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April 19, 2026Journal of Medical Imaging0 citationsOpen Access

Parameter-efficient deep-learning-based model for segmentation with radiomic feature extraction

DSDaniel SleimanNANavchetan Awasthi

Key Points

  • The research aims to evaluate the effectiveness of parameter-efficient deep learning models for tumor segmentation in DCE-MRI images.
  • Developed a deep learning model focusing on parameter efficiency for image segmentation.
  • Utilized DCE-MRI imaging for tumor analysis.
  • Implemented radiomic feature extraction during the segmentation process.
  • Achieved competitive performance in tumor segmentation compared to more complex models.
  • Showed improvements in processing efficiency without significant loss in accuracy.

Abstract

Our results demonstrate that parameter-efficient models can achieve competitive performance in DCE-MRI tumor segmentation.

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Cite This Study

Sleiman et al. (2026) studied this question.

synapsesocial.com/papers/69e470a4010ef96374d8d7f6https://doi.org/10.1117/1.jmi.13.2.024502
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