Relevant bibliographies by topics / Human body skeleton detection

Contents

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

Academic literature on the topic 'Human body skeleton detection'

Author: Grafiati
Published: 4 June 2021
Last updated: 26 July 2025

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Journal articles on the topic "Human body skeleton detection"

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Rosdiyana, Samad, Wen Yan Law, Mustafa Mahfuzah, Rul Hasma Abdullah Nor, and Pebrianti Dwi. "Multiple Human Body Postures Detection using Kinect." Indonesian Journal of Electrical Engineering and Computer Science 10, no. 2 (2018): 528–36. https://doi.org/10.11591/ijeecs.v10.i2.pp528-536.

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This paper presents a method to detect multiple human body postures using Kinect sensor. In this study, a combination of shape features and body joint points are used as input features. The Kinect sensor which used infrared camera to produce a depth image is suitable to be used in an environment that has varying lighting conditions. The method for human detection is done by processing the depth image and joint data (skeleton) which able to overcome several problems such as cluttered background, various articulated poses, and change in color and illumination. Then, the body joint coordinates fo
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Zhang, Heng, and Fa Wang. "Research on Human Action Detection and Recognition Methods Based on Interpretable Artificial Intelligence." Journal of Combinatorial Mathematics and Combinatorial Computing 127a (April 15, 2025): 1143–58. https://doi.org/10.61091/jcmcc127a-066.

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Deep learning-based methods can be combined with skeleton data, but they only consider the feature vectors formed by joint coordinates and do not extract the spatio-temporal dependencies between skeletons. In order to provide a more comprehensive detection and recognition of spatio-temporal relationships in human action sequences, this paper proposes a graph neural network-based human action detection and recognition method by combining YOLOv5, AlphaPose, and spatio-temporal graph convolutional network (ST-GCN) algorithms under the interpretable artificial intelligence (XAI) perspective. First
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Tus Sadia, Halima, Lutfur Nahar, Israt Jahan, Md Khaliluzzaman, Md Rashedul Islam, and Md Jiabul Hoque. "Skeleton and Joint Angle Estimation Based on MobileNet." International Journal of Advanced Networking and Applications 14, no. 06 (2023): 5727–33. http://dx.doi.org/10.35444/ijana.2023.14610.

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2D pose estimation is a general problem in computer vision, where the main objective is to detect a person’s body key-points and estimate a 2D skeletonized pose of a person.Skeleton estimation is outbound as an essential part of body parts detection in many fields, such as healthcare, rehabilitation, sports and fitness, animation, gaming, augmented reality, robotics. These systems are based on neural network applications and able to give reliable, objective and cost-effective benefits. Various methods are available based on this topic and used to update existing systems. In this regard, in thi
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Abduljabbar Ali, Mohammed, Abir Jaafar Hussain, and Ahmed T. Sadiq. "Human Fall Down Recognition Using Coordinates Key Points Skeleton." International Journal of Online and Biomedical Engineering (iJOE) 18, no. 02 (2022): 88–104. http://dx.doi.org/10.3991/ijoe.v18i02.28017.

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Falls pose a substantial threat to human safety and can quickly result in disastrous repercussions. This threat is particularly true for the elderly, where falls are the leading cause of hospitalization and injury-related death. A fall that is detected and responded to quickly has a lower danger and long-term impact. Many real-time fall detection solutions are available; however, these solutions have specific privacy, maintenance, and proper use issues. Vision-based fall event detection has the benefit of being completely private and straightforward to use and maintain. However, in real-world
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Seredin, O. S., A. V. Kopylov, and E. E. Surkov. "The study of skeleton description reduction in the human fall-detection task." Computer Optics 44, no. 6 (2020): 951–58. http://dx.doi.org/10.18287/2412-6179-co-753.

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Accurate and reliable real-time fall detection is a key aspect of any intelligent elderly people care system. A lot of modern RGB-D cameras can provide a skeleton description of a human figure as a compact pose presentation. This makes it possible to use this description for further analysis without access to real video and, thus, to increase the privacy of the whole system. The skeleton description reduction based on the anthropometrical characteristics of a human body is proposed. The experimental study on the TST Fall Detection dataset v2 by the Leave-One-Person-Out method shows that the pr
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Chen, Weiming, Zijie Jiang, Hailin Guo, and Xiaoyang Ni. "Fall Detection Based on Key Points of Human-Skeleton Using OpenPose." Symmetry 12, no. 5 (2020): 744. http://dx.doi.org/10.3390/sym12050744.

