Artigos de revistas sobre o tema "Ultrasound image segmentation"
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J. Hemalatha, R., Dr V. Vijaybaskar, A. Josephin Arockia Dhivya e . "Early detection of joint abnormalities from ultrasound images". International Journal of Engineering & Technology 7, n.º 2.25 (3 de maio de 2018): 105. http://dx.doi.org/10.14419/ijet.v7i2.25.16569.
Texto completo da fonteKwak, Deawon, Jiwoo Choi e Sungjin Lee. "Rethinking Breast Cancer Diagnosis through Deep Learning Based Image Recognition". Sensors 23, n.º 4 (19 de fevereiro de 2023): 2307. http://dx.doi.org/10.3390/s23042307.
Texto completo da fonteBao, Junxiao, Cuilin Bei, Xiang Zheng e Jinli Wang. "Deep Learning Algorithm in Biomedical Engineering in Intelligent Automatic Processing and Analysis of Sports Images". Wireless Communications and Mobile Computing 2022 (30 de julho de 2022): 1–10. http://dx.doi.org/10.1155/2022/3196491.
Texto completo da fonteSree, S. Jayanthi, e C. Vasanthanayaki. "Ultrasound Fetal Image Segmentation Techniques: A Review". Current Medical Imaging Formerly Current Medical Imaging Reviews 15, n.º 1 (7 de dezembro de 2018): 52–60. http://dx.doi.org/10.2174/1573405613666170622115527.
Texto completo da fonteShao, Liping, Zubang Zhou, Hongmei Wu, Jinrong Ni e Shulan Li. "Modeling of Hidden Markov in Ultrasound Image-Assisted Diagnosis". Journal of Healthcare Engineering 2021 (12 de abril de 2021): 1–10. http://dx.doi.org/10.1155/2021/5597591.
Texto completo da fonteWu, Shibin, Shaode Yu, Ling Zhuang, Xinhua Wei, Mark Sak, Neb Duric, Jiani Hu e Yaoqin Xie. "Automatic Segmentation of Ultrasound Tomography Image". BioMed Research International 2017 (2017): 1–8. http://dx.doi.org/10.1155/2017/2059036.
Texto completo da fonteNoble, J. A., e D. Boukerroui. "Ultrasound image segmentation: a survey". IEEE Transactions on Medical Imaging 25, n.º 8 (agosto de 2006): 987–1010. http://dx.doi.org/10.1109/tmi.2006.877092.
Texto completo da fonteSun, Jingmeng, e Yifei Liu. "Segmentation for Human Motion Injury Ultrasound Medical Images Using Deep Feature Fusion". Mathematical Problems in Engineering 2022 (29 de agosto de 2022): 1–9. http://dx.doi.org/10.1155/2022/4825720.
Texto completo da fonteSuri, Jasjit, Yujun Guo, Cara Coad, Tim Danielson, Idris Elbakri e Roman Janer. "Image Quality Assessment via Segmentation of Breast Lesion in X-ray and Ultrasound Phantom Images from Fischer's Full Field Digital Mammography and Ultrasound (FFDMUS) System". Technology in Cancer Research & Treatment 4, n.º 1 (fevereiro de 2005): 83–92. http://dx.doi.org/10.1177/153303460500400111.
Texto completo da fonteCai, Lina, Qingkai Li, Junhua Zhang, Zhenghua Zhang, Rui Yang e Lun Zhang. "Ultrasound image segmentation based on Transformer and U-Net with joint loss". PeerJ Computer Science 9 (20 de outubro de 2023): e1638. http://dx.doi.org/10.7717/peerj-cs.1638.
Texto completo da fonteOrlando, Nathan, Igor Gyacskov, Derek J. Gillies, Fumin Guo, Cesare Romagnoli, David D’Souza, Derek W. Cool, Douglas A. Hoover e Aaron Fenster. "Effect of dataset size, image quality, and image type on deep learning-based automatic prostate segmentation in 3D ultrasound". Physics in Medicine & Biology 67, n.º 7 (29 de março de 2022): 074002. http://dx.doi.org/10.1088/1361-6560/ac5a93.
Texto completo da fonteSaeed, Jwan N. "A SURVEY OF ULTRASONOGRAPHY BREAST CANCER IMAGE SEGMENTATION TECHNIQUES". Academic Journal of Nawroz University 9, n.º 1 (11 de fevereiro de 2020): 1. http://dx.doi.org/10.25007/ajnu.v9n1a523.
Texto completo da fonteZhang, Yingtao, Min Xian, Heng-Da Cheng, Bryar Shareef, Jianrui Ding, Fei Xu, Kuan Huang, Boyu Zhang, Chunping Ning e Ying Wang. "BUSIS: A Benchmark for Breast Ultrasound Image Segmentation". Healthcare 10, n.º 4 (14 de abril de 2022): 729. http://dx.doi.org/10.3390/healthcare10040729.
