Clinical Applications of Artificial Intelligence in Medical Imaging and Image Processing—A Review-Reference-Cited by-同舟云学术

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Clinical Applications of Artificial Intelligence in Medical Imaging and Image Processing—A Review

Published:2024-05-14 Issue:10 Volume:16 Page:1870
ISSN:2072-6694
Container-title:Cancers
language:en
Short-container-title:Cancers

Author:

Obuchowicz Rafał¹^ORCID,Strzelecki Michał²^ORCID,Piórkowski Adam³^ORCID

Affiliation:

1. Department of Diagnostic Imaging, Jagiellonian University Medical College, 31-008 Krakow, Poland

2. Institute of Electronics, Lodz University of Technology, 93-590 Lodz, Poland

3. Department of Biocybernetics and Biomedical Engineering, AGH University of Krakow, 30-059 Krakow, Poland

Abstract

Artificial intelligence (AI) is currently becoming a leading field in data processing [...]

Publisher

MDPI AG

Link

https://www.mdpi.com/2072-6694/16/10/1870/pdf

Reference40 articles.

1. Ozkara, B., Chen, M., Federau, C., Karabacak, M., Briere, T., Li, J., and Wintermark, M. (2023). Deep Learning for Detecting Brain Metastases on MRI: A Systematic Review and Meta-Analysis. Cancers, 15.

2. Rahmanuddin, S., Jamil, A., Chaudhry, A., Seto, T., Brase, J., Motarjem, P., Khan, M., Tomasetti, C., Farwa, U., and Boswell, W. (2023). COVID and Cancer: A Complete 3D Advanced Radiological CT-Based Analysis to Predict the Outcome. Cancers, 15.

3. Nam, H., Park, S., Ho, J., Park, S., Cho, J., and Lee, Y. (2023). Key-Point Detection Algorithm of Deep Learning Can Predict Lower Limb Alignment with Simple Knee Radiographs. J. Clin. Med., 12.

4. Avoiding Tissue Overlap in 2D Images: Single-Slice DBT Classification Using Convolutional Neural Networks;Mendes;Tomography,2023

5. Rodrigues, N., Silva, S., Vanneschi, L., and Papanikolaou, N. (2023). A Comparative Study of Automated Deep Learning Segmentation Models for Prostate MRI. Cancers, 15.

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