Artigos de revistas sobre o tema "Echocardiography segmentation"
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Liao, Minqi, Yifan Lian, Yongzhao Yao, Lihua Chen, Fei Gao, Long Xu, Xin Huang, Xinxing Feng e Suxia Guo. "Left Ventricle Segmentation in Echocardiography with Transformer". Diagnostics 13, n.º 14 (13 de julho de 2023): 2365. http://dx.doi.org/10.3390/diagnostics13142365.
Texto completo da fonteHuang, Helin, Zhenyi Ge, Hairui Wang, Jing Wu, Chunqiang Hu, Nan Li, Xiaomei Wu e Cuizhen Pan. "Segmentation of Echocardiography Based on Deep Learning Model". Electronics 11, n.º 11 (27 de maio de 2022): 1714. http://dx.doi.org/10.3390/electronics11111714.
Texto completo da fonteOno, Shunzaburo, Masaaki Komatsu, Akira Sakai, Hideki Arima, Mie Ochida, Rina Aoyama, Suguru Yasutomi et al. "Automated Endocardial Border Detection and Left Ventricular Functional Assessment in Echocardiography Using Deep Learning". Biomedicines 10, n.º 5 (6 de maio de 2022): 1082. http://dx.doi.org/10.3390/biomedicines10051082.
Texto completo da fonteChen, Tongwaner, Menghua Xia, Yi Huang, Jing Jiao e Yuanyuan Wang. "Cross-Domain Echocardiography Segmentation with Multi-Space Joint Adaptation". Sensors 23, n.º 3 (28 de janeiro de 2023): 1479. http://dx.doi.org/10.3390/s23031479.
Texto completo da fonteWilczewska, Aleksandra, Szymon Cygan e Jakub Żmigrodzki. "Segmentation Enhanced Elastic Image Registration for 2D Speckle Tracking Echocardiography—Performance Study In Silico". Ultrasonic Imaging 44, n.º 1 (janeiro de 2022): 39–54. http://dx.doi.org/10.1177/01617346211068812.
Texto completo da fonteTuncay, V., N. Prakken, P. M. A. van Ooijen, R. P. J. Budde, T. Leiner e M. Oudkerk. "Semiautomatic, Quantitative Measurement of Aortic Valve Area Using CTA: Validation and Comparison with Transthoracic Echocardiography". BioMed Research International 2015 (2015): 1–9. http://dx.doi.org/10.1155/2015/648283.
Texto completo da fonteEl rai, Marwa Chendeb, Muna Darweesh e Mina Al-Saad. "Semi-Supervised Segmentation of Echocardiography Videos Using Graph Signal Processing". Electronics 11, n.º 21 (26 de outubro de 2022): 3462. http://dx.doi.org/10.3390/electronics11213462.
Texto completo da fonteHuang, Jun, Aiyue Huang, Ruqin Xu, Musheng Wu, Peng Wang e Qing Wang. "Automatic Segmentation and Assessment of Valvular Regurgitations with Color Doppler Echocardiography Images: A VABC-UNet-Based Framework". Bioengineering 10, n.º 11 (16 de novembro de 2023): 1319. http://dx.doi.org/10.3390/bioengineering10111319.
Texto completo da fonteCai Ming, Huang Xiaoyang, Wang Boliang e Su Maolong. "Automatic Mitral Valve Leaflet Scallops Segmentation in Echocardiography". International Journal of Advancements in Computing Technology 5, n.º 8 (30 de abril de 2013): 687–94. http://dx.doi.org/10.4156/ijact.vol5.issue8.78.
Texto completo da fonteSkalski, Andrzej, e Paweł Turcza. "Heart Segmentation in Echo Images". Metrology and Measurement Systems 18, n.º 2 (1 de janeiro de 2011): 305–14. http://dx.doi.org/10.2478/v10178-011-0012-y.
Texto completo da fonteBarrile, V., F. Cotroneo, E. Genovese, E. Barrile e G. Bilotta. "AN AI SEGMENTER ON MEDICAL IMAGING FOR GEOMATICS APPLICATIONS CONSISTING OF A TWO-STATE PIPELINE, SNNS NETWORK AND WATERSHED ALGORITHM". International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XLVIII-2/W3-2023 (12 de maio de 2023): 21–26. http://dx.doi.org/10.5194/isprs-archives-xlviii-2-w3-2023-21-2023.
