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Journal articles on the topic 'Skeleton segmentation'

Author: Grafiati

Published: 25 June 2021

Last updated: 29 July 2025

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1

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 (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 regio

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Tian, Haitao, and Pierre Payeur. "Stitch, Contrast, and Segment: Learning a Human Action Segmentation Model Using Trimmed Skeleton Videos." Proceedings of the AAAI Conference on Artificial Intelligence 39, no. 7 (2025): 7365–73. https://doi.org/10.1609/aaai.v39i7.32792.

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Existing skeleton-based human action classification models rely on well-trimmed action-specific skeleton videos for both training and testing, precluding their scalability to real-world applications where untrimmed videos exhibiting concatenated actions are predominant. To overcome this limitation, recently introduced skeleton action segmentation models involve un-trimmed skeleton videos into end-to-end training. The model is optimized to provide frame-wise predictions for any length of testing videos, simultaneously realizing action localization and classification. Yet, achieving such an impr

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Li, Xiaofeng, Yuxin Guo, Han Yang, Qixiang Ye, and Limin Jia. "DWPIS: Dynamic-Weight Parallel Instance and Skeleton Network for Railway Centerline Detection." Applied Sciences 13, no. 10 (2023): 6133. http://dx.doi.org/10.3390/app13106133.

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The primary premise of autonomous railway inspection using unmanned aerial vehicles is achieving autonomous flight along the railway. In our previous work, fitted centerline-based unmanned aerial vehicle (UAV) navigation is proven to be an effective method to guide UAV autonomous flying. However, the empirical parameters utilized in the fitting procedure lacked a theoretical basis and the fitted curves were also not coherent nor smooth. To address these problems, this paper proposes a skeleton detection method, called the dynamic-weight parallel instance and skeleton network, to directly extra

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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 (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 t

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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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Zhao, Mingyue, Han Li, Di Zhang, et al. "Skeleton2Mask: Skeleton-supervised airway segmentation." Medical Image Analysis 105 (October 2025): 103693. https://doi.org/10.1016/j.media.2025.103693.

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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 r

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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 s

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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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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 (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 th

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Kontges, G., and A. Lumsden. "Rhombencephalic neural crest segmentation is preserved throughout craniofacial ontogeny." Development 122, no. 10 (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

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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 (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

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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 (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 pro

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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 (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 irre

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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 (2010): 719. http://dx.doi.org/10.1167/8.6.719.

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Shimizu, Akinobu, Hayato Wakabayashi, Takumi Kanamori, et al. "Automated measurement of bone scan index from a whole-body bone scintigram." International Journal of Computer Assisted Radiology and Surgery 15, no. 3 (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 furt

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Yu, Po-Nien, Yung-Chi Lai, Yi-You Chen, and Da-Chuan Cheng. "Skeleton Segmentation on Bone Scintigraphy for BSI Computation." Diagnostics 13, no. 13 (2023): 2302. http://dx.doi.org/10.3390/diagnostics13132302.

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Bone Scan Index (BSI) is an image biomarker for quantifying bone metastasis of cancers. To compute BSI, not only the hotspots (metastasis) but also the bones have to be segmented. Most related research focus on binary classification in bone scintigraphy: having metastasis or none. Rare studies focus on pixel-wise segmentation. This study compares three advanced convolutional neural network (CNN) based models to explore bone segmentation on a dataset in-house. The best model is Mask R-CNN, which reaches the precision, sensitivity, and F1-score: 0.93, 0.87, 0.90 for prostate cancer patients and

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Hossen, Md Amran, Abdul Ghani Naim, and Pg Emeroylariffion Abas. "Deep Learning for Skeleton-Based Human Activity Segmentation: An Autoencoder Approach." Technologies 12, no. 7 (2024): 96. http://dx.doi.org/10.3390/technologies12070096.