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According to statistics, falls are the primary cause of injury or death for the elderly over 65 years old. About 30% of the elderly over 65 years old fall every year. Along with the increase in the elderly fall accidents each year, it is urgent to find a fast and effective fall detection method to help the elderly fall.The reason for falling is that the center of gravity of the human body is not stable or symmetry breaking, and the body cannot keep balance. To solve the above problem, in this paper, we propose an approach for reorganization of accidental falls based on the symmetry principle.
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Samad, Rosdiyana, Law Wen Yan, Mahfuzah Mustafa, Nor Rul Hasma Abdullah, and Dwi Pebrianti. "Multiple Human Body Postures Detection using Kinect." Indonesian Journal of Electrical Engineering and Computer Science 10, no. 2 (2018): 528. http://dx.doi.org/10.11591/ijeecs.v10.i2.pp528-536.

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<span lang="EN-US">This paper presents a method to detect multiple human body postures using Kinect sensor. In this study, a combination of shape features and body joint points are used as input features. The Kinect sensor which used infrared camera to produce a depth image is suitable to be used in an environment that has varying lighting conditions. The method for human detection is done by processing the depth image and joint data (skeleton) which able to overcome several problems such as cluttered background, various articulated poses, and change in color and illumination. Then, the
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Ramirez, Heilym, Sergio A. Velastin, Paulo Aguayo, Ernesto Fabregas, and Gonzalo Farias. "Human Activity Recognition by Sequences of Skeleton Features." Sensors 22, no. 11 (2022): 3991. http://dx.doi.org/10.3390/s22113991.

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In recent years, much effort has been devoted to the development of applications capable of detecting different types of human activity. In this field, fall detection is particularly relevant, especially for the elderly. On the one hand, some applications use wearable sensors that are integrated into cell phones, necklaces or smart bracelets to detect sudden movements of the person wearing the device. The main drawback of these types of systems is that these devices must be placed on a person’s body. This is a major drawback because they can be uncomfortable, in addition to the fact that these
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Li, Ruotong, Weixin Si, Michael Weinmann, and Reinhard Klein. "Constraint-Based Optimized Human Skeleton Extraction from Single-Depth Camera." Sensors 19, no. 11 (2019): 2604. http://dx.doi.org/10.3390/s19112604.

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As a cutting-edge research topic in computer vision and graphics for decades, human skeleton extraction from single-depth camera remains challenging due to possibly occurring occlusions of different body parts, huge appearance variations, and sensor noise. In this paper, we propose to incorporate human skeleton length conservation and symmetry priors as well as temporal constraints to enhance the consistency and continuity for the estimated skeleton of a moving human body. Given an initial estimation of the skeleton joint positions provided per frame by the Kinect SDK or Nuitrack SDK, which do
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Li, Zhi. "Three-Dimensional Diffusion Model in Sports Dance Video Human Skeleton Detection and Extraction." Advances in Mathematical Physics 2021 (September 7, 2021): 1–11. http://dx.doi.org/10.1155/2021/3772358.

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The research in this paper mainly includes as follows: for the principle of action recognition based on the 3D diffusion model convolutional neural network, the whole detection process is carried out from fine to coarse using a bottom-up approach; for the human skeleton detection accuracy, a multibranch multistage cascaded CNN structure is proposed, and this network structure enables the model to learn the relationship between the joints of the human body from the original image and effectively predict the occluded parts, allowing simultaneous prediction of skeleton point positions and skeleto
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Dissertations / Theses on the topic "Human body skeleton detection"

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Smith, Patricia R. "The detection of haemoglobin in ancient human skeleton remains." Thesis, University of Essex, 1989. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.235815.

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Feng, Weinan. "Multiple Human Body Detection in Crowds." Thesis, Högskolan i Gävle, Avdelningen för Industriell utveckling, IT och Samhällsbyggnad, 2012. http://urn.kb.se/resolve?urn=urn:nbn:se:hig:diva-12352.

