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Journal articles on the topic 'Skeleton segmentation'

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1

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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2

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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8

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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9

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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10

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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LI, YANLI, ZHONG ZHOU, and WEI WU. "A UNIFIED FRAMEWORK FOR JOINT VIDEO PEDESTRIAN SEGMENTATION AND POSE TRACKING." International Journal of Pattern Recognition and Artificial Intelligence 27, no. 07 (November 2013): 1355012. http://dx.doi.org/10.1142/s0218001413550124.

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Pedestrian segmentation and pose tracking are performed to infer human silhouettes and skeletons, respectively. Although the two tasks are complementary in nature, few works have been done on combining them together to improve each other, and some related methods are limited to still images. In this paper, we propose an approach to jointly solving them in monocular videos via a unified framework. Basically, the framework is built on EM-based maximum likelihood estimation, in which pose tracking is fulfilled through Bayesian filtering using body silhouette as an observation cue, and pedestrian segmentation is inferred by guided filtering with constraint of body skeleton. The two sets of parameters are alternatively updated along the video. In the initialization of the framework, we utilize a hierarchical shape matching scheme to obtain the silhouette and skeleton in the first frame. Experiments on challenging pedestrian datasets verify the approach's effectiveness to cluttered backgrounds, moving camera and various articulated bodies, and the performance is improved significantly by solving the two tasks together.
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12

Deng, Wu, Kai Luo, Qinke Shi, Yi Yang, and Ning Ning. "Automatic Segmentation and Diagnosis Based on Multi-Scale Two-Stage Region Growing and Skeleton Extraction for Vessel Stenosis in Coronary Angiography." Journal of Medical Imaging and Health Informatics 10, no. 2 (February 1, 2020): 446–51. http://dx.doi.org/10.1166/jmihi.2020.2878.

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Although great progress has been made in vessel segmentation, the existing methods still can not accurately segment small vessels. A novel vessel segmentation and automatic diagnosis in coronary angiography image was proposed. During vessel segmentation, a new vessel function based on Hessian matrix was put forward. Then the vessel contour was extracted by the dual-stage region growing with automatic selection of seed point. Next, the automatic diagnosis was realized by vessel skeleton extraction, skeleton point search and diameter measurement. The experimental results demonstrate that our proposed vessel segmentation can extract the main branch contour accurately and have a good effect on the enhancement and segmentation of small vessels. The automatic diagnosis of vessel stenosis is fast. With a relatively accurate diagnosis result, it can provide a good reference and quantitative basis for the final judgment of the doctor.
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13

Bates, Alan William, and Krsty Nale. "SEGMENTATION DEFECTS OF THE HUMAN AXIAL SKELETON WITHOUT DYSOSTOSES OR SKELETAL DYSPLASIAS." Fetal and Pediatric Pathology 24, no. 2 (January 2005): 121–27. http://dx.doi.org/10.1080/15227950500257333.

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14

Wu, Kan, Li Chen, Jing Li, and Yanheng Zhou. "Tooth segmentation on dental meshes using morphologic skeleton." Computers & Graphics 38 (February 2014): 199–211. http://dx.doi.org/10.1016/j.cag.2013.10.028.

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15

Shimizu, Akinobu, Hayato Wakabayashi, Takumi Kanamori, Atsushi Saito, Kazuhiro Nishikawa, Hiromitsu Daisaki, Shigeaki Higashiyama, and Joji Kawabe. "Automated measurement of bone scan index from a whole-body bone scintigram." International Journal of Computer Assisted Radiology and Surgery 15, no. 3 (December 13, 2019): 389–400. http://dx.doi.org/10.1007/s11548-019-02105-x.

