Shoji Kido

发表

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

Rui Xu, Tatsuro Hayashi, Hiroshi Fujita, 2012, 2012 International Conference on Computerized Healthcare (ICCH).

Discrimination of Lung Sounds Using a Statistics of Waveform Intervals

Shoji Kido, Hayaru Shouno, Taketoshi Orihashi, 2006, PDPTA.

Feature Representation Analysis of Deep Convolutional Neural Network using Two-stage Feature Transfer -An Application for Diffuse Lung Disease Classification- pdf

Shoji Kido, Hayaru Shouno, Hidenori Sakanashi, 2018, ArXiv.

Detection of pulmonary nodules on chest x-ray images using R-CNN

Shingo Mabu, Yasushi Hirano, Shoji Kido, 2019, Other Conferences.

Effect of microscopic magnification on the establishment of an artificial intelligence for cervical cells using deep learning

Shoji Kido, Masaki Mori, Taisuke Tsumori, 2020 .

A Transfer Learning Method with Deep Convolutional Neural Network for Diffuse Lung Disease Classification

Satoshi Suzuki, Shoji Kido, Hayaru Shouno, 2015, ICONIP.

Pulmonary Textures Classification via a Multi-Scale Attention Network

Rui Xu, Yasushi Hirano, Shoji Kido, 2020, IEEE Journal of Biomedical and Health Informatics.

Evolutionary Neural Network and Visualization for CNN-based Pulmonary Textures Classification

Rui Xu, Lin Lin, Shoji Kido, 2020, 2020 IEEE 32nd International Conference on Tools with Artificial Intelligence (ICTAI).

Automatic liver segmentation from multiphase CT images by using level set method

Huimin Lu, Kentaro Saito, Joo Kooi Tan, 2017, 2017 17th International Conference on Control, Automation and Systems (ICCAS).

A Sparse Representation Based Method to Classify Pulmonary Patterns of Diffuse Lung Diseases

Rui Xu, Yasushi Hirano, Shoji Kido, 2015, Comput. Math. Methods Medicine.

Detection of abnormal candidate regions on temporal subtraction images based on DCNN

Huimin Lu, Hyoungseop Kim, Yuriko Yoshino, 2017, 2017 17th International Conference on Control, Automation and Systems (ICCAS).

Extraction of GGO regions from chest CT images using deep learning

Huimin Lu, Joo Kooi Tan, Hyoungseop Kim, 2017, 2017 17th International Conference on Control, Automation and Systems (ICCAS).

Computer-aided diagnosis for distinction between benign and malignant pulmonary nodules on chest radiographs using temporal subtraction images

Kunio Doi, Shoji Kido, Hideyuki Watanabe, 2004, CARS.

Lung Sound Classification Using Deep Neural Networks with Pre-training

Shoji Kido, Takashi Kuremoto, Ryosuke Wakamoto, 2020 .

A computerized analysis system in chest radiography: Evaluation of interstitial lung abnormalities

Hironobu Nakamura, Shinichi Tamura, Shoji Kido, 1997, Journal of Digital Imaging.

Detection and classification of lung abnormalities by use of convolutional neural network (CNN) and regions with CNN features (R-CNN)

Shoji Kido, Noriaki Hashimoto, Yasusi Hirano, 2018, 2018 International Workshop on Advanced Image Technology (IWAIT).

Investigating the Effects of Transfer Learning on ROI-based Classification of Chest CT Images: A Case Study on Diffuse Lung Diseases

Shingo Mabu, Shoji Kido, Takashi Kuremoto, 2020, J. Signal Process. Syst..

Detection of lung nodules on temporal subtraction images Using 3D sparse coding

Huimin Lu, Joo Kooi Tan, Hyoungseop Kim, 2017, 2017 17th International Conference on Control, Automation and Systems (ICCAS).

Automatic segmentation of small pulmonary nodules on multi detector-row CT images

Shoji Kido, Hayaru Shouno, Rie Tachibana, 2003, Computer Assisted Radiology and Surgery - International Congress and Exhibition.

Automatic identification of lung candidate nodules on chest CT images based on temporal subtraction images

Joo Kooi Tan, Hyoungseop Kim, Shuji Tanaka, 2014, 2014 Joint 7th International Conference on Soft Computing and Intelligent Systems (SCIS) and 15th International Symposium on Advanced Intelligent Systems (ISIS).

Introduction to deep learning: minimum essence required to launch a research

Shoji Kido, Noriyuki Tomiyama, Tomohiro Wataya, 2020, Japanese Journal of Radiology.

Automatic Classification of Large-Scale Respiratory Sound Dataset Based on Convolutional Neural Network

Shingo Mabu, Huimin Lu, Hyoungseop Kim, 2019, 2019 19th International Conference on Control, Automation and Systems (ICCAS).