Texto completo da fonteDr. M. Renukadevi, S. Suganyadevi,. "SEGMENTATION OF KIDNEY STONE REGION IN ULTRA SOUND IMAGEBY USING REGION PARTITION AND MOUNTING SEGMENTATION ALGORITHM (RPM)". INFORMATION TECHNOLOGY IN INDUSTRY 9, n.º 1 (5 de março de 2021): 512–18. http://dx.doi.org/10.17762/itii.v9i1.164.
Texto completo da fonteKhan, Muhammad Salim, Laiba Saqib, Zahir Shah, Haider Ali e Ahmad Alshehri. "Efficient Echocardiographic Image Segmentation". Mathematical Problems in Engineering 2022 (10 de setembro de 2022): 1–5. http://dx.doi.org/10.1155/2022/1754291.
Texto completo da fonteYang, Jing, Ping Tang, Jie Chen e Huaxiang Shen. "Application and Analysis of Imaging Characteristics of Four-Dimensional Ultrasound in the Diagnosis of Fetal Cleft Lip and Palate". Journal of Medical Imaging and Health Informatics 11, n.º 1 (1 de janeiro de 2021): 133–38. http://dx.doi.org/10.1166/jmihi.2021.3520.
Texto completo da fonteChandra De, Utpal, Madhabananda Das, Debashis Mishra e Debashis Mishra. "Threshold based brain tumor image segmentation". International Journal of Engineering & Technology 7, n.º 3 (22 de agosto de 2018): 1801. http://dx.doi.org/10.14419/ijet.v7i3.12425.
Texto completo da fonteCarriere, Jay, Ron Sloboda, Nawaid Usmani e Mahdi Tavakoli. "Autonomous Prostate Segmentation in 2D B-Mode Ultrasound Images". Applied Sciences 12, n.º 6 (15 de março de 2022): 2994. http://dx.doi.org/10.3390/app12062994.
Texto completo da fonteNoble, J. A. "Ultrasound image segmentation and tissue characterization". Proceedings of the Institution of Mechanical Engineers, Part H: Journal of Engineering in Medicine 224, n.º 2 (17 de agosto de 2009): 307–16. http://dx.doi.org/10.1243/09544119jeim604.
Texto completo da fonteKrivanek, A., e M. Sonka. "Ovarian ultrasound image analysis: follicle segmentation". IEEE Transactions on Medical Imaging 17, n.º 6 (1998): 935–44. http://dx.doi.org/10.1109/42.746626.
Texto completo da fonteArchip, Neculai, Robert Rohling, Peter Cooperberg e Hamid Tahmasebpour. "Ultrasound image segmentation using spectral clustering". Ultrasound in Medicine & Biology 31, n.º 11 (novembro de 2005): 1485–97. http://dx.doi.org/10.1016/j.ultrasmedbio.2005.07.005.
Texto completo da fonteHuang, Qinghua, Yaozhong Luo e Qiangzhi Zhang. "Breast ultrasound image segmentation: a survey". International Journal of Computer Assisted Radiology and Surgery 12, n.º 3 (9 de janeiro de 2017): 493–507. http://dx.doi.org/10.1007/s11548-016-1513-1.
Texto completo da fonteHarkey, Matthew S., Nicholas Michel, Christopher Kuenze, Ryan Fajardo, Matt Salzler, Jeffrey B. Driban e Ilker Hacihaliloglu. "Validating a Semi-Automated Technique for Segmenting Femoral Articular Cartilage on Ultrasound Images". CARTILAGE 13, n.º 2 (abril de 2022): 194760352210930. http://dx.doi.org/10.1177/19476035221093069.
Texto completo da fonteShen, Jiaqi, Fangfang Huang e Myers Ulrich. "Evaluation and Analysis of Cardiovascular Function in Intensive Care Unit Patients by Ultrasound Image Segmentation Based on Deep Learning". Journal of Medical Imaging and Health Informatics 10, n.º 8 (1 de agosto de 2020): 1892–98. http://dx.doi.org/10.1166/jmihi.2020.3119.
Texto completo da fonteMuhammad, Muhammad, Diyar Zeebaree, Adnan Mohsin Abdulazeez Brifcani, Jwan Saeed e Dilovan Asaad Zebari. "A Review on Region of Interest Segmentation Based on Clustering Techniques for Breast Cancer Ultrasound Images". Journal of Applied Science and Technology Trends 1, n.º 3 (24 de junho de 2020): 78–91. http://dx.doi.org/10.38094/2020jastt1328.