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Abstract Purpose We propose a deep learning-based image interpretation system for skeleton segmentation and extraction of hot spots of bone metastatic lesion from a whole-body bone scintigram followed by automated measurement of a bone scan index (BSI), which will be clinically useful. Methods The proposed system employs butterfly-type networks (BtrflyNets) for skeleton segmentation and extraction of hot spots of bone metastatic lesions, in which a pair of anterior and posterior images are processed simultaneously. BSI is then measured using the segmented bones and extracted hot spots. To further improve the networks, deep supervision (DSV) and residual learning technologies were introduced. Results We evaluated the performance of the proposed system using 246 bone scintigrams of prostate cancer in terms of accuracy of skeleton segmentation, hot spot extraction, and BSI measurement, as well as computational cost. In a threefold cross-validation experiment, the best performance was achieved by BtrflyNet with DSV for skeleton segmentation and BtrflyNet with residual blocks. The cross-correlation between the measured and true BSI was 0.9337, and the computational time for a case was 112.0 s. Conclusion We proposed a deep learning-based BSI measurement system for a whole-body bone scintigram and proved its effectiveness by threefold cross-validation study using 246 whole-body bone scintigrams. The automatically measured BSI and computational time for a case are deemed clinically acceptable and reliable.
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16

Lewandowicz, Elżbieta, and Paweł Flisek. "Base Point Split Algorithm for Generating Polygon Skeleton Lines on the Example of Lakes." ISPRS International Journal of Geo-Information 9, no. 11 (November 15, 2020): 680. http://dx.doi.org/10.3390/ijgi9110680.

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This article presents the Base Point Split (BPSplit) algorithm to generate a complex polygon skeleton based on sets of vector data describing lakes and rivers. A key feature of the BPSplit algorithm is that it is dependent on base points representing the source or mouth of a river or a stream. The input values of base points determine the shape of the resulting skeleton of complex polygons. Various skeletons can be generated with the use of different base points. Base points are applied to divide complex polygon boundaries into segments. Segmentation supports the selection of triangulated irregular network (TIN) edges inside complex polygons. The midpoints of the selected TIN edges constitute a basis for generating a skeleton. The algorithm handles complex polygons with numerous holes, and it accounts for all holes. This article proposes a method for modifying a complex skeleton with numerous holes. In the discussed approach, skeleton edges that do not meet the preset criteria (e.g., that the skeleton is to be located between holes in the center of the polygon) are automatically removed. An algorithm for smoothing zigzag lines was proposed.
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17

Lux, Jérôme. "AUTOMATIC SEGMENTATION AND STRUCTURAL CHARACTERIZATION OF LOW DENSITY FIBREBOARDS." Image Analysis & Stereology 32, no. 1 (March 19, 2013): 13. http://dx.doi.org/10.5566/ias.v32.p13-25.

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In this paper, a new skeleton-based algorithm for the segmentation of individual fibres in 3D tomographic images is described. The proposed method is designed to deal with low density materials featuring fibres with varied sizes, shapes and tortuosities, like composite fibreboards used for buildings insulation. To this end the paths of the skeleton are first classified according to their connectivity, the connectivity of their adjacent nodes, their orientation, their average radius and the variation of the distance transform along each path. This allows for the identification of spurious paths and paths linking two fibres. Reconstruction of the path of the fibres is done thanks to an optimal pairing algorithm which joins paths that show the most similar orientation and radius at each node/link. The segmented skeleton is finally dilated by means of a growing algorithm ordonned by the average radius of the fibres in order to reconstruct each identified fibres. As an application, the algorithm is used to segment a 3D tomographic image of hemp/polymer fibreboard for buildings insulation. Information such as the number of contacts, tortuosity, length, average radius, orientation of fibres are finally measured on both the segmented skeleton and reconstructed image, which allow for a thorough characterization of the fibre network.
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18

Trinh, Nhon H., and Benjamin B. Kimia. "Skeleton Search: Category-Specific Object Recognition and Segmentation Using a Skeletal Shape Model." International Journal of Computer Vision 94, no. 2 (January 22, 2011): 215–40. http://dx.doi.org/10.1007/s11263-010-0412-0.

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Kim, Minjoon, Zucheul Lee, and Wonha Kim. "Realtime Human Object Segmentation Using Image and Skeleton Characteristics." Journal of Broadcast Engineering 21, no. 5 (September 30, 2016): 782–91. http://dx.doi.org/10.5909/jbe.2016.21.5.782.

