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For: Saito R, Koizumi N, Nishiyama Y, Imaizumi T, Kusahara K, Yagasaki S, Matsumoto N, Masuzaki R, Takahashi T, Ogawa M. Evaluation of ultrasonic fibrosis diagnostic system using convolutional network for ordinal regression. Int J Comput Assist Radiol Surg 2021;16:1969-1975. [PMID: 34545465 DOI: 10.1007/s11548-021-02491-1] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/19/2021] [Accepted: 09/03/2021] [Indexed: 12/21/2022]
Number Cited by Other Article(s)
1
Fujii I, Matsumoto N, Ogawa M, Konishi A, Kaneko M, Watanabe Y, Masuzaki R, Kogure H, Koizumi N, Sugitani M. Artificial Intelligence and Image Analysis-Assisted Diagnosis for Fibrosis Stage of Metabolic Dysfunction-Associated Steatotic Liver Disease Using Ultrasonography: A Pilot Study. Diagnostics (Basel) 2024;14:2585. [PMID: 39594250 PMCID: PMC11593288 DOI: 10.3390/diagnostics14222585] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/29/2024] [Revised: 10/31/2024] [Accepted: 11/07/2024] [Indexed: 11/28/2024]  Open
2
Hirata S, Isshiki A, Tai DI, Tsui PH, Yoshida K, Yamaguchi T. Convolutional neural network classification of ultrasound images by liver fibrosis stages based on echo-envelope statistics. FRONTIERS IN PHYSICS 2023;11. [DOI: 10.3389/fphy.2023.1164622] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 12/04/2024]
3
Wang X, Song L, Zhuang Y, Han L, Chen K, Lin J, Luo Y. A Hierarchical Siamese Network for Noninvasive Staging of Liver Fibrosis Based on US Image Pairs of the Liver and Spleen. SENSORS (BASEL, SWITZERLAND) 2023;23:5450. [PMID: 37420617 DOI: 10.3390/s23125450] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/24/2023] [Revised: 06/01/2023] [Accepted: 06/05/2023] [Indexed: 07/09/2023]
4
Isshiki A, Tai DI, Tsui PH, Yoshida K, Yamaguchi T, Hirata S. Convolutional Neural Network Classification of Liver Fibrosis Stages Using Ultrasonic Images Colorized by Features of Echo-Envelope Statistics. LECTURE NOTES IN ELECTRICAL ENGINEERING 2023:441-451. [DOI: 10.1007/978-981-16-6775-6_36] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 01/04/2025]
5
Ma L, Wang R, He Q, Huang L, Wei X, Lu X, Du Y, Luo J, Liao H. Artificial intelligence-based ultrasound imaging technologies for hepatic diseases. ILIVER 2022;1:252-264. [DOI: 10.1016/j.iliver.2022.11.001] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 01/04/2025]
6
Guo X, Lei Y, He P, Zeng W, Yang R, Ma Y, Feng P, Lyu Q, Wang G, Shan H. An ensemble learning method based on ordinal regression for COVID-19 diagnosis from chest CT. Phys Med Biol 2021;66. [PMID: 34715678 DOI: 10.1088/1361-6560/ac34b2] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/20/2021] [Accepted: 10/29/2021] [Indexed: 12/16/2022]
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