Texto completo da fonteRachmatullah, M. N., Siti Nurmaini, A. I. Sapitri, A. Darmawahyuni, B. Tutuko e Firdaus Firdaus. "Convolutional neural network for semantic segmentation of fetal echocardiography based on four-chamber view". Bulletin of Electrical Engineering and Informatics 10, n.º 4 (1 de agosto de 2021): 1987–96. http://dx.doi.org/10.11591/eei.v10i4.3060.
Texto completo da fonteCai, Junfeng, Xiahai Zhuang, Yuanyuan Nie, Zhe Luo e Lixu Gu. "Real-time aortic valve segmentation from transesophageal echocardiography sequence". International Journal of Computer Assisted Radiology and Surgery 10, n.º 4 (3 de agosto de 2014): 447–58. http://dx.doi.org/10.1007/s11548-014-1104-y.
Texto completo da fonteValanrani, B. Arockia. "PREDICTING CARDIAC ISSUES FROM ECHOCARDIOGRAMS: A LITERATURE REVIEW USING DEEP LEARNING AND MACHINE LEARNING TECHNIQUES". international journal of advanced research in computer science 15, n.º 1 (20 de fevereiro de 2024): 5–13. http://dx.doi.org/10.26483/ijarcs.v15i1.7040.
Texto completo da fonteDong, Suyu, Gongning Luo, Kuanquan Wang, Shaodong Cao, Qince Li e Henggui Zhang. "A Combined Fully Convolutional Networks and Deformable Model for Automatic Left Ventricle Segmentation Based on 3D Echocardiography". BioMed Research International 2018 (10 de setembro de 2018): 1–16. http://dx.doi.org/10.1155/2018/5682365.
Texto completo da fonteShoaib, Muhammad Ali, Joon Huang Chuah, Raza Ali, Samiappan Dhanalakshmi, Yan Chai Hum, Azira Khalil e Khin Wee Lai. "Fully Automatic Left Ventricle Segmentation Using Bilateral Lightweight Deep Neural Network". Life 13, n.º 1 (1 de janeiro de 2023): 124. http://dx.doi.org/10.3390/life13010124.
Texto completo da fonteTeng, Long, ZhongLiang Fu, Qian Ma, Yu Yao, Bing Zhang, Kai Zhu e Ping Li. "Interactive Echocardiography Translation Using Few-Shot GAN Transfer Learning". Computational and Mathematical Methods in Medicine 2020 (19 de março de 2020): 1–9. http://dx.doi.org/10.1155/2020/1487035.
Texto completo da fonteMortada, MHD Jafar, Selene Tomassini, Haidar Anbar, Micaela Morettini, Laura Burattini e Agnese Sbrollini. "Segmentation of Anatomical Structures of the Left Heart from Echocardiographic Images Using Deep Learning". Diagnostics 13, n.º 10 (9 de maio de 2023): 1683. http://dx.doi.org/10.3390/diagnostics13101683.
Texto completo da fonteNurmaini, Siti, Muhammad Naufal Rachmatullah, Ade Iriani Sapitri, Annisa Darmawahyuni, Bambang Tutuko, Firdaus Firdaus, Radiyati Umi Partan e Nuswil Bernolian. "Deep Learning-Based Computer-Aided Fetal Echocardiography: Application to Heart Standard View Segmentation for Congenital Heart Defects Detection". Sensors 21, n.º 23 (30 de novembro de 2021): 8007. http://dx.doi.org/10.3390/s21238007.
Texto completo da fonteYe, Zi, Yogan Jaya Kumar, Fengyan Song, Guanxi Li e Suyu Zhang. "Bi-DCNet: Bilateral Network with Dilated Convolutions for Left Ventricle Segmentation". Life 13, n.º 4 (18 de abril de 2023): 1040. http://dx.doi.org/10.3390/life13041040.
Texto completo da fonteKim, Dong Ok, Minsu Chae e HwaMin Lee. "Revolutionizing Echocardiography: A Comparative Study of Advanced AI Models for Precise Left Ventricular Segmentation". International Journal on Advanced Science, Engineering and Information Technology 14, n.º 3 (5 de junho de 2024): 835–40. http://dx.doi.org/10.18517/ijaseit.14.3.18073.