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HISHIDA, Hiroyuki, Takashi MICHIKAWA, Yutaka OHTAKE, Hiromasa SUZUKI, and Satoshi OOTA. "9D-03 Skeleton CT image segmentation using structural analysis." Proceedings of the Bioengineering Conference Annual Meeting of BED/JSME 2010.23 (2011): 359–60. http://dx.doi.org/10.1299/jsmebio.2010.23.359.

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Xiang, Dehui, Jie Tian, Fei Yang, Qi Yang, Xing Zhang, Qingde Li, and Xin Liu. "Skeleton Cuts—An Efficient Segmentation Method for Volume Rendering." IEEE Transactions on Visualization and Computer Graphics 17, no. 9 (September 2011): 1295–306. http://dx.doi.org/10.1109/tvcg.2010.239.

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22

Alexander, Tara, Christof Nolte, and Robb Krumlauf. "HoxGenes and Segmentation of the Hindbrain and Axial Skeleton." Annual Review of Cell and Developmental Biology 25, no. 1 (November 2009): 431–56. http://dx.doi.org/10.1146/annurev.cellbio.042308.113423.

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Nikolaou, Nikos, Michael Makridis, Basilis Gatos, Nikolaos Stamatopoulos, and Nikos Papamarkos. "Segmentation of historical machine-printed documents using Adaptive Run Length Smoothing and skeleton segmentation paths." Image and Vision Computing 28, no. 4 (April 2010): 590–604. http://dx.doi.org/10.1016/j.imavis.2009.09.013.

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Ward, Carol V., Thierra K. Nalley, Fred Spoor, Paul Tafforeau, and Zeresenay Alemseged. "Thoracic vertebral count and thoracolumbar transition in Australopithecus afarensis." Proceedings of the National Academy of Sciences 114, no. 23 (May 22, 2017): 6000–6004. http://dx.doi.org/10.1073/pnas.1702229114.

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The evolution of the human pattern of axial segmentation has been the focus of considerable discussion in paleoanthropology. Although several complete lumbar vertebral columns are known for early hominins, to date, no complete cervical or thoracic series has been recovered. Several partial skeletons have revealed that the thoracolumbar transition in early hominins differed from that of most extant apes and humans. Australopithecus africanus, Australopithecus sediba, and Homo erectus all had zygapophyseal facets that shift from thoracic-like to lumbar-like at the penultimate rib-bearing level, rather than the ultimate rib-bearing level, as in most humans and extant African apes. What has not been clear is whether Australopithecus had 12 thoracic vertebrae as in most humans, or 13 as in most African apes, and where the position of the thoracolumbar transitional element was. The discovery, preparation, and synchrotron scanning of the Australopithecus afarensis partial skeleton DIK-1-1, from Dikika, Ethiopia, provides the only known complete hominin cervical and thoracic vertebral column before 60,000 years ago. DIK-1-1 is the only known Australopithecus skeleton to preserve all seven cervical vertebrae and provides evidence for 12 thoracic vertebrae with a transition in facet morphology at the 11th thoracic level. The location of this transition, one segment cranial to the ultimate rib-bearing vertebra, also occurs in all other early hominins and is higher than in most humans or extant apes. At 3.3 million years ago, the DIK-1-1 skeleton is the earliest example of this distinctive and unusual pattern of axial segmentation.
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Do, Nhu-Tai, Soo-Hyung Kim, Hyung-Jeong Yang, and Guee-Sang Lee. "Robust Hand Shape Features for Dynamic Hand Gesture Recognition Using Multi-Level Feature LSTM." Applied Sciences 10, no. 18 (September 10, 2020): 6293. http://dx.doi.org/10.3390/app10186293.

