Automatic detection of vertebral number abnormalities in body CT images

Author:

Hanaoka ShouheiORCID,Nakano Yoshiyasu,Nemoto Mitsutaka,Nomura Yukihiro,Takenaga Tomomi,Miki Soichiro,Yoshikawa Takeharu,Hayashi Naoto,Masutani Yoshitaka,Shimizu Akinobu

Funder

JSPS Grants-in-Aid for Scientific Research KAKENHI

Publisher

Springer Science and Business Media LLC

Subject

Health Informatics,Radiology Nuclear Medicine and imaging,General Medicine,Surgery,Computer Graphics and Computer-Aided Design,Computer Science Applications,Computer Vision and Pattern Recognition,Biomedical Engineering

Cited by 5 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. Lumbosacral transitional vertebrae in children and adolescents (literature review, illustrated with clinical observations);Genij Ortopedii;2024-04-22

2. Comparative Study and Detection of Spinal Deformities using Supervised Machine Learning Algorithms;2022 International Conference on Computing, Communication, Security and Intelligent Systems (IC3SIS);2022-06-23

3. VerSe: A Vertebrae labelling and segmentation benchmark for multi-detector CT images;Medical Image Analysis;2021-10

4. Automatic Path Planning for Navigated Pedicle Screw Surgery Based on Deep Neural Network;2019 WRC Symposium on Advanced Robotics and Automation (WRC SARA);2019-08

5. Assessment of optimal deep learning configuration for vertebrae segmentation from CT images;Medical Imaging 2019: Imaging Informatics for Healthcare, Research, and Applications;2019-03-15

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