentation by Skeleton Cut Space Analysis." In Lecture Notes in Computer Science, 607–18. Cham: Springer International Publishing, 2015. http://dx.doi.org/10.1007/978-3-319-18720-4_51.

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Lovato, Christian, Umberto Castellani, and Andrea Giachetti. "Automatic Segmentation of Scanned Human Body Using Curve Skeleton Analysis." In Computer Vision/Computer Graphics CollaborationTechniques, 34–45. Berlin, Heidelberg: Springer Berlin Heidelberg, 2009. http://dx.doi.org/10.1007/978-3-642-01811-4_4.

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Yangel, Boris, and Dmitry Vetrov. "Image Segmentation with a Shape Prior Based on Simplified Skeleton." In Lecture Notes in Computer Science, 247–60. Berlin, Heidelberg: Springer Berlin Heidelberg, 2011. http://dx.doi.org/10.1007/978-3-642-23094-3_18.

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Wu, Zonghan, Baochang Zhang, Jun Yang, Na Li, and Shoujun Zhou. "Segmentation of Arteriovenous Malformation Based on Weighted Breadth-First Search of Vascular Skeleton." In Communications in Computer and Information Science, 294–301. Cham: Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-39343-4_25.

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Rabatel, Gilles, Anne-Gaëlle Manh, Marie-José Aldon, and Bernard Bonicelli. "Skeleton-Based Shape Models with Pressure Forces: Application to Segmentation of Overlapping Leaves." In Lecture Notes in Computer Science, 249–59. Berlin, Heidelberg: Springer Berlin Heidelberg, 2001. http://dx.doi.org/10.1007/3-540-45129-3_22.

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Ng, Kok-Why, Abdullah Junaidi, and Sew-Lai Ng. "Semi-automatic Segmentation of 3D Point Clouds Skeleton without Explicit Computation for Critical Points." In Lecture Notes in Computer Science, 783–88. Berlin, Heidelberg: Springer Berlin Heidelberg, 2012. http://dx.doi.org/10.1007/978-3-642-32695-0_73.

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Shankar, Venkatesh Gauri, Bali Devi, Ujwal Sachdeva, and Harsh Harsola. "Real-Time Human Body Tracking System for Posture and Movement Using Skeleton-Based Segmentation." In Micro-Electronics and Telecommunication Engineering, 499–510. Singapore: Springer Singapore, 2021. http://dx.doi.org/10.1007/978-981-33-4687-1_48.

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Xie, Wenjie, Renato Perucchio, David Sedmera, and Robert P. Thompson. "Topological Segmentation and Smoothing of Discrete Curve Skeletons." In Computer-Aided Intelligent Recognition Techniques and Applications, 389–409. Chichester, UK: John Wiley & Sons, Ltd, 2005. http://dx.doi.org/10.1002/0470094168.ch20.

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Röhrle, O., H. Köstler, and M. Loch. "Segmentation of Skeletal Muscle Fibres for Applications in Computational Skeletal Muscle Mechanics." In Computational Biomechanics for Medicine, 107–17. New York, NY: Springer New York, 2011. http://dx.doi.org/10.1007/978-1-4419-9619-0_12.

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Conference papers on the topic "Skeleton segmentation"

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"Skeleton-Based Shape Segmentation." In International Workshop on Image Mining Theory and Applications. SciTePress - Science and and Technology Publications, 2009. http://dx.doi.org/10.5220/0001963500840092.

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Neubauer, Andre, and Rainer Wegenkittl. "Skeleton-based myocardium segmentation." In Electronic Imaging 2003, edited by Robert F. Erbacher, Philip C. Chen, Jonathan C. Roberts, Matti T. Groehn, and Katy Boerner. SPIE, 2003. http://dx.doi.org/10.1117/12.473945.

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Reniers, Dennie, and Alexandru Telea. "Skeleton-based Hierarchical Shape Segmentation." In IEEE International Conference on Shape Modeling and Applications 2007 (SMI '07). IEEE, 2007. http://dx.doi.org/10.1109/smi.2007.33.

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Cai, Ling, Fengna Wang, Valentin Enescu, and Hichem Sahli. "Object Segmentation Based on Contour-Skeleton Duality." In 2014 22nd International Conference on Pattern Recognition (ICPR). IEEE, 2014. http://dx.doi.org/10.1109/icpr.2014.438.

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de Belen, Ryan Anthony J., and Rowel O. Atienza. "Automatic skeleton generation using hierarchical mesh segmentation." In SA '16: SIGGRAPH Asia 2016. New York, NY, USA: ACM, 2016. http://dx.doi.org/10.1145/2992138.2992150.

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Jacques Junior, Julio C. S., Claudio R. Jung, and Soraia R. Musse. "Skeleton-based human segmentation in still images." In 2012 19th IEEE International Conference on Image Processing (ICIP 2012). IEEE, 2012. http://dx.doi.org/10.1109/icip.2012.6466815.

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Manolas, Iason, Aris S. Lalos, and Konstantinos Moustakas. "Parallel 3D Skeleton Extraction Using Mesh Segmentation." In 2018 International Conference on Cyberworlds (CW). IEEE, 2018. http://dx.doi.org/10.1109/cw.2018.00041.

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Yu, Donggang, Tuan D. Pham, Hong Yan, Wei Lai, Denis I. Crane, Tuan D. Pham, and Xiaobo Zhou. "Segmentation and Reconstruction of Cultured Neuron Skeleton." In COMPUTATIONAL MODELS FOR LIFE SCIENCES/CMLS '07. AIP, 2007. http://dx.doi.org/10.1063/1.2816626.

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Wshah, Safwan, Zhixin Shi, and Venu Govindaraju. "Segmentation of Arabic Handwriting Based on both Contour and Skeleton Segmentation." In 2009 10th International Conference on Document Analysis and Recognition. IEEE, 2009. http://dx.doi.org/10.1109/icdar.2009.152.

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Tal, Ayellet. "Mesh Segmentation for CAD Applications." In ASME 2008 9th Biennial Conference on Engineering Systems Design and Analysis. ASMEDC, 2008. http://dx.doi.org/10.1115/esda2008-59565.

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Abstract:
Segmentation of meshes has received a lot of attention in recent years, due to its growing number of applications. In this paper, we discuss properties that have been used in the literature to evaluate segmentation algorithms. Then, we describe some applications of segmentation in CAD. For each application, we review one of our segmentation algorithms that is suitable for the problem. We focus on four applications: modeling by example, shape-based retrieval, skeleton extraction, and paper crafting.
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