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This study builds robust hand shape features from the two modalities of depth and skeletal data for the dynamic hand gesture recognition problem. For the hand skeleton shape approach, we use the movement, the rotations of the hand joints with respect to their neighbors, and the skeletal point-cloud to learn the 3D geometric transformation. For the hand depth shape approach, we use the feature representation from the hand component segmentation model. Finally, we propose a multi-level feature LSTM with Conv1D, the Conv2D pyramid, and the LSTM block to deal with the diversity of hand features. Therefore, we propose a novel method by exploiting robust skeletal point-cloud features from skeletal data, as well as depth shape features from the hand component segmentation model in order for the multi-level feature LSTM model to benefit from both. Our proposed method achieves the best result on the Dynamic Hand Gesture Recognition (DHG) dataset with 14 and 28 classes for both depth and skeletal data with accuracies of 96.07% and 94.40%, respectively.
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Domakhina, L. G. "Skeleton-based segmentation and decomposition of raster pairs of shapes." Pattern Recognition and Image Analysis 20, no. 3 (September 2010): 293–302. http://dx.doi.org/10.1134/s1054661810030053.

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27

Kikuchi, Akihiro, Masahisa Onoguchi, Hiroyuki Horikoshi, Karl Sjöstrand, and Lars Edenbrandt. "Automated segmentation of the skeleton in whole-body bone scans." Nuclear Medicine Communications 33, no. 9 (September 2012): 947–53. http://dx.doi.org/10.1097/mnm.0b013e3283567407.

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Khmelinskii, Artem, Harald C. Groen, Martin Baiker, Marion de Jong, and Boudewijn P. F. Lelieveldt. "Segmentation and Visual Analysis of Whole-Body Mouse Skeleton microSPECT." PLoS ONE 7, no. 11 (November 12, 2012): e48976. http://dx.doi.org/10.1371/journal.pone.0048976.

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Devadas, Sahana, Varun Govindarajan, Anil Kumar Hanumanna, Chethana Gowda, and Mallesh Kariyappa. "Jarcho-Levin syndrome term baby with recurrent apnea." International Journal of Contemporary Pediatrics 8, no. 7 (June 24, 2021): 1287. http://dx.doi.org/10.18203/2349-3291.ijcp20212489.

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Jarcho-Levin syndrome or spondylocostal dysostosis, is a rare axial skeleton anomaly due to mutation in genes involved in somitic segmentation during embryogenesis. We describe a term, newborn baby with antenatally detected midthoracic lordotic deformity with skeletal features of multiple rib anomalies and vertebral defects, but with normal limb lengths. Baby had recurrent apnea requiring non-invasive ventilation and was successfully weaned to room air within 2 days. This syndrome is underdiagnosed and we wish to highlight the simple process involved in making a clinico-radiological diagnosis.
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Wang, Peng Cheng, De Qun Li, Jin Long Zhao, Zhi Yan Zhen, and Liang Ming Yan. "Reconstruction of Human Skeleton Model Based on Selective Laser Sintering." Advanced Materials Research 189-193 (February 2011): 3659–63. http://dx.doi.org/10.4028/www.scientific.net/amr.189-193.3659.

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Based on CT data of the lesion of an orthopedic patient with knee, Mimics13.1, Magics9.5 can be used for the medical image processing. The CT image data were filtered, interpolated, sharpen, the interest region was extracted by the application of threshold segmentation method and was grown. The three dimension model of patient’s skeleton is reconstructed. Based on selective laser sintering, the digit model of patient’s skeleton reconstructed can be accurately transformed into the object model of the individual matching skeleton. The results indicated that the contour of reconstructed knee-joint bone object model were very coincident, and symmetric with knee-joint bone defect.
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Ye, Qing, Jun Feng Dong, and Yong Mei Zhang. "Real-Time Human Skeleton Extraction Based on Video Sequences." Applied Mechanics and Materials 401-403 (September 2013): 1410–14. http://dx.doi.org/10.4028/www.scientific.net/amm.401-403.1410.

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Thinning algorithm is widely used in image processing and pattern recognition.In this paper we proposed an optimized thinning algorithm based on Zhan-Suen thinning and applied it to video sequences of moving human body to extract real-time body skeleton. We firstly used background subtraction method to detect moving body, then made use of adaptive threshold segmentation to gain the binary moving body image, finally we used the optimized algorithm to the binary image and got its skeleton. The skeleton not only maintains the movement geometry and body image’s topological properties, also reduces image redundancy and computation cost, and helps us clearly recognize the moving body posture.
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Fu, Yabo, Shi Liu, H. Harold Li, and Deshan Yang. "Automatic and hierarchical segmentation of the human skeleton in CT images." Physics in Medicine and Biology 62, no. 7 (March 14, 2017): 2812–33. http://dx.doi.org/10.1088/1361-6560/aa6055.

