Bimodal Network Architectures for Automatic Generation of Image Annotation from Text
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Densely Connected Convolutional Networks
Huang, G., Liu, Z., Van Der Maaten, L., & Weinberger, K. Q. (2017) · 2017 IEEE Conference on Computer Vision and Pattern Recognition (CVPR) · doi:10.1109/cvpr.2017.243 · Cited by 48,566 · see citing works
Glove: Global Vectors for Word Representation
Pennington, J., Socher, R., & Manning, C. (2014) · Proceedings of the 2014 Conference on Empirical Methods in Natural Language Processing (EMNLP) · doi:10.3115/v1/d14-1162 · Cited by 34,071 · see citing works
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CheXNet: Radiologist-Level Pneumonia Detection on Chest X-Rays with Deep LearningPreprint
Rajpurkar, P., Irvin, J., Zhu, K., Yang, B., Mehta, H., Duan, T., Ding, D. Y., Bagul, A., Langlotz, C. P., Shpanskaya, K. S., et al. (2017) · arXiv (Cornell University) · doi:10.48550/arxiv.1711.05225 · Cited by 2,283 · see citing works
Preparing a collection of radiology examinations for distribution and retrieval
Demner-Fushman, D., Kohli, M. D., Rosenman, M. B., Shooshan, S. E., Rodriguez, L., Antani, S., Thoma, G. R., & McDonald, C. J. (2016) · Journal of the American Medical Informatics Association · doi:10.1093/jamia/ocv080 · Cited by 1,164 · see citing works
Wang, X., Peng, Y., Lü, L., Lu, Z., & Summers, R. M. (2018) · IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings - IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings · doi:10.1109/cvpr.2018.00943 · Cited by 574 · see citing works
Can Masses of Non-Experts Train Highly Accurate Image Classifiers?
Maier‐Hein, L., Mersmann, S., Kondermann, D., Bodenstedt, S., Sanchez, A., Stock, C., Kenngott, H., Eisenmann, M., & Speidel, S. (2014) · Lecture notes in computer science · doi:10.1007/978-3-319-10470-6_55 · Cited by 94 · see citing works
Ground truth generation in medical imaging
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A Cross-Modality Neural Network Transform for Semi-automatic Medical Image Annotation
Moradi, M., Guo, Y., Gur, Y., et al. (2016) · Lecture notes in computer science · doi:10.1007/978-3-319-46723-8_35 · Cited by 30 · see citing works
Self-citationImage segmentation in Twenty Questions
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An overview of deep learning in medical imaging focusing on MRI
Lundervold, A. S., & Lundervold, A. (2019) · Zeitschrift für Medizinische Physik · doi:10.1016/j.zemedi.2018.11.002 · Cited by 2,058 · see citing works
A Pilot Study in Surveying Clinical Judgments to Evaluate Radiology Report Generation
Boag, W., Kané, H., Rawat, S., Wei, J., & Goehler, A. (2021) · Proceedings of the 2021 ACM Conference on Fairness, Accountability, and Transparency · doi:10.1145/3442188.3445909 · Cited by 5 · see citing works
- Authors
- Moradi, M., Madani, A., Gur, Y., Guo, Y., & Syeda-Mahmood, T.
- Affiliations
- IBM Research - Almaden (US)
- Corresponding author
- Moradi, Mehdi
- Venue
- Lecture Notes in Computer Science
- Publisher
- Springer International Publishing
- Published
- 2018
- Pages
- 449-456
- ISSN
- 0302-9743 (ISSN-L)
- 1611-3349
- OpenAlex
- W2891266422
- Cited by
- 20
- References
- 11
- Citations by year
- 2024: 1 · 2022: 3 · 2021: 7 · 2020: 5 · 2019: 2 · 2018: 2
- FWCI
- 1.21
- Type
- conference paper
- Language
- en
- Open access
- green
- arxiv.org
- Licence
- Locations
- Lecture notes in computer science (publishedVersion)
- arXiv (Cornell University) (submittedVersion)
- arXiv (Cornell University)
- Topics
- Physical Sciences › Computer Science › Computer Vision and Pattern Recognition › Multimodal Machine Learning Applications
- Physical Sciences › Computer Science › Computer Vision and Pattern Recognition › Image Retrieval and Classification Techniques
- Physical Sciences › Computer Science › Computer Vision and Pattern Recognition › Medical Image Segmentation Techniques
- Keywords
- automatic image annotation, region of interest localization, chest X-ray images, clinical reports, medical image annotation
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Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
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