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Automatic segmentation is essential for enhancing human activity recognition, especially given the limitations of publicly available datasets that often lack diversity in daily activities. This study introduces a novel segmentation method that utilizes skeleton data for a more accurate and efficient analysis of human actions. By employing an autoencoder, this method extracts representative features and reconstructs the dataset, using the discrepancies between the original and reconstructed data to establish a segmentation threshold. This innovative approach allows for the automatic segmentatio

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Lux, Jérôme. "AUTOMATIC SEGMENTATION AND STRUCTURAL CHARACTERIZATION OF LOW DENSITY FIBREBOARDS." Image Analysis & Stereology 32, no. 1 (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

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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 (2005): 121–27. http://dx.doi.org/10.1080/15227950500257333.

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Wang, Yaxin, Qi Liu, Jie Yang, et al. "A Method for Tomato Plant Stem and Leaf Segmentation and Phenotypic Extraction Based on Skeleton Extraction and Supervoxel Clustering." Agronomy 14, no. 1 (2024): 198. http://dx.doi.org/10.3390/agronomy14010198.

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To address the current problem of the difficulty of extracting the phenotypic parameters of tomato plants in a non-destructive and accurate way, we proposed a method of stem and leaf segmentation and phenotypic extraction of tomato plants based on skeleton extraction and supervoxel clustering. To carry out growth and cultivation experiments on tomato plants in a solar greenhouse, we obtained multi-view image sequences of the tomato plants to construct three-dimensional models of the plant. We used Laplace’s skeleton extraction algorithm to extract the skeleton of the point cloud after removing

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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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Liu, Xinpeng, Kanyu Xu, Risa Shinoda, Hiroaki Santo, and Fumio Okura. "Masks-to-Skeleton: Multi-View Mask-Based Tree Skeleton Extraction with 3D Gaussian Splatting." Sensors 25, no. 14 (2025): 4354. https://doi.org/10.3390/s25144354.

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Accurately reconstructing tree skeletons from multi-view images is challenging. While most existing works use skeletonization from 3D point clouds, thin branches with low-texture contrast often involve multi-view stereo (MVS) to produce noisy and fragmented point clouds, which break branch connectivity. Leveraging the recent development in accurate mask extraction from images, we introduce a mask-guided graph optimization framework that estimates a 3D skeleton directly from multi-view segmentation masks, bypassing the reliance on point cloud quality. In our method, a skeleton is modeled as a g

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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 (2011): 215–40. http://dx.doi.org/10.1007/s11263-010-0412-0.

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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 (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,

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Li, Shuofeng, Bing Li, Jin Li, and Bin Liu. "Brown Rice Germ Integrity Identification Based on Deep Learning Network." Journal of Food Quality 2022 (March 27, 2022): 1–18. http://dx.doi.org/10.1155/2022/6709787.

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For the quality inspection of brown rice, the segmentation of connected brown rice and the identification of germ integrity are very important. However, there is no better traditional algorithm to achieve better segmentation and recognition results. This paper improves the brown rice (BR) segmentation algorithm based on background skeleton. The candidate matching points are obtained by the background skeleton method, and the optimal matching points are found by the ant colony algorithm. Experimental results show that the proposed segmentation algorithm achieves 96% accuracy, indicating that it

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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 (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. T

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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 (2016): 782–91. http://dx.doi.org/10.5909/jbe.2016.21.5.782.

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

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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 (2009): 431–56. http://dx.doi.org/10.1146/annurev.cellbio.042308.113423.

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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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Zhang, Yujie, and Haibin Cai. "Sequence Segmentation Attention Network for Skeleton-Based Action Recognition." Electronics 12, no. 7 (2023): 1549. http://dx.doi.org/10.3390/electronics12071549.

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With skeleton-based action recognition, it is crucial to recognize the dependencies among joints. However, the current methods are not able to capture the relativity of the various joints among the frames, which is extremely helpful because various parts of the body are moving at the same time. In order to solve this problem, a new sequence segmentation attention network (SSAN) is presented. The successive frames are encoded in each of the segments that make up the skeleton sequence. Then, we provide a self-attention block that may record the associated information among various joints in succ

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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 (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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Scucchia, Federica, Katrein Sauer, Paul Zaslansky, and Tali Mass. "Artificial Intelligence as a Tool to Study the 3D Skeletal Architecture in Newly Settled Coral Recruits: Insights into the Effects of Ocean Acidification on Coral Biomineralization." Journal of Marine Science and Engineering 10, no. 3 (2022): 391. http://dx.doi.org/10.3390/jmse10030391.

