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Soichiro Miki
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2020 – today
- 2024
- [j14]Yukihiro Nomura
, Shouhei Hanaoka, Naoto Hayashi, Takeharu Yoshikawa, Saori Koshino
Performance changes due to differences among annotating radiologists for training data in computerized lesion detection. Int. J. Comput. Assist. Radiol. Surg. 19(8): 1527-1536 (2024) - [i2]Yosuke Yamagishi, Shouhei Hanaoka, Tomohiro Kikuchi, Takahiro Nakao, Yuta Nakamura, Yukihiro Nomura, Soichiro Miki, Takeharu Yoshikawa, Osamu Abe:
Zero-shot 3D Segmentation of Abdominal Organs in CT Scans Using Segment Anything Model 2: Adapting Video Tracking Capabilities for 3D Medical Imaging. CoRR abs/2408.06170 (2024) - 2023
- [c9]Yoshinobu Kano, Neo Watanabe, Kaito Kagaminuma, Claus Aranha, Jaewon Lee, Benedek Hauer, Hisaichi Shibata, Soichiro Miki, Yuta Nakamura, Takuya Okubo, Soga Shigemura, Rei Ito, Kazuki Takashima, Tomoki Fukuda, Masahiro Wakutani, Tomoya Hatanaka, Mami Uchida, Mikio Abe, Akihiro Mikami, Takashi Otsuki, Zhiyang Qi, Kei Harada, Michimasa Inaba, Daisuke Katagami, Hirotaka Osawa, Fujio Toriumi:
AIWolfDial 2023: Summary of Natural Language Division of 5th International AIWolf Contest. INLG (Generation Challenges) 2023: 84-100 - [i1]Hisaichi Shibata, Soichiro Miki, Yuta Nakamura
Playing the Werewolf game with artificial intelligence for language understanding. CoRR abs/2302.10646 (2023) - 2021
- [j13]Tomomi Takenaga
Multichannel three-dimensional fully convolutional residual network-based focal liver lesion detection and classification in Gd-EOB-DTPA-enhanced MRI. Int. J. Comput. Assist. Radiol. Surg. 16(9): 1527-1536 (2021) - [j12]Yukihiro Nomura
Preliminary study of generalized semiautomatic segmentation for 3D voxel labeling of lesions based on deep learning. Int. J. Comput. Assist. Radiol. Surg. 16(11): 1901-1913 (2021) - [j11]Takahiro Nakao
Unsupervised Deep Anomaly Detection in Chest Radiographs. J. Digit. Imaging 34(2): 418-427 (2021) - [j10]Yuta Nakamura
Automatic detection of actionable radiology reports using bidirectional encoder representations from transformers. BMC Medical Informatics Decis. Mak. 21(1): 262 (2021) - 2020
- [j9]Yukihiro Nomura
Novel platform for development, training, and validation of computer-assisted detection/diagnosis software. Int. J. Comput. Assist. Radiol. Surg. 15(4): 661-672 (2020) - [j8]Yukihiro Nomura
Development of training environment for deep learning with medical images on supercomputer system based on asynchronous parallel Bayesian optimization. J. Supercomput. 76(9): 7315-7332 (2020)
2010 – 2019
- 2019
- [j7]Tomomi Takenaga
Four-dimensional fully convolutional residual network-based liver segmentation in Gd-EOB-DTPA-enhanced MRI. Int. J. Comput. Assist. Radiol. Surg. 14(8): 1259-1266 (2019) - [j6]Shouhei Hanaoka
HoTPiG: a novel graph-based 3-D image feature set and its applications to computer-assisted detection of cerebral aneurysms and lung nodules. Int. J. Comput. Assist. Radiol. Surg. 14(12): 2095-2107 (2019) - 2018
- [c8]Issei Sato, Yukihiro Nomura
Managing Computer-Assisted Detection System Based on Transfer Learning with Negative Transfer Inhibition. KDD 2018: 695-704 - [c7]Daisuke Sato, Shouhei Hanaoka, Yukihiro Nomura
A primitive study on unsupervised anomaly detection with an autoencoder in emergency head CT volumes. Computer-Aided Diagnosis 2018: 105751P - 2017
- [j5]Shouhei Hanaoka
Landmark-guided diffeomorphic demons algorithm and its application to automatic segmentation of the whole spine and pelvis in CT images. Int. J. Comput. Assist. Radiol. Surg. 12(3): 413-430 (2017) - [j4]Shouhei Hanaoka
Automatic detection of vertebral number abnormalities in body CT images. Int. J. Comput. Assist. Radiol. Surg. 12(5): 719-732 (2017) - [j3]Mitsutaka Nemoto
Feasibility Study of a Generalized Framework for Developing Computer-Aided Detection Systems - a New Paradigm. J. Digit. Imaging 30(5): 629-639 (2017) - [j2]Shouhei Hanaoka
Automatic detection of over 100 anatomical landmarks in medical CT images: A framework with independent detectors and combinatorial optimization. Medical Image Anal. 35: 192-214 (2017) - 2016
- [c6]Mitsutaka Nemoto, Naoto Hayashi, Shouhei Hanaoka, Yukihiro Nomura
A primitive study of voxel feature generation by multiple stacked denoising autoencoders for detecting cerebral aneurysms on MRA. Computer-Aided Diagnosis 2016: 97852S - 2015
- [c5]Shouhei Hanaoka, Yukihiro Nomura
HoTPiG: A Novel Geometrical Feature for Vessel Morphometry and Its Application to Cerebral Aneurysm Detection. MICCAI (2) 2015: 103-110 - 2013
- [c4]Shouhei Hanaoka, Yoshitaka Masutani
A Multiple Anatomical Landmark Detection System for Body CT Images. CANDAR 2013: 308-311 - [c3]Mitsutaka Nemoto, Yoshitaka Masutani
Post-processing of Anatomical Landmark Detection: Distance Error Reduction by Pictorial Structure Matching-Based Method. CANDAR 2013: 316-319 - [c2]Yukihiro Nomura
Training Strategy for Performance Improvement in Computer-Assisted Detection of Lesions: Based on Multi-institutional Study in Teleradiology Environment. CANDAR 2013: 320-323 - [c1]Mitsutaka Nemoto, Yoshitaka Masutani
Coarse-to-fine localization of anatomical landmarks in CT images based on multi-scale local appearance and rotation-invariant spatial landmark distribution model. Image Processing 2013: 866917 - 2010
- [j1]Yukihiro Nomura, Naoto Hayashi, Yoshitaka Masutani, Takeharu Yoshikawa, Mitsutaka Nemoto, Shohei Hanaoka, Soichiro Miki, Eriko Maeda, Kuni Ohtomo:
CIRCUS: an MDA Platform for Clinical Image Analysis in Hospitals. Trans. Mass Data Anal. Images Signals 2(1): 112-127 (2010)
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