Literature DB >> 26002240

Pitfalls in chest radiographic interpretation: blind spots.

Patricia M de Groot1, Brett W Carter2, Gerald F Abbott3, Carol C Wu2.   

Abstract

Mesh：

Year:  2015        PMID： 26002240     DOI： 10.1053/j.ro.2015.01.008

Source DB:  PubMed          Journal:  Semin Roentgenol        ISSN： 0037-198X            Impact factor:   0.800


× No keyword cloud information.
  8 in total

1.  AI-based improvement in lung cancer detection on chest radiographs: results of a multi-reader study in NLST dataset.

Authors:  Hyunsuk Yoo; Sang Hyup Lee; Chiara Daniela Arru; Ruhani Doda Khera; Ramandeep Singh; Sean Siebert; Dohoon Kim; Yuna Lee; Ju Hyun Park; Hye Joung Eom; Subba R Digumarthy; Mannudeep K Kalra
Journal:  Eur Radiol       Date:  2021-06-04       Impact factor: 5.315

2.  Undetected Lung Cancer at Posteroanterior Chest Radiography: Potential Role of a Deep Learning-based Detection Algorithm.

Authors:  Ju Gang Nam; Eui Jin Hwang; Da Som Kim; Seung-Jin Yoo; Hyewon Choi; Jin Mo Goo; Chang Min Park
Journal:  Radiol Cardiothorac Imaging       Date:  2020-12-10

3.  Validation of deep learning-based computer-aided detection software use for interpretation of pulmonary abnormalities on chest radiographs and examination of factors that influence readers' performance and final diagnosis.

Authors:  Naoki Toda; Masahiro Hashimoto; Yu Iwabuchi; Misa Nagasaka; Ryo Takeshita; Minoru Yamada; Yoshitake Yamada; Masahiro Jinzaki
Journal:  Jpn J Radiol       Date:  2022-09-19       Impact factor: 2.701

4.  Bone Suppression on Chest Radiographs for Pulmonary Nodule Detection: Comparison between a Generative Adversarial Network and Dual-Energy Subtraction.

Authors:  Kyungsoo Bae; Dong Yul Oh; Il Dong Yun; Kyung Nyeo Jeon
Journal:  Korean J Radiol       Date:  2022-01       Impact factor: 3.500

5.  Association of Artificial Intelligence-Aided Chest Radiograph Interpretation With Reader Performance and Efficiency.

Authors:  Jong Seok Ahn; Shadi Ebrahimian; Shaunagh McDermott; Sanghyup Lee; Laura Naccarato; John F Di Capua; Markus Y Wu; Eric W Zhang; Victorine Muse; Benjamin Miller; Farid Sabzalipour; Bernardo C Bizzo; Keith J Dreyer; Parisa Kaviani; Subba R Digumarthy; Mannudeep K Kalra
Journal:  JAMA Netw Open       Date:  2022-08-01

Review 6.  Missed Lung Cancers on Chest Radiograph: An Illustrative Review of Common Blind Spots on Chest Radiograph with Emphasis on Various Radiologic Presentations of Lung Cancers.

Authors:  Goun Choi; Bo Da Nam; Jung Hwa Hwang; Ki-Up Kim; Hyun Jo Kim; Dong Won Kim
Journal:  Taehan Yongsang Uihakhoe Chi       Date:  2020-02-18

7.  Performance and educational training of radiographers in lung nodule or mass detection: Retrospective comparison with different deep learning algorithms.

Authors:  Pai-Hsueh Teng; Chia-Hao Liang; Yun Lin; Angel Alberich-Bayarri; Rafael López González; Pin-Wei Li; Yu-Hsin Weng; Yi-Ting Chen; Chih-Hsien Lin; Kang-Ju Chou; Yao-Shen Chen; Fu-Zong Wu
Journal:  Medicine (Baltimore)       Date:  2021-06-11       Impact factor: 1.817

8.  Lung nodule detection in chest X-rays using synthetic ground-truth data comparing CNN-based diagnosis to human performance.

Authors:  Manuel Schultheiss; Philipp Schmette; Jannis Bodden; Juliane Aichele; Christina Müller-Leisse; Felix G Gassert; Florian T Gassert; Joshua F Gawlitza; Felix C Hofmann; Daniel Sasse; Claudio E von Schacky; Sebastian Ziegelmayer; Fabio De Marco; Bernhard Renger; Marcus R Makowski; Franz Pfeiffer; Daniela Pfeiffer
Journal:  Sci Rep       Date:  2021-08-04       Impact factor: 4.379
  8 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.