Deep Learning Applications in Chest Radiography and Computed Tomography-Reference-Cited by-同舟云学术

Deep Learning Applications in Chest Radiography and Computed Tomography

Published:2019-03 Issue:2 Volume:34 Page:75-85
ISSN:0883-5993
Container-title:Journal of Thoracic Imaging
language:en
Short-container-title:

Author:

Lee Sang Min,Seo Joon Beom,Yun Jihye,Cho Young-Hoon,Vogel-Claussen Jens,Schiebler Mark L.,Gefter Warren B.,van Beek Edwin J.R.,Goo Jin Mo,Lee Kyung Soo,Hatabu Hiroto,Gee James,Kim Namkug

Publisher

Ovid Technologies (Wolters Kluwer Health)

Subject

Pulmonary and Respiratory Medicine,Radiology, Nuclear Medicine and imaging

Reference59 articles.

1. Deep learning;LeCun;Nature,2015

2. Imagenet classification with deep convolutional neural networks;Krizhevsky;Adv Neural Inf Process Syst,2012

3. Deep neural networks for acoustic modeling in speech recognition: the shared views of four research groups;Hinton;IEEE Signal Proc Mag,2012

4. Development and validation of a deep learning algorithm for detection of diabetic retinopathy in retinal fundus photographs;Gulshan;JAMA,2016

5. Dermatologist-level classification of skin cancer with deep neural networks;Esteva;Nature,2017

Cited by 100 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. 2D organic-inorganic lead perovskite: Advancing X-ray detection capability;Journal of Alloys and Compounds;2024-09

2. Imaging of Acute Pulmonary Embolism;Radiologic Clinics of North America;2024-09

3. Medical imaging: A Critical Review on X-ray Imaging for the Detection of Infection;Biomedical Materials & Devices;2024-07-15

4. Modern imaging of acute pulmonary embolism;Thrombosis Research;2024-06

5. Assessment of inspiration and technical quality in anteroposterior thoracic radiographs using machine learning;Radiography;2024-01