For: | Sugimoto K, Shiraishi J, Moriyasu F, Doi K. Computer-aided diagnosis for contrast-enhanced ultrasound in the liver. World J Radiol 2010; 2(6): 215-223 [PMID: 21160633 DOI: 10.4329/wjr.v2.i6.215] |
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URL: | https://www.wjgnet.com/1949-8470/full/v2/i6/215.htm |
Number | Citing Articles |
1 |
R. Suganya, S. Rajaram. Classification of liver diseases from ultrasound images using a hybrid kohonen SOM and LPND speckle reduction method. 2012 IEEE International Conference on Signal Processing, Computing and Control 2012; : 1 doi: 10.1109/ISPCC.2012.6224368
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2 |
Catalin Daniel Caleanu, Georgiana Simion. A Bag of Features Approach for CEUS Liver Lesions Investigation. 2019 42nd International Conference on Telecommunications and Signal Processing (TSP) 2019; : 323 doi: 10.1109/TSP.2019.8768851
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3 |
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4 |
Katsutoshi Sugimoto, Junji Shiraishi, Hironori Tanaka, Kaoru Tsuchiya, Kazunobu Aso, Yoshiyuki Kobayashi, Hiroko Iijima, Fuminori Moriyasu. Computer‐aided diagnosis for estimating the malignancy grade of hepatocellular carcinoma using contrast‐enhanced ultrasound: an ROC observer study. Liver International 2016; 36(7): 1026 doi: 10.1111/liv.13043
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5 |
Luminita Moraru, Dorin Bibicu, Anjan Biswas. Standalone functional CAD system for multi-object case analysis in hepatic disorders. Computers in Biology and Medicine 2013; 43(8): 967 doi: 10.1016/j.compbiomed.2013.04.014
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6 |
馨瑶 王. Application Value of Ultasound-Based Radiomics in the Diagnosis and Treatment of Hepatocellular Carcinoma. Advances in Clinical Medicine 2023; 13(11): 18386 doi: 10.12677/ACM.2023.13112582
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7 |
Akiko Saito, Masakazu Yamamoto, Satoshi Katagiri, Shingo Yamashita, Masayuki Nakano, Toshio Morizane. Early hemodynamics of hepatocellular carcinoma using contrast-enhanced ultrasound with Sonazoid: focus on the pure arterial and early portal phases. Global Health & Medicine 2020; 2(5): 319 doi: 10.35772/ghm.2020.01092
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8 |
Marinela-Cristiana Urhuț, Larisa Daniela Săndulescu, Costin Teodor Streba, Mădălin Mămuleanu, Adriana Ciocâlteu, Sergiu Marian Cazacu, Suzana Dănoiu. Diagnostic Performance of an Artificial Intelligence Model Based on Contrast-Enhanced Ultrasound in Patients with Liver Lesions: A Comparative Study with Clinicians. Diagnostics 2023; 13(21): 3387 doi: 10.3390/diagnostics13213387
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9 |
Ana L. M. Pavan, Marwa Benabdallah, Marie-Ange Lebre, Diana Rodrigues de Pina, Faouzi Jaziri, Antoine Vacavant, Achraf Mtibaa, Hawa Mohamed Ali, Manuel Grand-Brochier, Hugo Rositi, Benoît Magnin, Armand Abergel, Pascal Chabrot. A parallel framework for HCC detection in DCE-MRI sequences with wavelet-based description and SVM classification. Proceedings of the 33rd Annual ACM Symposium on Applied Computing 2018; : 14 doi: 10.1145/3167132.3167167
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10 |
A. Bhagya, S. Perumal. Preprocessing and feature extraction of MRI Liver Tumour images using A novel multi-class identification (NMCI) framework. 2024 International Conference on Emerging Systems and Intelligent Computing (ESIC) 2024; : 143 doi: 10.1109/ESIC60604.2024.10481596
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11 |
