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Deep Learning for Image Segmentation

EasyChair Preprint no. 8983

9 pagesDate: October 4, 2022


The purpose of this article is to explore the application value of deep learning algorithm in ultrasound images of thyroid nodules. A dataset of 7288 ultrasound images of thyroid nodules collected from the MICCAI 2020 challenge is established, the U_Net method is used, and adjustments are made on the basis of this method. Through continuous training, the optimal model is found and the computation is autonomous. accurate segmentation of thyroid nodules. The segmentation accuracy obtained by this network reaches 0.955, which has good segmentation performance.

Keyphrases: deep learning, Thyroid Nodules, U_Net

BibTeX entry
BibTeX does not have the right entry for preprints. This is a hack for producing the correct reference:
  author = {Xueting Zhou and Yan Chen and Shoushan Liu},
  title = {Deep Learning for Image Segmentation},
  howpublished = {EasyChair Preprint no. 8983},

  year = {EasyChair, 2022}}
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