Deep Convolution Neural Network with 2-Stage Transfer Learning for Medical Image Classification

Satoshi Suzuki, Shoji Kido, Hayaru Shouno, 2017 .

Pulmonary Textures Classification Using A Deep Neural Network with Appearance and Geometry Cues

Rui Xu, Yasushi Hirano, Shoji Kido, 2018, 2018 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP).

Weak supervision in convolutional neural network for semantic segmentation of diffuse lung diseases using partially annotated dataset

Shoji Kido, Noriyuki Tomiyama, Yuki Suzuki, 2020, Medical Imaging.

Classification of Idiopathic Interstitial Pneumonia on High-resolution CT Images using Counter-propagation Network

Yuki Tanaka, Shoji Kido, Hayaru Shouno, 2010, International Conference on Parallel and Distributed Processing Techniques and Applications.

Particle System Based Adaptive Sampling on Spherical Parameter Space to Improve the MDL Method for Construction of Statistical Shape Models

Rui Xu, Xiangrong Zhou, Hiroshi Fujita, 2013, Comput. Math. Methods Medicine.

Deep Learning in Textural Medical Image Analysis

Shoji Kido, Hayaru Shouno, Hidenori Sakanashi, 2019 .

Automatic Classification of Respiratory Sounds Considering Time Series Information Based on VGG16 with LSTM

Shingo Mabu, Shoji Kido, Tohru Kamiya, 2020, 2020 20th International Conference on Control, Automation and Systems (ICCAS).

Unsupervised and semi-supervised learning for efficient opacity annotation of diffuse lung diseases

Shingo Mabu, Yasushi Hirano, Shoji Kido, 2019, Other Conferences.

Classification of patterns for diffuse lung diseases in thoracic CT images by AdaBoost algorithm

Shoji Kido, Hayaru Shouno, Masayuki Kuwahara, 2009, Medical Imaging.

A pilot study to utilize a deep convolutional network to segment lungs with complex opacities

Yasushi Hirano, Shoji Kido, Xinchen Ye, 2017, 2017 Chinese Automation Congress (CAC).

Automated extraction of pleural effusion in three-dimensional thoracic CT images

Shoji Kido, Akinori Tsunomori, 2009, Medical Imaging.

Detection Method for Candidate Regions of Ground Glass Opacity on LIDC Database Using Image Features

Joo Kooi Tan, Hyoungseop Kim, Yasushi Hirano, 2016 .

A Detection Method for Liver Cancer Region Based on Faster R-CNN

Shingo Mabu, Huimin Lu, Hyoungseop Kim, 2019, 2019 19th International Conference on Control, Automation and Systems (ICCAS).

Semantic characteristics prediction of pulmonary nodule using Artificial Neural Networks

Joo Kooi Tan, Hyoungseop Kim, Yasushi Hirano, 2013, 2013 35th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC).

Transparent visualization of large-scale and complex polygon meshes using a stochastic point-based rendering method

Yen-Wei Chen, Rui Xu, Tomoko Tateyama, 2015, SIGGRAPH Asia Visualization in High Performance Computing.

Supervoxel Graph Cuts: An Effective Method for GGO Candidate Regions Extraction on CT Images

Huimin Lu, Hyoungseop Kim, Shoji Kido, 2020, IEEE Consumer Electronics Magazine.

Automatic classification of lung nodules on MDCT images with the temporal subtraction technique

Huimin Lu, Joo Kooi Tan, Hyoungseop Kim, 2017, International Journal of Computer Assisted Radiology and Surgery.

Opacity Labeling of Diffuse Lung Diseases in CT Images Using Unsupervised and Semi-supervised Learning

Shingo Mabu, Shoji Kido, Takashi Kuremoto, 2020 .

Deep Learning for Pulmonary Image Analysis: Classification, Detection, and Segmentation.

Shingo Mabu, Yasushi Hirano, Shoji Kido, 2020, Advances in experimental medicine and biology.

Unsupervised class labeling of diffuse lung diseases using frequent attribute patterns

Shingo Mabu, Yasushi Hirano, Shoji Kido, 2016, International Journal of Computer Assisted Radiology and Surgery.

Automated lesion detection methods for 2D and 3D chest X-ray images

Hiroshi Fujita, Shoji Kido, Takeshi Hara, 1999, Proceedings 10th International Conference on Image Analysis and Processing.

Deep radiomic prediction with clinical predictors of the survival in patients with rheumatoid arthritis-associated interstitial lung diseases

Hiroyuki Yoshida, Shoji Kido, Janne J. Näppi, 2018, Medical Imaging.

Determination of lung regions on chest ct images with diffuse lung diseases by use of anatomical structures and pulmonary textures

Kazuki Kozuka, Yasushi Hirano, Shoji Kido, 2015, 2015 37th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC).