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Adama, David Ada, Ahmad Lotfi, and Robert Ranson. "Adaptive Segmentation and Sequence Learning of human activities from skeleton data." Expert Systems with Applications 164 (February 2021): 113836. http://dx.doi.org/10.1016/j.eswa.2020.113836.

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Nguyen, Ngoc-Hoang, Tran-Dac-Thinh Phan, Guee-Sang Lee, Soo-Hyung Kim, and Hyung-Jeong Yang. "Gesture Recognition Based on 3D Human Pose Estimation and Body Part Segmentation for RGB Data Input." Applied Sciences 10, no. 18 (September 6, 2020): 6188. http://dx.doi.org/10.3390/app10186188.

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This paper presents a novel approach for dynamic gesture recognition using multi-features extracted from RGB data input. Most of the challenges in gesture recognition revolve around the axis of the presence of multiple actors in the scene, occlusions, and viewpoint variations. In this paper, we develop a gesture recognition approach by hybrid deep learning where RGB frames, 3D skeleton joint information, and body part segmentation are used to overcome such problems. Extracted from the RGB images are the multimodal input observations, which are combined by multi-modal stream networks suited to different input modalities: residual 3D convolutional neural networks based on ResNet architecture (3DCNN_ResNet) for RGB images and color body part segmentation modalities; long short-term memory network (LSTM) for 3D skeleton joint modality. We evaluated the proposed model on four public datasets: UTD multimodal human action dataset, gaming 3D dataset, NTU RGB+D dataset, and MSRDailyActivity3D dataset and the experimental results on these datasets proves the effectiveness of our approach.
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Zhu, Q., W. Jiang, and J. Zhang. "FEATURE LINE BASED BUILDING DETECTION AND RECONSTRUCTION FROM OBLIQUE AIRBORNE IMAGERY." ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XL-4/W5 (May 12, 2015): 199–204. http://dx.doi.org/10.5194/isprsarchives-xl-4-w5-199-2015.

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In this paper, a feature line based method for building detection and reconstruction from oblique airborne imagery is presented. With the development of Multi-View Stereo technology, increasing photogrammetric softwares are provided to generate textured meshes from oblique airborne imagery. However, errors in image matching and mesh segmentation lead to the low geometrical accuracy of building models, especially at building boundaries. To simplify massive meshes and construct accurate 3D building models, we integrate multi-view images and meshes by using feature lines, in which contour lines are used for building detection and straight skeleton for building reconstruction. Firstly, through the contour clustering method, buildings can be quickly and robustly detected from meshes. Then, a feature preserving mesh segmentation method is applied to accurately extract 3D straight skeleton from meshes. Finally, straight feature lines derived from multi-view images are used to rectify inaccurate parts of 3D straight skeleton of buildings. Therefore, low quality model can be refined by the accuracy improvement of mesh feature lines and rectification with feature lines of multi-view images. The test dataset in Zürich is provided by ISPRS/EuroSDR initiative Benchmark on High Density Image Matching for DSM Computation. The experiments reveal that the proposed method can obtain convincing and high quality 3D building models from oblique airborne imagery.
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Wang, Monan, Lei Sun, and Yuming Liu. "Anatomically Based Geometric Modelling Using Medical Image Data: Methods and Programs." Open Biomedical Engineering Journal 9, no. 1 (May 29, 2015): 126–31. http://dx.doi.org/10.2174/1874120701509010126.

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Geometric modeling software that can realize two-dimensional medical image browsing, preprocessing, and three-dimensional (3D) reconstruction is designed for modeling human organs. This software performs medical image segmentation using a method that combines the region growing and the interactive segmentation methods. The Marching Cubes surface reconstruction algorithm is used to obtain a 3D geometric model. The program is compiled using Visual Studio 2010. The software is employed to obtain the geometric model of the human femur, hipbone, and muscle. The geometric modeling results can accurately express the structural information of the skeleton and muscle.
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Zhao, Jingxiu, Qian Zhao, Riqiang Lin, and Jing Meng. "A microvascular image analysis method for optical-resolution photoacoustic microscopy." Journal of Innovative Optical Health Sciences 13, no. 04 (July 2020): 2050019. http://dx.doi.org/10.1142/s1793545820500194.