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The objective of this project is to use digital imaging devices to monitor a delineated area of the public space and to register statistics about people moving across this area. A feasible detecting approach, which is based on background subtraction, has been developed and has been tested on 39 images. Individual pedestrians in images can be detected and counted. The approach is suitably used to detect and count pedestrians without overlapping. Accuracy rate of detection is higher than 80%.
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Topcu, Hasan Huseyin. "Human Body Part Detection And Multi-human Tracking Insurveillance Videos." Master's thesis, METU, 2012. http://etd.lib.metu.edu.tr/upload/12614308/index.pdf.

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With the recent developments in Computer Vision and Pattern Recognition, surveillance applications are equipped with the capabilities of event/activity understanding and interpretation which usually require recognizing humans in real world scenes. Real world scenes such as airports, streets and train stations are complex because they involve many people, complicated occlusions and cluttered backgrounds. Although complex real world scenes exist, human detectors have the capability to locate pedestrians accurately even in complex scenes and visual trackers have the capability to track targets in
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Azhar, Faisal. "Marker-less human body part detection, labelling and tracking for human activity recognition." Thesis, University of Warwick, 2015. http://wrap.warwick.ac.uk/69575/.

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This thesis focuses on the development of a real-time and cost effective marker-less computer vision method for significant body point or part detection (i.e., the head, arm, shoulder, knee, and feet), labelling and tracking, and its application to activity recognition. This work comprises of three parts: significantbody point detection and labelling, significant body point tracking, and activity recognition. Implicit body models are proposed based on human anthropometry, kinesiology, and human vision inspired criteria to detect and label significant body points. The key idea of the proposed me
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Abedan, Kondori Farid. "Bring Your Body into Action : Body Gesture Detection, Tracking, and Analysis for Natural Interaction." Doctoral thesis, Umeå universitet, Institutionen för tillämpad fysik och elektronik, 2014. http://urn.kb.se/resolve?urn=urn:nbn:se:umu:diva-88508.

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Due to the large influx of computers in our daily lives, human-computer interaction has become crucially important. For a long time, focusing on what users need has been critical for designing interaction methods. However, new perspective tends to extend this attitude to encompass how human desires, interests, and ambitions can be met and supported. This implies that the way we interact with computers should be revisited. Centralizing human values rather than user needs is of the utmost importance for providing new interaction techniques. These values drive our decisions and actions, and are e
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Smith, Jason Alan. "Naturalistic skeletal gesture movement and rendered gesture decoding." Diss., Online access via UMI:, 2006.

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Zhan, Wenjie, and Maowei Zheng. "From Body Parts Responses to Underwater Human Detection: A Deep Learning Approach." Thesis, Blekinge Tekniska Högskola, Institutionen för datavetenskap, 2020. http://urn.kb.se/resolve?urn=urn:nbn:se:bth-20099.

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Context. Underwater human detection has been an important problem in computer vision areas. Body part-based models could gain good performance in on-land human detection with occlusion existing scenarios. This thesis explores the feasibility of human body parts detection in underwater environment. Objectives. This thesis aims to build a DNN-based underwater human body part detector for human body part detection task. Three body part detectors implemented with different DNN-based models (Faster R-CNN, SSD and YOLO) are built and compared over underwater human body part detection task. Methods.
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Fallah, Haghmohammadi Hamidreza. "Fever Detection for Dynamic Human Environment Using Sensor Fusion." Thesis, Université d'Ottawa / University of Ottawa, 2018. http://hdl.handle.net/10393/37332.

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The objective of this thesis is to present an algorithm for processing infrared images and accomplishing automatic detection and path tracking of moving subjects with fever. The detection is based on two main features: the distinction between the geometry of a human face and other objects in the field of view of the camera and the temperature of the radiating object. These features are used for tracking the identified person with fever. The position of camera with respect to direction of motion the walkers appeared to be critical in this process. Infrared thermography is a remote sensing techn
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Liu, X. (Xin). "Human motion detection and gesture recognition using computer vision methods." Doctoral thesis, Oulun yliopisto, 2019. http://urn.fi/urn:isbn:9789526222011.

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Abstract Gestures are present in most daily human activities and automatic gestures analysis is a significant topic with the goal of enabling the interaction between humans and computers as natural as the communication between humans. From a computer vision perspective, a gesture analysis system is typically composed of two stages, the low-level stage for human motion detection and the high-level stage for understanding human gestures. Therefore, this thesis contributes to the research on gesture analysis from two aspects, 1) Detection: human motion segmentation from video sequences, and 2) Un
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Levinrad, Ester. "“The weight of my skeleton is my only honesty” : language and the speaking body in Marlene van Niekerk’s Agaat." Thesis, Stellenbosch : University of Stellenbosch, 2010. http://hdl.handle.net/10019.1/4369.