Texto completo da fonteStoean, Catalin, Nebojsa Bacanin, Wiesław Paja, Ruxandra Stoean, Dominic Iliescu, Ciprian Patru e Rodica Nagy. "Semantic segmentation of fetal heart components in second trimester echocardiography". Procedia Computer Science 207 (2022): 3085–92. http://dx.doi.org/10.1016/j.procs.2022.09.366.
Texto completo da fonteMazaheri, Samaneh, Puteri Suhaiza Binti Sulaiman, Rahmita Wirza, Mohd Zamrin Dimon, Fatima Khalid e Rohollah Moosavi Tayebi. "Segmentation Methods of Echocardiography Images for Left Ventricle Boundary Detection". Journal of Computer Science 11, n.º 9 (1 de setembro de 2015): 957–70. http://dx.doi.org/10.3844/jcssp.2015.957.970.
Texto completo da fonteSigit, Riyanto, Calvin Alfa Roji, Tri Harsono e Son Kuswadi. "Improved echocardiography segmentation using active shape model and optical flow". TELKOMNIKA (Telecommunication Computing Electronics and Control) 17, n.º 2 (1 de abril de 2019): 809. http://dx.doi.org/10.12928/telkomnika.v17i2.11821.
Texto completo da fonteDanilov, V. V., I. P. Skirnevskiy e O. M. Gerget. "Segmentation of anatomical structures of the heart based on echocardiography". Journal of Physics: Conference Series 803 (janeiro de 2017): 012031. http://dx.doi.org/10.1088/1742-6596/803/1/012031.
Texto completo da fonteCorinzia, Luca, Fabian Laumer, Alessandro Candreva, Maurizio Taramasso, Francesco Maisano e Joachim M. Buhmann. "Neural collaborative filtering for unsupervised mitral valve segmentation in echocardiography". Artificial Intelligence in Medicine 110 (novembro de 2020): 101975. http://dx.doi.org/10.1016/j.artmed.2020.101975.
Texto completo da fonteCelestin, B. E., S. P. Bagherzadeh, E. Santana, M. Frost, I. Mathias, A. J. Sweatt, R. Zamanian et al. "Echocardiography in Pulmonary Arterial Hypertension Using Deep Learning Segmentation Algorithms". Journal of Heart and Lung Transplantation 43, n.º 4 (abril de 2024): S410. http://dx.doi.org/10.1016/j.healun.2024.02.1312.
Texto completo da fonteBalasubramani, Madankumar, Chih-Wei Sung, Mu-Yang Hsieh, Edward Pei-Chuan Huang, Jiann-Shing Shieh e Maysam F. Abbod. "Automated Left Ventricle Segmentation in Echocardiography Using YOLO: A Deep Learning Approach for Enhanced Cardiac Function Assessment". Electronics 13, n.º 13 (1 de julho de 2024): 2587. http://dx.doi.org/10.3390/electronics13132587.
Texto completo da fonteWu, Huisi, Jingyin Lin, Wende Xie e Jing Qin. "Super-efficient Echocardiography Video Segmentation via Proxy- and Kernel-Based Semi-supervised Learning". Proceedings of the AAAI Conference on Artificial Intelligence 37, n.º 3 (26 de junho de 2023): 2803–11. http://dx.doi.org/10.1609/aaai.v37i3.25381.
Texto completo da fonteZhuang, Zhemin, Pengcheng Jin, Alex Noel Joseph Raj, Ye Yuan e Shuxin Zhuang. "Automatic Segmentation of Left Ventricle in Echocardiography Based on YOLOv3 Model to Achieve Constraint and Positioning". Computational and Mathematical Methods in Medicine 2021 (16 de maio de 2021): 1–11. http://dx.doi.org/10.1155/2021/3772129.
Texto completo da fonteShiri, M., H. Behnam, H. Yeganegi, Z. A. Sani e N. Nematollahi. "TRACKABLE-SPECKLE DETECTION USING A DUAL-PATH CONVOLUTIONAL NEURAL NETWORK FOR NODES SELECTION IN SPECKLE TRACKING ECHOCARDIOGRAPHY". Asian Journal Of Medical Technology 2, n.º 2 (5 de agosto de 2022): 33–54. http://dx.doi.org/10.32896/ajmedtech.v2n2.33-54.