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Optical-resolution photoacoustic microscopy (OR-PAM) has been shown to be an excellent tool for high-resolution imaging of microvasculature, and quantitative analysis of the microvasculature can provide valuable information for the early diagnosis and treatment of various vascular-related diseases. In order to address the characteristics of weak signals, discontinuity and small diameters in photoacoustic microvascular images, we propose a method adaptive to the microvascular segmentation in photoacoustic images, including Hessian matrix enhancement and the morphological connection operators. The accuracy of our vascular segmentation method is quantitatively evaluated by the multiple criteria. To obtain more precise and continuous microvascular skeletons, an improved skeleton extraction framework based on the multistencil fast marching (MSFM) method is developed. We carried out in vivo OR-PAM microvascular imaging in mouse ears and subcutaneous hepatoma tumor model to verify the correctness and superiority of our proposed method. Compared with the previous methods, our proposed method can extract the microvascular network more completely, continuously and accurately, and provide an effective solution for the quantitative analysis of photoacoustic microvascular images with many small branches.
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Wang, Chao. "Research on the Detection Method of Implicit Self Symmetry in a High-Level Semantic Model." Symmetry 12, no. 1 (December 21, 2019): 28. http://dx.doi.org/10.3390/sym12010028.

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In order to improve the accuracy of semantic model intrinsic detection, a skeleton-based high-level semantic model intrinsic self-symmetry detection method is proposed. The semantic analysis of the model set is realized by the uniform segmentation of the model within the same style, the component correspondence of the model between different styles, and the shape content clustering. Based on the results of clustering analysis, for a given three-dimensional (3D) point cloud model, according to the curve skeleton, the skeleton point pairs reflecting the symmetry between the model surface points are obtained by the election method, and the symmetry is extended to the model surface vertices according to these skeleton point pairs. With the help of skeleton, the symmetry of the point cloud model is obtained, and then the symmetry region of point cloud model is obtained by the symmetric correspondence matrix and spectrum method, so as to realize the intrinsic symmetry detection of the model. The experimental results show that the proposed method has the advantages of less time, high accuracy, and high reliability.
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39

Idowu, N. A. A., C. Nardi, H. Long, T. Varslot, and P. E. E. Øren. "Effects of Segmentation and Skeletonization Algorithms on Pore Networks and Predicted Multiphase-Transport Properties of Reservoir-Rock Samples." SPE Reservoir Evaluation & Engineering 17, no. 04 (August 13, 2014): 473–83. http://dx.doi.org/10.2118/166030-pa.

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Summary Networks of large pores connected by narrower throats (pore networks) are essential inputs into network models that are routinely used to predict transport properties from digital rock images. Extracting pore networks from microcomputed-tomography (micro-CT) images of rocks involves a number of steps: filtering, segmentation, skeletonization, and others. Because of the amount of clay and its distribution, the segmentation of micro-CT images is not trivial, and different algorithms exist for achieving this. Similarly, several methods are available for skeletonizing the segmented images and for extracting the pore networks. The nonuniqueness of these processes raises questions about the predictive power of network models. In the present work, we evaluate the effects of these processes on the computed petrophysical and multiphase-flow properties of reservoir-rock samples. By use of micro-CT images of reservoir sandstones, we first apply three different segmentation algorithms and assess the effects of the different algorithms on estimated porosity, amount of clay, and clay distribution. Single-phase properties are computed directly on the segmented images and compared with experimental data. Next, we extract skeletons from the segmented images by use of three different algorithms. On the pore networks generated from the different skeletons, we simulate two-phase oil/ water and three-phase gas/oil/water displacements by use of a quasistatic pore-network model. Analysis of the segmentation results shows differences in the amount of clay, in the total porosity, and in the computed singlephase properties. Simulated results show that there are differences in the network-predicted single-phase properties as well. However, predicted multiphase-transport properties from the different networks are in good agreement. This indicates that the topology of the pore space is well preserved in the extracted skeleton. Comparison of the computed capillary pressure and relative permeability curves for all networks with available experimental data shows good agreements. By use of a segmentation that captures porosity and microporosity, we show that the extracted networks can be used to reliably predict multiphase-transport properties, irrespective of the algorithms used.
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Tsai, Joseph C., Shih Ming Chang, Shwu Huey Yen, Timothy K. Shih, and Kuan Ching Li. "3D skeleton construction by multi-view 2D images and 3D model segmentation." International Journal of Computational Science and Engineering 10, no. 4 (2015): 368. http://dx.doi.org/10.1504/ijcse.2015.070988.

