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Disambiguation of "Hayashi, Naoto"

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Appearance Similarity Flow for Quantification of Anatomical Landmark Uncertainty in Medical Images.

, , , , and . ISVC (1), volume 7431 of Lecture Notes in Computer Science, page 12-21. Springer, (2012)

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Naoto Kamano

Naoto Matsumura

Ken Hayashi

Mutsumi Hayashi

Akiko Hayashi

 

Other publications of authors with the same name

Aging prediction using deep generative model toward the development of preventive medicine., , , , and . CoRR, (2022)Appearance Similarity Flow for Quantification of Anatomical Landmark Uncertainty in Medical Images., , , , and . ISVC (1), volume 7431 of Lecture Notes in Computer Science, page 12-21. Springer, (2012)Improved identification of tumors in 18F-FDG-PET examination by normalizing the standard uptake in the liver based on blood test data., , , , , , , , and . Int. J. Comput. Assist. Radiol. Surg., 19 (3): 581-590 (March 2024)Clinical Comparable Corpus Describing the Same Subjects with Different Expressions., , , , , , , and . MedInfo, volume 290 of Studies in Health Technology and Informatics, page 253-257. IOS Press, (2021)On the Matrix-Free Generation of Adversarial Perturbations for Black-Box Attacks., , , , and . CoRR, (2020)Lung lesion detection in FDG-PET/CT with Gaussian process regression., , , , , , and . Medical Imaging: Computer-Aided Diagnosis, volume 10134 of SPIE Proceedings, page 101340C. SPIE, (2017)A unified framework for concurrent detection of anatomical landmarks for medical image understanding., , , , , , , and . Medical Imaging: Image Processing, volume 7962 of SPIE Proceedings, page 79623E. SPIE, (2011)3-D Graph Cut Segmentation with Riemannian Metrics to Avoid the Shrinking Problem., , , , , , , and . MICCAI (3), volume 6893 of Lecture Notes in Computer Science, page 554-561. Springer, (2011)Managing Computer-Assisted Detection System Based on Transfer Learning with Negative Transfer Inhibition., , , , , , and . KDD, page 695-704. ACM, (2018)Four-dimensional fully convolutional residual network-based liver segmentation in Gd-EOB-DTPA-enhanced MRI., , , , , , , , , and . Int. J. Comput. Assist. Radiol. Surg., 14 (8): 1259-1266 (2019)