Texto completo da fonteMuhammad, Muhammad, Diyar Zeebaree, Adnan Mohsin Abdulazeez Brifcani, Jwan Saeed e Dilovan Asaad Zebari. "Region of Interest Segmentation Based on Clustering Techniques for Breast Cancer Ultrasound Images: A Review". Journal of Applied Science and Technology Trends 1, n.º 3 (24 de junho de 2020): 78–91. http://dx.doi.org/10.38094/jastt20201328.
Texto completo da fonteMuhammad, Muhammad, Diyar Zeebaree, Adnan Mohsin Abdulazeez Brifcani, Jwan Saeed e Dilovan Asaad Zebari. "A Review on Region of Interest Segmentation Based on Clustering Techniques for Breast Cancer Ultrasound Images". Journal of Applied Science and Technology Trends 1, n.º 3 (24 de junho de 2020): 78–91. http://dx.doi.org/10.38094/jastt1328.
Texto completo da fonteJeba Shiney, O., J. Amar Pratap Singh e Priestly Shan B. "EXTRACTION OF FETAL FEATURES FROM B MODE ULTRASONOGRAMS FOR EFFICIENT DIAGNOSIS OF DOWN SYNDROME IN FIRST AND SECOND TRIMESTER". Biomedical & Pharmacology Journal 12, n.º 3 (30 de setembro de 2019): 1135–39. http://dx.doi.org/10.13005/bpj/1741.
Texto completo da fonteSheela, S. "Enhancer for ovarian cyst segmentation using adaptive thresholding technique". Indian Journal of Science and Technology 13, n.º 39 (24 de outubro de 2020): 4142–50. http://dx.doi.org/10.17485/ijst/v13i39.1602.
Texto completo da fonteKhaledyan, Donya, Thomas J. Marini, Timothy M. Baran, Avice O’Connell e Kevin Parker. "Enhancing breast ultrasound segmentation through fine-tuning and optimization techniques: Sharp attention UNet". PLOS ONE 18, n.º 12 (13 de dezembro de 2023): e0289195. http://dx.doi.org/10.1371/journal.pone.0289195.
Texto completo da fonteMaolood, Ismail Yaqub, Yahya Eneid Abdulridha Al-Salhi e Songfeng Lu. "Thresholding for medical image segmentation for cancer using fuzzy entropy with level set algorithm". Open Medicine 13, n.º 1 (8 de setembro de 2018): 374–83. http://dx.doi.org/10.1515/med-2018-0056.
Texto completo da fonteHolland, Lawrence, Sofia I. Hernandez Torres e Eric J. Snider. "Using AI Segmentation Models to Improve Foreign Body Detection and Triage from Ultrasound Images". Bioengineering 11, n.º 2 (29 de janeiro de 2024): 128. http://dx.doi.org/10.3390/bioengineering11020128.
Texto completo da fonteBargsten, Lennart, Silas Raschka e Alexander Schlaefer. "Capsule networks for segmentation of small intravascular ultrasound image datasets". International Journal of Computer Assisted Radiology and Surgery 16, n.º 8 (14 de junho de 2021): 1243–54. http://dx.doi.org/10.1007/s11548-021-02417-x.
Texto completo da fonteWang, Xinyu, Zhengqi Chang, Qingfang Zhang, Cheng Li, Fei Miao e Gang Gao. "Prostate Ultrasound Image Segmentation Based on DSU-Net". Biomedicines 11, n.º 3 (21 de fevereiro de 2023): 646. http://dx.doi.org/10.3390/biomedicines11030646.
Texto completo da fonteBargsten, Lennart, Katharina A. Riedl, Tobias Wissel, Fabian J. Brunner, Klaus Schaefers, Michael Grass, Stefan Blankenberg, Moritz Seiffert e Alexander Schlaefer. "Deep learning for calcium segmentation in intravascular ultrasound images". Current Directions in Biomedical Engineering 7, n.º 1 (1 de agosto de 2021): 96–100. http://dx.doi.org/10.1515/cdbme-2021-1021.
Texto completo da fontePregitha R., Eveline, Vinod Kumar R. S. e Ebbie Selvakumar C. "FOE NET: Segmentation of Fetal in Ultrasound Images Using V-NET". International journal of electrical and computer engineering systems 14, n.º 10 (12 de dezembro de 2023): 1141–49. http://dx.doi.org/10.32985/ijeces.14.10.7.
Texto completo da fonteChang, Chenkai, Fei Qi, Chang Xu, Yiwei Shen e Qingwu Li. "A dual-modal dynamic contour-based method for cervical vascular ultrasound image instance segmentation". Mathematical Biosciences and Engineering 21, n.º 1 (2023): 1038–57. http://dx.doi.org/10.3934/mbe.2024043.
Texto completo da fonteHuang, Kuan, Yingtao Zhang, Heng-Da Cheng e Ping Xing. "Trustworthy Breast Ultrasound Image Semantic Segmentation Based on Fuzzy Uncertainty Reduction". Healthcare 10, n.º 12 (8 de dezembro de 2022): 2480. http://dx.doi.org/10.3390/healthcare10122480.