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41

Eley, Karen A., and Gaspar Delso. "Automated Segmentation of the Craniofacial Skeleton With “Black Bone” Magnetic Resonance Imaging." Journal of Craniofacial Surgery 31, no. 4 (June 2020): 1015–17. http://dx.doi.org/10.1097/scs.0000000000006552.

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42

Hosseini, Babak, Romain Montagne, and Barbara Hammer. "Deep-Aligned Convolutional Neural Network for Skeleton-Based Action Recognition and Segmentation." Data Science and Engineering 5, no. 2 (May 16, 2020): 126–39. http://dx.doi.org/10.1007/s41019-020-00123-3.

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43

MANDAL, RANJU, PARTHA PRATIM ROY, and UMAPADA PAL. "SIGNATURE SEGMENTATION FROM MACHINE PRINTED DOCUMENTS USING CONTEXTUAL INFORMATION." International Journal of Pattern Recognition and Artificial Intelligence 26, no. 07 (November 2012): 1253003. http://dx.doi.org/10.1142/s0218001412530035.

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Automatic signature segmentation from a printed document is a challenging task due to the nature of handwriting of the signatory, overlapping/touching of signature strokes with printed text, graphics, noise, etc. In this paper, we propose a two-stage approach for signature segmentation from a document page. In the first stage, a document is segmented into blocks and then blocks are classified into two classes: signature block and printed word block. Gradient-based features are used for block feature extraction and support vector machine classifier is used for block-wise classification. In the second stage, printed characters that may be present in isolated form or overlapped/touched with signature part are removed from signature blocks. From each of the detected signature blocks, the isolated printed characters (if exist) are removed using context information. To detect overlapping/touching printed stroke in a signature block, at first some hypothetical zones are detected where possible overlapping/touching may occur. Bounding box information of neighboring printed word block and local linearity of character strings near the signature blocks are used to detect hypothetical zones. Next, to detect the overlapping/touching printed strokes in hypothetical zones of a signature block, the corner points of contours obtained by Douglas and Peucker polygonal approximation algorithm and skeleton junction points are used. Finally, the touching strokes of signature are separated from text characters using the contour smoothness information near skeleton junction points. The experiment is performed in "Tobacco-800" dataset [The legacy tobacco document library (ltdl), available at http://legacy.library.ucsf.edu/ , University of California, San Francisco, 2007.] and the results obtained from the experiment are promising.
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44

BAG, SOUMEN, and GAURAV HARIT. "SKELETONIZING CHARACTER IMAGES USING A MODIFIED MEDIAL AXIS-BASED STRATEGY." International Journal of Pattern Recognition and Artificial Intelligence 25, no. 07 (November 2011): 1035–54. http://dx.doi.org/10.1142/s0218001411009020.

