Who Cited It

GAN-based synthetic medical image augmentation for increased CNN performance in liver lesion classification

2018 · Neurocomputing · 1,976 citations · 1 from inside this corpus

Maayan Frid-Adar, Idit Diamant, Eyal Klang, Michal Marianne Amitai, Jacob Goldberger, Hayit Greenspan

No abstract in the source record.

GAN-based synthetic medical image augmentation for increased CNN performance in liver les… (2018)GAN-based synthetic medical i…Adam: A Method for Stochastic Optimization (2014)Adam: A Method for Stochastic…Dropout: a simple way to prevent neural networks from overfitting (2014)Dropout: a simple way to prev…Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Sh… (2024)Batch Normalization: Accelera…A survey on deep learning in medical image analysis (2017)A survey on deep learning in …Guest Editorial Deep Learning in Medical Imaging: Overview and Future Promise of an Excit… (2016)Guest Editorial Deep Learning…Generative adversarial network in medical imaging: A review (2019)Generative adversarial networ…
6 of 6 neighbouring works in this corpus. Blue is what this paper cites; orange is what cites it, and a dashed line is one neighbour citing another. Only the largest labels are drawn — every node carries its full title on hover.
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What this paper cites, inside the corpus

PaperYearCited
Adam: A Method for Stochastic Optimization201484,698
Dropout: a simple way to prevent neural networks from overfitting201434,236
Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Sh…202415,663
A survey on deep learning in medical image analysis201715,110
Guest Editorial Deep Learning in Medical Imaging: Overview and Future Promise of an Excit…20161,748

What cites it, inside the corpus

PaperYearCited
Generative adversarial network in medical imaging: A review20191,902

Links

DOI · Open access copy · OpenAlex record

Topics

AI in cancer detectionComputer Science
COVID-19 diagnosis using AIMedicine
Generative Adversarial Networks and Image SynthesisComputer Science

Is this record sound?

complete

Nothing in this record contradicts itself and no field we check is missing.

  • supports6 author record(s) attached.
  • supports57 reference(s) recorded.
  • supportsThe DOI's year agrees with the publication year.
  • supportsA title is present.

Provenance

Everything above was read from one stored OpenAlex payload, fetched 2026-09-04T03:58:51+00:00.

sha256 6e314d9c6052d1ed…