Texto completo da fonteHan, Guowei, Tianliang Jin, Li Zhang, Chen Guo, Hua Gui, Risu Na, Xuesong Wang e Haihua Bai. "Adoption of Compound Echocardiography under Artificial Intelligence Algorithm in Fetal Congenial Heart Disease Screening during Gestation". Applied Bionics and Biomechanics 2022 (1 de junho de 2022): 1–8. http://dx.doi.org/10.1155/2022/6410103.
Texto completo da fonteAzizi, Fityan, Mgs M. Luthfi Ramadhan e Wisnu Jatmiko. "Encoder-Decoder with Atrous Spatial Pyramid Pooling for Left Ventricle Segmentation in Echocardiography". Jurnal Ilmu Komputer dan Informasi 16, n.º 2 (3 de julho de 2023): 163–69. http://dx.doi.org/10.21609/jiki.v16i2.1165.
Texto completo da fonteAmer, Alyaa, Xujiong Ye e Faraz Janan. "ResDUnet: A Deep Learning-Based Left Ventricle Segmentation Method for Echocardiography". IEEE Access 9 (2021): 159755–63. http://dx.doi.org/10.1109/access.2021.3122256.
Texto completo da fonteAndreassen, Borge Solli, Federico Veronesi, Olivier Gerard, Anne H. Schistad Solberg e Eigil Samset. "Mitral Annulus Segmentation Using Deep Learning in 3-D Transesophageal Echocardiography". IEEE Journal of Biomedical and Health Informatics 24, n.º 4 (abril de 2020): 994–1003. http://dx.doi.org/10.1109/jbhi.2019.2959430.
Texto completo da fonteHu, Yujin, Bei Xia, Muyi Mao, Zelong Jin, Jie Du, Libao Guo, Alejandro F. Frangi, Baiying Lei e Tianfu Wang. "AIDAN: An Attention-Guided Dual-Path Network for Pediatric Echocardiography Segmentation". IEEE Access 8 (2020): 29176–87. http://dx.doi.org/10.1109/access.2020.2971383.
Texto completo da fonteBernard, Olivier, Johan G. Bosch, Brecht Heyde, Martino Alessandrini, Daniel Barbosa, Sorina Camarasu-Pop, Frederic Cervenansky et al. "Standardized Evaluation System for Left Ventricular Segmentation Algorithms in 3D Echocardiography". IEEE Transactions on Medical Imaging 35, n.º 4 (abril de 2016): 967–77. http://dx.doi.org/10.1109/tmi.2015.2503890.
Texto completo da fontePearlman, P. C., H. D. Tagare, B. A. Lin, A. J. Sinusas e J. S. Duncan. "Segmentation of 3D radio frequency echocardiography using a spatio-temporal predictor". Medical Image Analysis 16, n.º 2 (fevereiro de 2012): 351–60. http://dx.doi.org/10.1016/j.media.2011.09.002.
Texto completo da fonteDong, Suyu, Gongning Luo, Clara Tam, Wei Wang, Kuanquan Wang, Shaodong Cao, Bo Chen, Henggui Zhang e Shuo Li. "Deep Atlas Network for Efficient 3D Left Ventricle Segmentation on Echocardiography". Medical Image Analysis 61 (abril de 2020): 101638. http://dx.doi.org/10.1016/j.media.2020.101638.
Texto completo da fonteBersvendsen, Jørn, Fredrik Orderud, Øyvind Lie, Richard John Massey, Kristian Fosså, Raúl San José Estépar, Stig Urheim e Eigil Samset. "Semiautomated biventricular segmentation in three-dimensional echocardiography by coupled deformable surfaces". Journal of Medical Imaging 4, n.º 2 (24 de maio de 2017): 024005. http://dx.doi.org/10.1117/1.jmi.4.2.024005.
Texto completo da fonteShekhar, R., V. Zagrodsky e V. Walimbe. "3D Stress echocardiography: development of novel visualization, registration and segmentation algorithms". International Congress Series 1268 (junho de 2004): 1072–77. http://dx.doi.org/10.1016/j.ics.2004.03.107.