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Thesis (MA (English))--University of Stellenbosch, 2010.<br>ENGLISH ABSTRACT: This thesis proposes a detailed study of the novel Agaat by South African author Marlene van Niekerk (first published 2004). A particular focus throughout is on constructions of identity and subjectivity, and the novel is considered as writing within and against both the Realist tradition as well as the South African genre of the plaasroman and/or farm novel. The translation of the novel into English by Michiel Heyns (published 2006) is used as primary text, which furthermore raises questions of language and int
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Books on the topic "Human body skeleton detection"

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Bass, William M. Beyond the Body Farm: A Legendary Bone Detective Explores Murders, Mysteries, and the Revolution in Forensic Science. HarperLuxe, 2007.

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Jon, Jefferson, ed. Beyond the Body Farm: A Legendary Bone Detective Explores Murders, Mysteries, and the Revolution in Forensic Science. William Morrow, 2007.

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Anderson, Karen C. The bones & skeleton gamebook. Somerville House Publishing, 1993.

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Rolfe, Sophie, and Robin Anderson. Body detectives. Films for the Humanities & Sciences, 2004.

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Yancey, Diane. Body farms. Lucent Books, 2009.

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Nagel, Rob. Body by design: From the digestive system to the skeleton. UXL, 2000.

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Nagel, Rob. Body by design: From the digestive system to the skeleton. Edited by Des Chenes Betz. UXL, 2000.

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Cumbaa, Stephen L. The bones book. Workman Pub., 1991.

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Masayuki, Sebe, and Fuyuno Ichiko, eds. Hone wa dōshite katai no? Kin no Hoshi Sha, 1994.

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ill, Theinhardt Volker, ed. How my body moves. Viking Kestrel, 1986.

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Book chapters on the topic "Human body skeleton detection"

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Gnecco, Giorgio, Martina Fausto, Gabriele Romano, Gualtiero Volpe, and Antonio Camurri. "Improving Output Visualization of an Algorithm for the Automated Detection of the Perceived Origin of Movement." In Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering. Springer Nature Switzerland, 2024. http://dx.doi.org/10.1007/978-3-031-55722-4_8.

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AbstractThe perceived Origin of full-body human Movement (OoM), i.e., the part of the body that is perceived by an external observer as the joint from which movement originates, represents a relevant topic for movement analysis. Indeed, its automated detection is important to contribute to the automated analysis of full-body emotions and of non-verbal social signals, and has potential applications, among others, in dance and music teaching, cognitive and motor rehabilitation, sport, and entertainment. In this work, we further develop a recently proposed algorithm for the automated detection of
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Xu, Tao, and Yun Zhou. "Fall Detection Based on Skeleton Data." In Human Aspects of IT for the Aged Population. Applications, Services and Contexts. Springer International Publishing, 2017. http://dx.doi.org/10.1007/978-3-319-58536-9_38.

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Zhu, Xiaolong, Shihong Xia, Yong Yu, and Tianlu Mao. "A Novel Method for Cloth-Body Collision Detection." In Digital Human Modeling. Springer Berlin Heidelberg, 2007. http://dx.doi.org/10.1007/978-3-540-73321-8_118.

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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. Springer Berlin Heidelberg, 2009. http://dx.doi.org/10.1007/978-3-642-01811-4_4.

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Dufour, Rémi, Cyril Meurie, Olivier Lézoray, and Ankur Mahtani. "Space-Time Memory Networks for Multi-person Skeleton Body Part Detection." In Pattern Recognition and Artificial Intelligence. Springer International Publishing, 2022. http://dx.doi.org/10.1007/978-3-031-09282-4_7.

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Kehayias, Joseph J., and Hong Zhuang. "Measurement of Regional Body Fat in Vivo in Humans by Simultaneous Detection of Regional Carbon and Oxygen, Using Neutron Inelastic Scattering at Low Radiation Exposure." In Human Body Composition. Springer US, 1993. http://dx.doi.org/10.1007/978-1-4899-1268-8_9.