Texto completo da fonteYun, Ting, Yi Qing Xu e Lin Cao. "Semi-Supervised Ultrasound Image Segmentation Based on Curvelet Features". Applied Mechanics and Materials 239-240 (dezembro de 2012): 104–14. http://dx.doi.org/10.4028/www.scientific.net/amm.239-240.104.
Texto completo da fonteDarvish, Arman, e Shahryar Rahnamayan. "Optimal Parameter Setting of Active-Contours Using Differential Evolution and Expert-Segmented Sample Image". Journal of Advanced Computational Intelligence and Intelligent Informatics 16, n.º 6 (20 de setembro de 2012): 677–86. http://dx.doi.org/10.20965/jaciii.2012.p0677.
Texto completo da fonteWang, Yanwei, Junbo Ye, Tianxiang Wang, Jingyu Liu, Hao Dong e Xin Qiao. "Breast Ultrasound Image Segmentation Algorithm Using Adaptive Region Growing and Variation Level Sets". Mathematical Problems in Engineering 2022 (3 de outubro de 2022): 1–15. http://dx.doi.org/10.1155/2022/1752390.
Texto completo da fonteAmine, Mrabti Mohamed, e Hamdi Mohamed Ali. "Intravascular Ultrasound Image Segmentation Using Morphological Snakes". International Journal of Image, Graphics and Signal Processing 4, n.º 5 (18 de junho de 2012): 54–60. http://dx.doi.org/10.5815/ijigsp.2012.05.07.
Texto completo da fonteWen, Qiaonong, Shuang Xu e Suiren Wan. "Ultrasound Image Segmentation Based on Energy Functional". Journal of Nanoscience and Nanotechnology 16, n.º 9 (1 de setembro de 2016): 9359–70. http://dx.doi.org/10.1166/jnn.2016.12433.
Texto completo da fonteXian, Min, Yingtao Zhang, H. D. Cheng, Fei Xu, Boyu Zhang e Jianrui Ding. "Automatic breast ultrasound image segmentation: A survey". Pattern Recognition 79 (julho de 2018): 340–55. http://dx.doi.org/10.1016/j.patcog.2018.02.012.
Texto completo da fonteZhao, Yuan, Mingjie Jiang, Wai Sum Chan e Bernard Chiu. "Development of a Three-Dimensional Carotid Ultrasound Image Segmentation Workflow for Improved Efficiency, Reproducibility and Accuracy in Measuring Vessel Wall and Plaque Volume and Thickness". Bioengineering 10, n.º 10 (18 de outubro de 2023): 1217. http://dx.doi.org/10.3390/bioengineering10101217.
Texto completo da fonteFarook, I. Mohammed, S. Dhanalakshmi, V. Manikandan e C. Venkatesh. "Optimal Feature Selection for Carotid Artery Image Segmentation Using Evolutionary Computation". Applied Mechanics and Materials 626 (agosto de 2014): 79–86. http://dx.doi.org/10.4028/www.scientific.net/amm.626.79.
Texto completo da fonteDašić, Lazar, Nikola Radovanović, Tijana Šušteršič, Anđela Blagojević, Leo Benolić e Nenad Filipović. "Patch-based Convolutional Neural Network for Atherosclerotic Carotid Plaque Semantic Segmentation". Ipsi Transactions on Internet research 18, n.º 1 (1 de janeiro de 2022): 56–61. http://dx.doi.org/10.58245/ipsi.tir.22jr.10.
Texto completo da fonteLian, Jie, Mingyu Zhang, Na Jiang, Wei Bi e Xiaoqiu Dong. "Feature Extraction of Kidney Tissue Image Based on Ultrasound Image Segmentation". Journal of Healthcare Engineering 2021 (26 de abril de 2021): 1–16. http://dx.doi.org/10.1155/2021/9915697.
Texto completo da fonteArdhianto, Peter, Jen-Yung Tsai, Chih-Yang Lin, Ben-Yi Liau, Yih-Kuen Jan, Veit Babak Hamun Akbari e Chi-Wen Lung. "A Review of the Challenges in Deep Learning for Skeletal and Smooth Muscle Ultrasound Images". Applied Sciences 11, n.º 9 (28 de abril de 2021): 4021. http://dx.doi.org/10.3390/app11094021.
Texto completo da fonteDilna, Kaitheri Thacharedath, e Duraisamy Jude Hemanth. "Novel image enhancement approaches for despeckling in ultrasound images for fibroid detection in human uterus". Open Computer Science 11, n.º 1 (1 de janeiro de 2021): 399–410. http://dx.doi.org/10.1515/comp-2020-0140.
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