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In this paper we propose a thinning methodology applicable to character images. It is novel in terms of its ability to adapt to local character shape while constructing the thinned skeleton. Our method does not produce many of the distortions in the character shapes which normally result from the use of existing thinning algorithms. The proposed thinning methodology is based on the medial axis of the character. The skeleton has a width of one pixel. As a by-product of our thinning approach, the skeleton also gets segmented into strokes in vector form. Hence further stroke segmentation is not required. We have conducted experiments with printed and handwritten characters in several scripts such as English, Bengali, Hindi, Kannada and Tamil. We obtain less spurious branches compared to other thinning methods. Our method does not use any kind of post processing.
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45

Kim, Woong, Takaaki Matsui, Masataka Yamao, Makoto Ishibashi, Kota Tamada, Toru Takumi, Kenji Kohno, et al. "The period of the somite segmentation clock is sensitive to Notch activity." Molecular Biology of the Cell 22, no. 18 (September 15, 2011): 3541–49. http://dx.doi.org/10.1091/mbc.e11-02-0139.

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The number of vertebrae is defined strictly for a given species and depends on the number of somites, which are the earliest metameric structures that form in development. Somites are formed by sequential segmentation. The periodicity of somite segmentation is orchestrated by the synchronous oscillation of gene expression in the presomitic mesoderm (PSM), termed the “somite segmentation clock,” in which Notch signaling plays a crucial role. Here we show that the clock period is sensitive to Notch activity, which is fine-tuned by its feedback regulator, Notch-regulated ankyrin repeat protein (Nrarp), and that Nrarp is essential for forming the proper number and morphology of axial skeleton components. Null-mutant mice for Nrarp have fewer vertebrae and have defective morphologies. Notch activity is enhanced in the PSM of the Nrarp−/– embryo, where the ∼2-h segmentation period is extended by 5 min, thereby forming fewer somites and their resultant vertebrae. Reduced Notch activity partially rescues the Nrarp−/– phenotype in the number of somites, but not in morphology. Therefore we propose that the period of the somite segmentation clock is sensitive to Notch activity and that Nrarp plays essential roles in the morphology of vertebrae and ribs.
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46

WANG Wei-xing, 王卫星, 田利平 TIAN Li-ping, and 王悦 WANG Yue. "Segmentation of cell images based on improved graph MST and skeleton distance mapping." Optics and Precision Engineering 21, no. 9 (2013): 2464–71. http://dx.doi.org/10.3788/ope.20132109.2464.

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47

Huang, Guoheng, and Chi-Man Pun. "On-line video multi-object segmentation based on skeleton model and occlusion detection." Multimedia Tools and Applications 77, no. 23 (June 5, 2018): 31313–29. http://dx.doi.org/10.1007/s11042-018-6208-x.

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48

Bieth, Marie, Loic Peter, Stephan G. Nekolla, Matthias Eiber, Georg Langs, Markus Schwaiger, and Bjoern Menze. "Segmentation of Skeleton and Organs in Whole-Body CT Images via Iterative Trilateration." IEEE Transactions on Medical Imaging 36, no. 11 (November 2017): 2276–86. http://dx.doi.org/10.1109/tmi.2017.2720261.

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49

吕, 众鑫. "Particle Feature Recognition and Segmentation Method Based on Skeleton Local Curvature Watershed Algorithm." Computer Science and Application 11, no. 09 (2021): 2252–59. http://dx.doi.org/10.12677/csa.2021.119230.

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50

LI, YANLI, ZHONG ZHOU, and WEI WU. "AUTOMATIC PEDESTRIAN SEGMENTATION COMBINING SHAPE, PUZZLE AND APPEARANCE." International Journal on Artificial Intelligence Tools 22, no. 05 (October 2013): 1360004. http://dx.doi.org/10.1142/s021821301360004x.

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In this paper, we address the problem of automatically segmenting non-rigid pedestrians in still images. Since this task is well known difficult for any type of model or cue alone, a novel approach utilizing shape, puzzle and appearance cues is presented. The major contribution of this approach lies in the combination of multiple cues to refine pedestrian segmentation successively, which has two characterizations: (1) a shape guided puzzle integration scheme, which extracts pedestrians via assembling puzzles with constraint of a shape template; (2) a pedestrian refinement scheme, which is fulfilled by optimizing an automatically generated trimap that encodes both human silhouette and skeleton. Qualitative and quantitative evaluations on several public datasets verify the approach's effectiveness to various articulated bodies, human appearance and partial occlusion, and that this approach is able to segment pedestrians more accurately than methods based only on appearance or shape cue.
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