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Halder, Kumar Saikat, Ashwani Singla, and Ranjit Singh. "Novel Algorithm on Human Body Fall Detection." In Learning and Analytics in Intelligent Systems. Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-030-24322-7_28.

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McDermott, Barry, Eoghan Dunne, Martin O’Halloran, Emily Porter, and Adam Santorelli. "Brain Haemorrhage Detection Through SVM Classification of Electrical Impedance Tomography Measurements." In Brain and Human Body Modeling. Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-030-21293-3_12.

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Zhang, Chengyi, Hao Yan, Qiang Liu, Kun Yang, and Lin Lin. "Signal Transmission Through Human Body via Human Oxygen Saturation Detection." In Bio-inspired Information and Communications Technologies. Springer Nature Switzerland, 2023. http://dx.doi.org/10.1007/978-3-031-43135-7_18.

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Bian, Ziyang, Tingfa Xu, Chang Su, and Xuan Luo. "Human Abnormal Behavior Detection Based on RGBD Video’s Skeleton Information Entropy." In Proceedings of the 2015 International Conference on Communications, Signal Processing, and Systems. Springer Berlin Heidelberg, 2016. http://dx.doi.org/10.1007/978-3-662-49831-6_74.

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Conference papers on the topic "Human body skeleton detection"

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Chen, Lin, and Zhixiang Zhu. "Human Skeleton Point Detection Based on Super Resolution." In 2024 43rd Chinese Control Conference (CCC). IEEE, 2024. http://dx.doi.org/10.23919/ccc63176.2024.10661439.

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Qi, Yan, and Chaohui Yan. "A Smoking Behavior Detection Algorithm Based on YOLOv5 and Key Points of Human Skeleton." In 2024 2nd International Conference on Signal Processing and Intelligent Computing (SPIC). IEEE, 2024. http://dx.doi.org/10.1109/spic62469.2024.10691603.

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Chung, Ming-An, Jun-Hao Zhang, Ming-Chun Hsieh, et al. "Millimeter-Wave Beamforming System Assists in Human Body Moisture Detection." In 2025 IEEE MTT-S International Microwave Biomedical Conference (IMBioC). IEEE, 2025. https://doi.org/10.1109/imbioc63524.2025.10989730.

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Ren, Hailin, Anil Kumar, Xinran Wang, and Pinhas Ben-Tzvi. "Parallel Deep Learning Ensembles for Human Pose Estimation." In ASME 2018 Dynamic Systems and Control Conference. American Society of Mechanical Engineers, 2018. http://dx.doi.org/10.1115/dscc2018-9007.

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This paper presents an efficient method to detect human pose with monocular color imagery using a parallel architecture based on deep neural network. The network presented in this approach consists of two sequentially connected stages of 13 parallel CNN ensembles, where each ensemble is trained to detect one specific kind of linkage of the human skeleton structure. After detecting all skeleton linkages, a voting score-based post-processing algorithm assembles the individual linkages to form a complete human structure. This algorithm exploits human structural heuristics while assembling skeleto
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Behoora, Ishan, and Conrad S. Tucker. "Quantifying Emotional States Based on Body Language Data Using Non Invasive Sensors." In ASME 2014 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference. American Society of Mechanical Engineers, 2014. http://dx.doi.org/10.1115/detc2014-34770.

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Determining participant engagement is an important issue across a large number of fields, ranging from entertainment to education. Traditionally, feedback from participants is taken after the activity has been completed. Alternately, continuous observation by trained humans is needed. Thus, there is a need for an automated real time solution. In this paper, the authors propose a data mining driven approach that models a participant’s engagement, based on body language data acquired in real time using non-invasive sensors. Skeletal position data, that approximates human body motions, is acquire
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Feng, Bingbing, and Yulin Zhao. "Development of Techniques for Measuring Lower Limb Flexibility in the Elderly." In 2025 Intelligent Human Systems Integration. AHFE International, 2025. https://doi.org/10.54941/ahfe1005812.

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Flexibility as one of the influencing factors of physical fitness, is an essential component of overall health and can be regulated through muscle control and joint range of motion.However, the range of motion of many joints tends to decrease with age.The research suggests that, irrespective of gender, shoulder flexibility decreases by approximately 10% per decade from the age of 65. While some individuals maintain their flexibility as they age, their joint function range remains significantly less than that of younger individuals. The decline in joint flexibility directly contributes to reduc
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Mahbub, Fardeen, Rashedul Islam, Shouherdho Banerjee Akash, M. Tanseer Ali, and Saiful Islam. "Design and Implementation of a Microstrip Patch Antenna for the Detection of Cancers and Tumors in Skeletal Muscle of the Human Body Using ISM Band." In 2021 IEEE 12th Annual Information Technology, Electronics and Mobile Communication Conference (IEMCON). IEEE, 2021. http://dx.doi.org/10.1109/iemcon53756.2021.9623236.

