Inference-specific learning for improved medical image segmentation.

Journal: Medical physics
Published Date: May 12, 2025

Abstract

BACKGROUND: Deep learning networks map input data to output predictions by fitting network parameters using training data. However, applying a trained network to new, unseen inference data resembles an interpolation process, which may lead to inaccurate predictions if the training and inference data distributions differ significantly.

Authors

  • Yizheng Chen
    Department of Radiation Oncology, Stanford University, Stanford, 94305, USA.
  • Sheng Liu
    Medical School, Xizang Minzu University, Xianyang, People's Republic of China.
  • Mingjie Li
    Key Laboratory of Ministry of Education for Genetics, Breeding and Multiple Utilization of Crops, College of Agriculture, Fujian Agriculture and Forestry University, Fuzhou, China.
  • Bin Han
    2 Department of Radiation Oncology, Stanford University, Stanford, CA, USA.
  • Lei Xing
    Department of Radiation Oncology, Stanford University, CA, USA.

Keywords

No keywords available for this article.

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