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ZENODO
Dataset . 2018
License: CC BY
Data sources: Datacite
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ZENODO
Dataset . 2018
License: CC BY
Data sources: Datacite
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Dataset Of B-Mode Fatty Liver Ultrasound Images

Authors: Byra, Michal; Styczynski, Grzegorz; Szmigielski, Cezary; Kalinowski, Piotr; Michalowski, Lukasz; Paluszkiewicz, Rafal; Ziarkiewicz-Wroblewska, Bogna; +3 Authors

Dataset Of B-Mode Fatty Liver Ultrasound Images

Abstract

The dataset used and described in: M. Byra, G. Styczynski, C. Szmigielski, P. Kalinowski. Ł. Michałowski4. R. Paluszkiewicz. B. Ziarkiewicz-Wróblewska, K. Zieniewicz. P. Sobieraj, A. Nowicki. Transfer learning with deep convolutional neural network for liver steatosis assessment in ultrasound images. International Journal of Computer Assisted Radiology and Surgery, 2018. DOI: 10.1007/s11548-018-1843-2. Please refer to the above work if you use the dataset in your research. Contact: Michal Byra Department of Ultrasound Institute of Fundamental Technological Research Polish Academy of Sciences, Warsaw, Poland mbyra@ippt.pan.pl byra.michal@gmail.com

{"references": ["M. Byra, G. Styczynski, C. Szmigielski, P. Kalinowski. \u0141. Micha\u0142owski4. R. Paluszkiewicz. B. Ziarkiewicz-Wr\u00f3blewska,\u00a0K. Zieniewicz. P. Sobieraj, A. Nowicki. Transfer learning with deep convolutional neural network for liver steatosis assessment in ultrasound images.\u00a0International Journal of Computer Assisted Radiology and Surgery, 2018.\u00a0DOI: 10.1007/s11548-018-1843-2"]}

Keywords

Nonalcoholic fatty liver disease, Ultrasound imaging, Dataset

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This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
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