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Medical image processing and computer-aided detection/diagnosis (CAD).

H. Fujita, F. Nogata, H. Jiang, S. Kido, T. Feng, T. Hara, T. Hayashi, Y. Hirano, A. Katsumata, Y. Kawamura, T. Kokubo, J. Liu, C. Muramatsu, H. Shouno, R. Tachibana, X. Wang, F. Xiang, R. Xu, B. Yang, Y. Yokota, L. Zhang, Q. Li, and Z. Guo. ICCH, page 66-71. IEEE, (2012)

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Eiichi Kido

Ladislav Kido

Vassilios Kidonopoulos

Rafael Shoji

Shoji Wada

Other publications of authors with the same name

Automatic identification of lung candidate nodules on chest CT images based on temporal subtraction images.S. Tanaka, Y. Ikeda, H. Kim, J. Tan, S. Ishikawa, S. Murakami, T. Aoki, R. Tachibana, Y. Hirano, and S. Kido. SCIS&ISIS, page 1364-1368. IEEE, (2014)Computer-aided diagnosis for distinction between benign and malignant pulmonary nodules on chest radiographs using temporal subtraction images.N. Oda, S. Kido, S. Yamada, T. Aoki, H. Watanabe, Y. Korogi, S. Katsuragawa, and K. Doi. CARS, volume 1268 of International Congress Series, page 911-916. Elsevier, (2004)Low-cost soft-copy display accuracy in the detection of pulmonary nodules by single-exposure dual-energy subtraction: Comparison with hard-copy viewing.S. Kido, K. Kuriyama, N. Hosomi, E. Inoue, C. Kuroda, and T. Horai. J. Digit. Imaging, 13 (1): 33-37 (2000)Transparent visualization of large-scale and complex polygon meshes using a stochastic point-based rendering method.R. Xu, S. Tanaka, K. Hasegawa, W. Sheng, T. Tateyama, Y. Chen, and S. Kido. SIGGRAPH Asia Visualization in High Performance Computing, page 9:1-9:4. ACM, (2015)Automatic characterization of liver tumors from multi-phase CT images.K. Otani, D. Nishigaki, T. Hatsutani, T. Takamoto, Y. Suzuki, S. Kido, and N. Tomiyama. Medical Imaging: Computer-Aided Diagnosis, volume 12465 of SPIE Proceedings, SPIE, (2023)Unsupervised Detection of Pulmonary Opacities for Computer-Aided Diagnosis of COVID-19 on CT Images.R. Xu, X. Cao, Y. Wang, Y. Chen, X. Ye, L. Lin, W. Zhu, C. Chen, F. Xu, Y. Zhou and 3 other author(s). ICPR, page 9007-9014. IEEE, (2020)Semantic characteristics prediction of pulmonary nodule using Artificial Neural Networks.G. Li, H. Kim, J. Tan, S. Ishikawa, Y. Hirano, S. Kido, and R. Tachibana. EMBC, page 5465-5468. IEEE, (2013)Feature Representation Analysis of Deep Convolutional Neural Network using Two-stage Feature Transfer -An Application for Diffuse Lung Disease Classification-.A. Suzuki, H. Sakanashi, S. Kido, and H. Shouno. CoRR, (2018)Automated extraction of pleural effusion in three-dimensional thoracic CT images.S. Kido, and A. Tsunomori. Medical Imaging: Computer-Aided Diagnosis, volume 7260 of SPIE Proceedings, page 72600D. SPIE, (2009)Detection of Abnormal Opacity on Chest CT Images Using A 3D-CNN.Y. Koizumi, T. Kamiya, T. Aoki, and S. Kido. ICBBE, page 26-29. ACM, (2021)

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Disambiguation of "Kido, Shoji"

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Medical image processing and computer-aided detection/diagnosis (CAD).

Please choose a person to relate this publication to

Eiichi Kido

Ladislav Kido

Vassilios Kidonopoulos

Rafael Shoji

Shoji Wada

Other publications of authors with the same name

Disambiguation

BibSonomy

Disambiguation of "Kido, Shoji"

copydeleteadd this publication to your clipboardcommunity posthistory of this postURLDOIBibTeXEndNoteAPAChicagoDIN 1505HarvardMSOffice XML Medical image processing and computer-aided detection/diagnosis (CAD).

Please choose a person to relate this publication to

Eiichi Kido

Ladislav Kido

Vassilios Kidonopoulos

Rafael Shoji

Shoji Wada

Other publications of authors with the same name

Disambiguation

copy delete add this publication to your clipboard
community post
history of this post
URL
DOI
BibTeX
EndNote
APA
Chicago
DIN 1505
Harvard
MSOffice XML

Medical image processing and computer-aided detection/diagnosis (CAD).