Micro-nodule analysis by severity of pneumoconiosis using 3D CT images

被引:1
|
作者
Hahsimoto, Y. [1 ]
Matsuhiro, M. [2 ]
Suzuki, H. [1 ]
Kawata, Y. [1 ]
Ohtsuka, Y. [3 ]
Kishimoto, T. [4 ]
Ashizawa, K. [5 ]
Niki, N. [6 ]
机构
[1] Tokushima Univ, Tokushima, Japan
[2] Suzuka Univ Med Sci, Suzuka, Japan
[3] Hokkaido Chuo Rosai Hosp, Iwamizawa, Hokkaido, Japan
[4] Okayama Rosai Hosp, Okayama, Japan
[5] Nagasaki Univ, Nagasaki, Japan
[6] Med Sci Inst Inc, Tokushima, Japan
来源
MEDICAL IMAGING 2023 | 2023年 / 12469卷
关键词
pneumoconiosis; micro nodule; computed tomography; quantitative diagnostic criteria;
D O I
10.1117/12.2653766
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
Pneumoconiosis is an occupational respiratory disease caused by inhaling dust into the lungs. In Japan, 240,000 people undergo pneumoconiosis screening every year. X-rays are used worldwide to classify the severity of pneumoconiosis. It is important to distinguish between type 0/1 and type 1/0, which are eligible for recognition of occupational injury. CT images are expected to provide more accurate diagnosis because they can be confirmed in three dimensions compared to X-rays. We extract micro-nodules from 3D CT images for each severity of pneumoconiosis, and analyze and evaluate the number, size, position and CT values of micro-nodules in each lung lobe.
引用
收藏
页数:6
相关论文
共 50 条
  • [41] 3D image fusion using MRI/CT and infrared images
    Fusão 3D de imagens de MRI/CT e termografia
    2013, Sociedade Brasileira de Engenharia Biomedica, Caixa Postal 68510, Rio de Janeiro, RJ, 21941-972, Brazil (29):
  • [42] 3D Registration for PET/CT Images Using Genetic Algorithm
    Pratumgul, Weeragul
    Phramala, Sucheera
    Chamnongthai, Kosin
    PROCEEDING OF THE 10TH INTERNATIONAL CONFERENCE ON INTELLIGENT TECHNOLOGIES, 2009, : 598 - 600
  • [43] 3D micro-CT analysis of cancellous bone architecture
    Rossi, M
    Casali, F
    Romani, D
    Carabini, ML
    DEVELOPMENTS IN X-RAY TOMOGRAPHY III, 2002, 4503 : 349 - 358
  • [44] Application of cone beam CT 3D images to cephalometric analysis
    Ogawa, Naoki
    Miyazaki, Yoshikazu
    Kubota, Masato
    Huang, John C.
    Miller, Arthur J.
    Maki, Koutaro
    ORTHODONTIC WAVES, 2010, 26 (04): : 415 - 454
  • [45] Hierarchical approach for pulmonary-nodule identification from CT images using YOLO model and a 3D neural network classifier
    Yashar Ahmadyar
    Alireza Kamali-Asl
    Hossein Arabi
    Rezvan Samimi
    Habib Zaidi
    Radiological Physics and Technology, 2024, 17 : 124 - 134
  • [46] Hierarchical approach for pulmonary-nodule identification from CT images using YOLO model and a 3D neural network classifier
    Ahmadyar, Yashar
    Kamali-Asl, Alireza
    Arabi, Hossein
    Samimi, Rezvan
    Zaidi, Habib
    RADIOLOGICAL PHYSICS AND TECHNOLOGY, 2024, 17 (01) : 124 - 134
  • [47] Classification of micro-CT images using 3D characterization of bone canal patters in human osteogenesis imperfecta
    Abidin, Anas Z.
    Jameson, John
    Molthen, Robert
    Wismueller, Axel
    MEDICAL IMAGING 2017: COMPUTER-AIDED DIAGNOSIS, 2017, 10134
  • [48] A 3D Multi-scale Block LBP Filter for Lung Nodule Enhancement Based on the CT Images
    Xu, Fan
    Zhang, Wen-Jing
    Li, Xin-Yue
    Xiao, Hu
    Peng, Shao-Hu
    Nam, Hyun-Do
    Zhang, Mian-Feng
    2016 9TH INTERNATIONAL CONGRESS ON IMAGE AND SIGNAL PROCESSING, BIOMEDICAL ENGINEERING AND INFORMATICS (CISP-BMEI 2016), 2016, : 1376 - 1380
  • [49] A Novel Modeling Method Based on 3D CT Images for Dynamics Analysis of The Micro-Hemispherical Resonator Gyroscope
    Meng, Min
    Yang, Kai
    Su, Wei
    Dong, Shengwei
    Zhang, Hao
    Zhang, Jie
    Li, He
    Wang, Xi
    2022 9TH IEEE INTERNATIONAL SYMPOSIUM ON INERTIAL SENSORS AND SYSTEMS (IEEE INERTIAL 2022), 2022,
  • [50] Identification of high-risk population of pneumoconiosis using deep learning segmentation of lung 3D images and radiomics texture analysis
    Liu, Yafeng
    Wu, Jing
    Zhou, Jiawei
    Guo, Jianqiang
    Liang, Chao
    Xing, Yingru
    Wang, Zhongyu
    Chen, Lijuan
    Ding, Yan
    Ren, Dingfei
    Bai, Ying
    Hu, Dong
    COMPUTER METHODS AND PROGRAMS IN BIOMEDICINE, 2024, 244