Power spectral analysis of idiopathic interstitial pneumonias in high resolution CT images

Shoji Kido, Rie Tachibana, Nobuyuki Tanaka, 2004, CARS.

Deep neural network convolution (NNC) for three-class classification of diffuse lung disease opacities in high-resolution CT (HRCT): consolidation, ground-glass opacity (GGO), and normal opacity

Kenji Suzuki, Yasushi Hirano, Heber MacMahon, 2018, Medical Imaging.

Classification of Pneumoconiosis on HRCT Images for Computer-Aided Diagnosis

Rui Xu, Yasushi Hirano, Shoji Kido, 2013, IEICE Trans. Inf. Syst..

Unsupervised Content-Preserved Adaptation Network for Classification of Pulmonary Textures from Different CT Scanners

Rui Xu, Xinchen Ye, Shoji Kido, 2020, ICASSP 2020 - 2020 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP).

Automated segmentation of lungs with severe large opacities in multi-detector row CT images

Shoji Kido, 2011 .

Detection of Abnormal Regions on Temporal Subtraction Images based on CNN

Huimin Lu, Hyoungseop Kim, Shoji Kido, 2019, ICBIP '19.

GND-PCA-Based Statistical Modeling of Diaphragm Motion Extracted from 4D MRI

Yen-Wei Chen, Rui Xu, Hideaki Haneishi, 2013, Comput. Math. Methods Medicine.

Computer-Aided Diagnosis of Computational Anatomical Model and Application of Computer-Aided Autopsy Imaging

Rui Xu, Yasushi Hirano, Shoji Kido, 2011 .

3D-CNN with residual sub-blocks for automatic detection of lung nodules from temporal subtraction images

Huimin Lu, Yuriko Yoshino, Shoji Kido, 2020, 2020 International Conference on Artificial Intelligence in Information and Communication (ICAIIC).

Classification of Diffuse Lung Disease Patterns on High-Resolution Computed Tomography by a Bag of Words Approach

Rui Xu, Yasushi Hirano, Shoji Kido, 2011, MICCAI.

Automatic segmentation of pulmonary nodules on CT images by use of NCI lung image database consortium

Shoji Kido, Rie Tachibana, S. Kido, 2006, SPIE Medical Imaging.

Opacity annotation of diffuse lung diseases using deep convolutional neural network with multi-channel information

Shingo Mabu, Yasushi Hirano, Shoji Kido, 2018, Medical Imaging.

Construction of a Supporting System for Portable Terminal Devices using Middle-ware Server to Communicate with DICOM Service

Shoji Kido, Yuichi Seto, Hayaru Shono, 2008 .

Extraction of GGO Candidate Regions on Thoracic CT Images using SuperVoxel-Based Graph Cuts for Healthcare Systems

Huimin Lu, Yujie Li, Joo Kooi Tan, 2018, Mob. Networks Appl..

Development of image viewer for analyzing of temporal subtraction from chest CT images

Joo Kooi Tan, Hyoungseop Kim, Yasushi Hirano, 2015, 2015 15th International Conference on Control, Automation and Systems (ICCAS).

J022023 A method to extract bronchus region from CT images using cavity enhancement filter and region growing algorithm

Rui Xu, Yasushi Hirano, Shoji Kido, 2011 .

Analysis of the effects of transfer learning on opacity classification of diffuse lung diseases using convolutional neural network

Shingo Mabu, Yasushi Hirano, Shoji Kido, 2019, Other Conferences.

A Computer-aided Diagnosis Method for Classification of Pneumoconiosis Patterns on HRCT Images

Rui Xu, Wei Zhao, Yasushi Hirano, 2012 .

2703 Application of Model Order Reduction Method to Global/Local Dynamic Analysis

Naoki Takano, Shoji Kido, Atushi Sando, 2007 .

A Bag-of-Features Approach to Classify Six Types of Pulmonary Textures on High-Resolution Computed Tomography

Rui Xu, Yasushi Hirano, Shoji Kido, 2013, IEICE Trans. Inf. Syst..

Interactive semiautomatic segmentation tool of human organs using three-dimensional CT images

Shoji Kido, 2011 .

Segmentation of lung region from chest x-ray images using U-net

Yasushi Hirano, Shoji Kido, Keigo Furutani, 2019, Other Conferences.

Classification of diffuse lung diseases patterns by a sparse representation based method on HRCT images

Rui Xu, Yasushi Hirano, Shoji Kido, 2013, 2013 35th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC).

Analysis of Idiopathic interstitial Pneumonia by Self Organization Map on High-Resolution Computed Tomography Images

Shoji Kido, Hayaru Shouno, Yoshiharu Goto, 2007, PDPTA.