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Ding, Jianhao, Yigang Wang, and Lingyun Yu. "Extraction of Human Body Skeleton Based on Silhouette Images." In 2010 Second International Workshop on Education Technology and Computer Science. IEEE, 2010. http://dx.doi.org/10.1109/etcs.2010.241.

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Korumilli, Manasa, Koppula Sai Lasya, Naveen Cheggoju, Vipin Kamble, and Vishal R. Satpute. "Human Fall Detection using Skeleton Features." In 2023 2nd International Conference on Paradigm Shifts in Communications Embedded Systems, Machine Learning and Signal Processing (PCEMS). IEEE, 2023. http://dx.doi.org/10.1109/pcems58491.2023.10136111.

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Ramirez, H., S. A. Velastin, E. Fabregas, I. Meza, D. Makris, and G. Farias. "Fall Detection using Human Skeleton Features." In 11th International Conference of Pattern Recognition Systems (ICPRS 2021). Institution of Engineering and Technology, 2021. http://dx.doi.org/10.1049/icp.2021.1465.

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Reports on the topic "Human body skeleton detection"

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Matsumoto, David, Hyisung C. Hwang, Adam M. Fullenkamp, and C. M. Laurent. Human Deception Detection from Whole Body Motion Analysis. Defense Technical Information Center, 2015. http://dx.doi.org/10.21236/ada626755.

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Malinowski, Owen, Scott Riccardella, and Jason Van Velsor. PR-335-203810-R03 CT Fundamentals with Calibration and Reference Standards for Pipeline Anomaly Detection. Pipeline Research Council International, Inc. (PRCI), 2022. http://dx.doi.org/10.55274/r0012216.

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X-ray Computed Tomography (XRCT) was initially developed and utilized in the medical industry to image the internal structure of the human body. X-ray imaging was conceived and realized at the turn of the 20th century and subsequently, XRCT, was conceived in the middle of the 20th century and its development continues today. Near the end of the 20th century industrial cone beam XRCT for applications such as dimensional metrology branched off, including its use for identifying and dimensioning flaws. XRCT has been utilized successfully for three-dimensional imaging of flaws in the small panel c
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Spiegel, Yitzhak, Michael McClure, Itzhak Kahane, and B. M. Zuckerman. Characterization of the Phytophagous Nematode Surface Coat to Provide New Strategies for Biocontrol. United States Department of Agriculture, 1995. http://dx.doi.org/10.32747/1995.7613015.bard.

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Chemical composition and biological role of the surface coat (SC) of the root-knot nematodes, Meloidogyne spp. are described. SC proteins of M. incognita race 3 infective juveniles (J2) were characterized by electrophoresis and western blotting of extracts from radioiodine and biotin-labelled nematodes. J2 labelled with radioiodine and biotin released 125I and biotin-labelled molecules into water after 20 hours incubation, indicating that SC proteins may be loosely attached to the nematode. Antiserum to the principal protein reacted with the surface of live J2 and with surface proteins previou
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Rankin, Nicole, Deborah McGregor, Candice Donnelly, et al. Lung cancer screening using low-dose computed tomography for high risk populations: Investigating effectiveness and screening program implementation considerations: An Evidence Check rapid review brokered by the Sax Institute (www.saxinstitute.org.au) for the Cancer Institute NSW. The Sax Institute, 2019. http://dx.doi.org/10.57022/clzt5093.

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Background Lung cancer is the number one cause of cancer death worldwide.(1) It is the fifth most commonly diagnosed cancer in Australia (12,741 cases diagnosed in 2018) and the leading cause of cancer death.(2) The number of years of potential life lost to lung cancer in Australia is estimated to be 58,450, similar to that of colorectal and breast cancer combined.(3) While tobacco control strategies are most effective for disease prevention in the general population, early detection via low dose computed tomography (LDCT) screening in high-risk populations is a viable option for detecting asy
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