Catalin-Daniel Caleanu, Georgiana Simion, Ciprian David, Vasile Gui, Tudor Moga, Alina Popescu, Roxana Sirli, Ioan Sporea. A study over the importance of arterial phase temporal parameters in focal liver lesions CEUS based diagnosis. 2014 11th International Symposium on Electronics and Telecommunications (ISETC) 2014; : 1 doi: 10.1109/ISETC.2014.7010799
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12 |
Charlie A. Hamm, Clinton J. Wang, Lynn J. Savic, Marc Ferrante, Isabel Schobert, Todd Schlachter, MingDe Lin, James S. Duncan, Jeffrey C. Weinreb, Julius Chapiro, Brian Letzen. Deep learning for liver tumor diagnosis part I: development of a convolutional neural network classifier for multi-phasic MRI. European Radiology 2019; 29(7): 3338 doi: 10.1007/s00330-019-06205-9
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13 |
Marcel Vetter, Maximilian J Waldner, Sebastian Zundler, Daniel Klett, Thomas Bocklitz, Markus F Neurath, Werner Adler, Daniel Jesper. Artificial intelligence for the classification of focal liver lesions in ultrasound – a systematic review. Ultraschall in der Medizin - European Journal of Ultrasound 2023; 44(04): 395 doi: 10.1055/a-2066-9372
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14 |
M.R. Hüseynova, N.Y. Bayramov, M.H. Məmmədova. РОЛЬ АЛГОРИТМОВ ИСКУССТВЕННОГО ИНТЕЛЛЕКТА В ДИАГНОСТИКЕ. Azerbaijan Medical Journal 2023; (2): 164 doi: 10.34921/amj.2023.2.026
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15 |
Bhawna Singla, Soham Taneja, Rishika Garg, Preeti Nagrath. Liver disease prediction using machine learning and deep learning: A comparative study. Intelligent Decision Technologies 2022; 16(1): 71 doi: 10.3233/IDT-210065
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16 |
Dan Mihai Mihailescu, Vasile Gui, Corneliu Ioan Toma, Alina Popescu, Ioan Sporea. Simultaneous filtering and tracking of focal liver lesion for time intensity curve analysis in contrast enhanced ultrasound imagery. 2014 IEEE 12th International Symposium on Applied Machine Intelligence and Informatics (SAMI) 2014; : 233 doi: 10.1109/SAMI.2014.6822413
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17 |
U. Rajendra Acharya, Joel En Wei Koh, Yuki Hagiwara, Jen Hong Tan, Arkadiusz Gertych, Anushya Vijayananthan, Nur Adura Yaakup, Basri Johan Jeet Abdullah, Mohd Kamil Bin Mohd Fabell, Chai Hong Yeong. Automated diagnosis of focal liver lesions using bidirectional empirical mode decomposition features. Computers in Biology and Medicine 2018; 94: 11 doi: 10.1016/j.compbiomed.2017.12.024
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18 |
Alessandro Martinino, Mohammad Aloulou, Surobhi Chatterjee, Juan Pablo Scarano Pereira, Saurabh Singhal, Tapan Patel, Thomas Paul-Emile Kirchgesner, Salvatore Agnes, Salvatore Annunziata, Giorgio Treglia, Francesco Giovinazzo. Artificial Intelligence in the Diagnosis of Hepatocellular Carcinoma: A Systematic Review. Journal of Clinical Medicine 2022; 11(21): 6368 doi: 10.3390/jcm11216368
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19 |
Kazuya TAKAGI, Satoshi KONDO, Kensuke NAKAMURA, Mitsuyoshi TAKIGUCHI. Lesion Type Classification by Applying Machine-Learning Technique to Contrast-Enhanced Ultrasound Images. IEICE Transactions on Information and Systems 2014; (11): 2947 doi: 10.1587/transinf.2013EDP7464
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20 |
Dan Mihai Mihailescu, Vasile Gui, Corneliu Ioan Toma, Alina Popescu, Ioan Sporea. Automatic evaluation of steatosis by ultrasound image analysis. 2012 10th International Symposium on Electronics and Telecommunications 2012; : 311 doi: 10.1109/ISETC.2012.6408111
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