Toru Hironaka
According to our database1,
Toru Hironaka
authored at least 13 papers
between 2016 and 2021.
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Bibliography
2021
Weakly unsupervised conditional generative adversarial network for image-based prognostic prediction for COVID-19 patients based on chest CT.
Medical Image Anal., 2021
2020
Proceedings of the Medical Imaging 2020: Computer-Aided Diagnosis, 2020
Comparative performance of 3D-DenseNet, 3D-ResNet, and 3D-VGG models in polyp detection for CT colonography.
Proceedings of the Medical Imaging 2020: Computer-Aided Diagnosis, 2020
2019
Ensemble 3D residual network (E3D-ResNet) for reduction of false-positive polyp detections in CT colonography.
Proceedings of the Medical Imaging 2019: Computer-Aided Diagnosis, San Diego, 2019
2018
Deep radiomic prediction with clinical predictors of the survival in patients with rheumatoid arthritis-associated interstitial lung diseases.
Proceedings of the Medical Imaging 2018: Computer-Aided Diagnosis, 2018
Detection of colorectal masses in CT colonography: application of deep residual networks for differentiating masses from normal colon anatomy.
Proceedings of the Medical Imaging 2018: Computer-Aided Diagnosis, 2018
2017
Deep ensemble learning of virtual endoluminal views for polyp detection in CT colonography.
Proceedings of the Medical Imaging 2017: Computer-Aided Diagnosis, 2017
Deep multi-spectral ensemble learning for electronic cleansing in dual-energy CT colonography.
Proceedings of the Medical Imaging 2017: Computer-Aided Diagnosis, 2017
Electronic cleansing for CT colonography using spectral-driven iterative reconstruction.
Proceedings of the Medical Imaging 2017: Computer-Aided Diagnosis, 2017
Deep learning of contrast-coated serrated polyps for computer-aided detection in CT colonography.
Proceedings of the Medical Imaging 2017: Computer-Aided Diagnosis, 2017
2016
Proceedings of the Medical Imaging 2016: Computer-Aided Diagnosis, San Diego, 2016
Performance evaluation of multi-material electronic cleansing for ultra-low-dose dual-energy CT colonography.
Proceedings of the Medical Imaging 2016: Computer-Aided Diagnosis, San Diego, 2016
Deep transfer learning of virtual endoluminal views for the detection of polyps in CT colonography.
Proceedings of the Medical Imaging 2016: Computer-Aided Diagnosis, San Diego, 2016