Texto completo da fonteBatool, Samana, Imtiaz Ahmad Taj e Mubeen Ghafoor. "Ejection Fraction Estimation from Echocardiograms Using Optimal Left Ventricle Feature Extraction Based on Clinical Methods". Diagnostics 13, n.º 13 (24 de junho de 2023): 2155. http://dx.doi.org/10.3390/diagnostics13132155.
Texto completo da fonteHuang, Mu-Shiang, Chi-Shiang Wang, Jung-Hsien Chiang, Ping-Yen Liu e Wei-Chuan Tsai. "Automated Recognition of Regional Wall Motion Abnormalities Through Deep Neural Network Interpretation of Transthoracic Echocardiography". Circulation 142, n.º 16 (20 de outubro de 2020): 1510–20. http://dx.doi.org/10.1161/circulationaha.120.047530.
Texto completo da fonteMaman, S. Ghanbari, A. Shalbaf, H. Behnam, Z. Alizadeh Sani e M. Shojaei Fard. "FULLY AUTOMATIC SEGMENTATION OF LEFT VENTRICLE IN A SEQUENCE OF ECHOCARDIOGRAPHY IMAGES OF ONE CARDIAC CYCLE BY DYNAMIC DIRECTIONAL VECTOR FIELD CONVOLUTION (DDVFC) METHOD AND MANIFOLD LEARNING". Biomedical Engineering: Applications, Basis and Communications 25, n.º 02 (abril de 2013): 1350022. http://dx.doi.org/10.4015/s1016237213500221.
Texto completo da fonteKang, Seungyoung, Sun Ju Kim, Hong Gi Ahn, Kyoung-Chul Cha e Sejung Yang. "Left ventricle segmentation in transesophageal echocardiography images using a deep neural network". PLOS ONE 18, n.º 1 (20 de janeiro de 2023): e0280485. http://dx.doi.org/10.1371/journal.pone.0280485.
Texto completo da fonteGinty, Olivia K., John M. Moore, Yuanwei Xu, Wenyao Xia, Satoru Fujii, Daniel Bainbridge, Terry M. Peters, Bob B. Kiaii e Michael W. A. Chu. "Dynamic Patient-Specific Three-Dimensional Simulation of Mitral Repair". Innovations: Technology and Techniques in Cardiothoracic and Vascular Surgery 13, n.º 1 (janeiro de 2018): 11–22. http://dx.doi.org/10.1097/imi.0000000000000463.
Texto completo da fonteWahlang, Imayanmosha, Sk Mahmudul Hassan, Arnab Kumar Maji, Goutam Saha, Michal Jasinski, Zbigniew Leonowicz e Elzbieta Jasinska. "Classification of Valvular Regurgitation Using Echocardiography". Applied Sciences 12, n.º 20 (17 de outubro de 2022): 10461. http://dx.doi.org/10.3390/app122010461.
Texto completo da fonteCui, Xiaoxiao, Pengfei Zhang, Yujun Li, Zhi Liu, Xiaoyan Xiao, Yang Zhang, Longkun Sun, Lizhen Cui, Guang Yang e Shuo Li. "MCAL: An Anatomical Knowledge Learning Model for Myocardial Segmentation in 2-D Echocardiography". IEEE Transactions on Ultrasonics, Ferroelectrics, and Frequency Control 69, n.º 4 (abril de 2022): 1277–87. http://dx.doi.org/10.1109/tuffc.2022.3151647.
Texto completo da fonteLeclerc, Sarah, Erik Smistad, Joao Pedrosa, Andreas Ostvik, Frederic Cervenansky, Florian Espinosa, Torvald Espeland et al. "Deep Learning for Segmentation Using an Open Large-Scale Dataset in 2D Echocardiography". IEEE Transactions on Medical Imaging 38, n.º 9 (setembro de 2019): 2198–210. http://dx.doi.org/10.1109/tmi.2019.2900516.
Texto completo da fonteWu, H. S., D. Wang, L. Shi e C. M. Yu. "Automatic segmentation of left ventricle in 3D echocardiography using a level set approach". International Journal of Cardiology 164, n.º 2 (abril de 2013): S12—S13. http://dx.doi.org/10.1016/s0167-5273(13)70558-8.
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