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Understanding the formation of the coral skeleton has been a common subject uniting various marine and materials study fields. Two main regions dominate coral skeleton growth: Rapid Accretion Deposits (RADs) and Thickening Deposits (TDs). These have been extensively characterized at the 2D level, but their 3D characteristics are still poorly described. Here, we present an innovative approach to combine synchrotron phase contrast-enhanced microCT (PCE-CT) with artificial intelligence (AI) to explore the 3D architecture of RADs and TDs within the coral skeleton. As a reference study system, we u

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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-join

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Kubicek, Jan, Alice Varysova, Martin Cerny, et al. "Performance and Robustness of Regional Image Segmentation Driven by Selected Evolutionary and Genetic Algorithms: Study on MR Articular Cartilage Images." Sensors 22, no. 17 (2022): 6335. http://dx.doi.org/10.3390/s22176335.

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The analysis and segmentation of articular cartilage magnetic resonance (MR) images belongs to one of the most commonly routine tasks in diagnostics of the musculoskeletal system of the knee area. Conventional regional segmentation methods, which are based either on the histogram partitioning (e.g., Otsu method) or clustering methods (e.g., K-means), have been frequently used for the task of regional segmentation. Such methods are well known as fast and well working in the environment, where cartilage image features are reliably recognizable. The well-known fact is that the performance of thes

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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

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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 (2010): 590–604. http://dx.doi.org/10.1016/j.imavis.2009.09.013.

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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 (2012): 947–53. http://dx.doi.org/10.1097/mnm.0b013e3283567407.

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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 (2010): 293–302. http://dx.doi.org/10.1134/s1054661810030053.

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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 (2012): e48976. http://dx.doi.org/10.1371/journal.pone.0048976.

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Mata, Nitinan, and Sakchai Tangwannawit. "Kinematic Skeleton Extraction from 3D Model Based on Hierarchical Segmentation." Symmetry 17, no. 6 (2025): 879. https://doi.org/10.3390/sym17060879.

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A new approach for skeleton extraction has been designed to work directly with 3D point cloud data. It blends hierarchical segmentation with a multi-scale ensemble built on top of modified PointNet models. Outputs from three network variants trained at different spatial resolutions are aggregated using majority voting, unweighted averaging, and adaptive weighting, with the latter yielding the best performance. Each joint is set at the center of its part. A radius-based filter is used to remove any outliers, specifically, points that fall too far from where the joints are expected to be. When e

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Rougé, Pierre, Nicolas Passat, and Odyssée Merveille. "Topology aware multitask cascaded U-Net for cerebrovascular segmentation." PLOS ONE 19, no. 12 (2024): e0311439. https://doi.org/10.1371/journal.pone.0311439.

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Cerebrovascular segmentation is a crucial preliminary task for many computer-aided diagnosis tools dealing with cerebrovascular pathologies. Over the last years, deep learning based methods have been widely applied to this task. However, classic deep learning approaches struggle to capture the complex geometry and specific topology of cerebrovascular networks, which is of the utmost importance in many applications. To overcome these limitations, the clDice loss, a topological loss that focuses on the vessel centerlines, has been recently proposed. This loss requires computing the skeletons of

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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 a

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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 (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

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Abushehab, Abdallah, Jess D. Rames, Sara M. Hussein, et al. "Midface Skeletal Sexual Dimorphism: Lessons Learned from Advanced Three-dimensional Imaging in the White Population." Plastic and Reconstructive Surgery - Global Open 12, no. 10 (2024): e6215. http://dx.doi.org/10.1097/gox.0000000000006215.

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Background: Facial shape is significantly influenced by the underlying facial bony skeleton. Sexual dimorphisms in these structures are crucial for craniofacial, aesthetic, and gender-affirming surgery. Previous studies have examined the orbits and upper face, but less is known about the midface. This study aimed to elucidate the sexual dimorphism in the midface region, focusing on the maxilla and zygomatic bones. Methods: A retrospective review was conducted using facial computed tomography scans from 101 White patients aged 20–79 years, using Materialise Mimics and 3-Matics for segmentation

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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 (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

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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 (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 accura

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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 (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. T

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