most citedSurrogate Supervision for Medical Image Analysis: Effective Deep Learning From Limited Quantities of Labeled Data

12 citations

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2 papers

eess.IV2019

ErrorNet: Learning error representations from limited data to improve vascular segmentation

Nima Tajbakhsh, Brian Lai, Shilpa Ananth +1

Deep convolutional neural networks have proved effective in segmenting lesions and anatomies in various medical imaging modalities. However, in the presence of small sample size an…

cs.CV2019★ 12 cited

Surrogate Supervision for Medical Image Analysis: Effective Deep Learning From Limited Quantities of Labeled Data

Nima Tajbakhsh, Yufei Hu, Junli Cao +6

We investigate the effectiveness of a simple solution to the common problem of deep learning in medical image analysis with limited quantities of labeled training data. The underly…