Automatic detection of GGO regions on CT images in LIDC dataset based on statistical features

Joo Kooi Tan, Hyoungseop Kim, Yasushi Hirano, 2014, 2014 Joint 7th International Conference on Soft Computing and Intelligent Systems (SCIS) and 15th International Symposium on Advanced Intelligent Systems (ISIS).

Low-cost soft-copy display accuracy in the detection of pulmonary nodules by single-exposure dual-energy subtraction: Comparison with hard-copy viewing

Shoji Kido, Chikazumi Kuroda, Keiko Kuriyama, 2000, Journal of digital imaging.

Evaluation of abnormal respiratory sound "crackle" using time-expanded waveform and FFT analysis

Zhongwei Jiang, Shoji Kido, Naofumi Matsunaga, 2003 .

Classification of respiratory sounds using improved convolutional recurrent neural network

Shingo Mabu, Shoji Kido, Tohru Kamiya, 2021, Comput. Electr. Eng..

Optimizing early cancer diagnosis and detection using a temporal subtraction technique

Shoji Kido, Tohru Kamiya, Noriaki Miyake, 2021 .

Detail- Revealing Deep Low-Dose CT Reconstruction

Shoji Kido, Noriyuki Tomiyama, Xinchen Ye, 2021, 2020 25th International Conference on Pattern Recognition (ICPR).

Classification of lung cancer into adenocarcinoma and squamous cell carcinoma, and visualization of the grounds of classification

Yasushi Hirano, Shoji Kido, Erena Ise, 2021, Other Conferences.

BG-Net: Boundary-Guided Network for Lung Segmentation on Clinical CT Images

Yi Wang, Yen-Wei Chen, Shoji Kido, 2021, 2020 25th International Conference on Pattern Recognition (ICPR).

Semi-supervised CycleGAN for domain transformation of chest CT images and its application to opacity classification of diffuse lung diseases

Shingo Mabu, Shoji Kido, Takashi Kuremoto, 2021, International Journal of Computer Assisted Radiology and Surgery.

Lung region extraction from CT images of diffuse lung disease cases by deep learning

Yasushi Hirano, Shoji Kido, Daisuke Kurata, 2021, Other Conferences.

Segmentation of liver tumors in multiphase computed tomography images using hybrid method

Shingo Mabu, Shoji Kido, Tohru Kamiya, 2022, Computers & electrical engineering.

Unsupervised Detection of Pulmonary Opacities for Computer-Aided Diagnosis of COVID-19 on CT Images

Yen-Wei Chen, Shoji Kido, Hongjie Hu, 2021, 2020 25th International Conference on Pattern Recognition (ICPR).

A 3-D Non-Rigid Warping Method Based on Free Formed Deformation for Temporal Subtraction on Thoracic MDCT Images

Yuriko Yoshino, Shoji Kido, Hyoungseop Kim, 2016 .

Texture Analysis of Hepatic Fibrosis in CT Images

Yasushi Hirano, Shoji Kido, 2013 .

Su1566 Computer-Assisted Automatic Identification System for Colorectal Narrow Band Imaging (NBI) Classification

Hisao Tajiri, Shoji Kido, Takeshi Nakajima, 2011 .

Effectiveness of computer-aided diagnosis of colorectal lesions using novel software for magnifying narrow-band imaging: a pilot study

Kazuki Sumiyama, Hisao Tajiri, Shoji Kido, 2017, Endoscopy International Open.

Crackle analysis for chest auscultation and comparison with high-resolution CT findings.

Zhongwei Jiang, Shoji Kido, Naofumi Matsunaga, 2003, Radiation medicine.

Detection of simulated pulmonary nodules by single-exposure dual-energy computed radiography of the chest: effect of a computer-aided diagnosis system (Part 2).

Shoji Kido, Kazuo Shimura, Chikazumi Kuroda, 2002, European journal of radiology.

Texture analysis on 18F-FDG PET/CT images to differentiate malignant and benign bone and soft-tissue lesions

Satoshi Tanaka, Yasushi Hirano, Shoji Kido, 2014, Annals of Nuclear Medicine.

Fractal Analysis of Internal and Peripheral Textures of Small Peripheral Bronchogenic Carcinomas in Thin-section Computed Tomography: Comparison of Bronchioloalveolar Cell Carcinomas With Nonbronchioloalveolar Cell Carcinomas

Shoji Kido, Chikazumi Kuroda, Keiko Kuriyama, 2003, Journal of computer assisted tomography.

Computerized detection of pulmonary nodules by single-exposure dual-energy computed radiography of the chest (part 1).

Shoji Kido, Kazuo Shimura, Hironobu Nakamura, 2002, European Journal of Radiology.

Fractal Analysis of Small Peripheral Pulmonary Nodules in Thin-section CT: Evaluation of the Lung-nodule Interfaces

Shoji Kido, Chikazumi Kuroda, Keiko Kuriyama, 2002, Journal of computer assisted tomography.