Literature DB >> 32317574

Machine Learning/Deep Neuronal Network: Routine Application in Chest Computed Tomography and Workflow Considerations.

Andreas M Fischer1, Basel Yacoub1, Rock H Savage1, John D Martinez1, Julian L Wichmann2, Pooyan Sahbaee2, Sasa Grbic2, Akos Varga-Szemes1, U Joseph Schoepf1.   

Abstract

The constantly increasing number of computed tomography (CT) examinations poses major challenges for radiologists. In this article, the additional benefits and potential of an artificial intelligence (AI) analysis platform for chest CT examinations in routine clinical practice will be examined. Specific application examples include AI-based, fully automatic lung segmentation with emphysema quantification, aortic measurements, detection of pulmonary nodules, and bone mineral density measurement. This contribution aims to appraise this AI-based application for value-added diagnosis during routine chest CT examinations and explore future development perspectives.

Entities:  

Year:  2020        PMID： 32317574     DOI： 10.1097/RTI.0000000000000498

Source DB:  PubMed          Journal:  J Thorac Imaging        ISSN： 0883-5993            Impact factor:   3.000


  6 in total

1.  Deep Neural Networks for Dental Implant System Classification.

Authors:  Shintaro Sukegawa; Kazumasa Yoshii; Takeshi Hara; Katsusuke Yamashita; Keisuke Nakano; Norio Yamamoto; Hitoshi Nagatsuka; Yoshihiko Furuki
Journal:  Biomolecules       Date:  2020-07-01

2.  Automated detection of lung nodules and coronary artery calcium using artificial intelligence on low-dose CT scans for lung cancer screening: accuracy and prognostic value.

Authors:  Jordan Chamberlin; Madison R Kocher; Jeffrey Waltz; Madalyn Snoddy; Natalie F C Stringer; Joseph Stephenson; Pooyan Sahbaee; Puneet Sharma; Saikiran Rapaka; U Joseph Schoepf; Andres F Abadia; Jonathan Sperl; Phillip Hoelzer; Megan Mercer; Nayana Somayaji; Gilberto Aquino; Jeremy R Burt
Journal:  BMC Med       Date:  2021-03-04       Impact factor: 8.775

3.  AI Lung Segmentation and Perfusion Analysis of Dual-Energy CT Can Help to Distinguish COVID-19 Infiltrates from Visually Similar Immunotherapy-Related Pneumonitis Findings and Can Optimize Radiological Workflows.

Authors:  Andreas S Brendlin; Markus Mader; Sebastian Faby; Bernhard Schmidt; Ahmed E Othman; Sebastian Gassenmaier; Konstantin Nikolaou; Saif Afat
Journal:  Tomography       Date:  2021-12-23

Review 4.  A Review of Posteromedial Lesions of the Chest Wall: What Should a Chest Radiologist Know?

Authors:  Sara Haseli; Bahar Mansoori; Mehrzad Shafiei; Firoozeh Shomal Zadeh; Hamid Chalian; Parisa Khoshpouri; David Yousem; Majid Chalian
Journal:  Diagnostics (Basel)       Date:  2022-01-25

5.  Tumor burden of lung metastases at initial staging in breast cancer patients detected by artificial intelligence as a prognostic tool for precision medicine.

Authors:  Madison R Kocher; Jordan Chamberlin; Jeffrey Waltz; Madalyn Snoddy; Natalie Stringer; Joseph Stephenson; Jacob Kahn; Megan Mercer; Dhiraj Baruah; Gilberto Aquino; Ismail Kabakus; Philipp Hoelzer; Pooyan Sahbaee; U Joseph Schoepf; Jeremy R Burt
Journal:  Heliyon       Date:  2022-02-15

6.  Artificial Intelligence Applied to Chest X-ray for Differential Diagnosis of COVID-19 Pneumonia.

Authors:  Christian Salvatore; Matteo Interlenghi; Caterina B Monti; Davide Ippolito; Davide Capra; Andrea Cozzi; Simone Schiaffino; Annalisa Polidori; Davide Gandola; Marco Alì; Isabella Castiglioni; Cristina Messa; Francesco Sardanelli
Journal:  Diagnostics (Basel)       Date:  2021-03-16
  6 in total

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