LRTHR-Net: A Low-Resolution-to-High-Resolution Framework to Iteratively Refine the Segmentation of Thyroid Nodule in Ultrasound Images-Reference-Cited by-同舟云学术

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LRTHR-Net: A Low-Resolution-to-High-Resolution Framework to Iteratively Refine the Segmentation of Thyroid Nodule in Ultrasound Images

Published:2021 Issue: Volume: Page:116-121
ISSN:0302-9743
Container-title:Segmentation, Classification, and Registration of Multi-modality Medical Imaging Data
language:
Short-container-title:

Author:

Chen Huai,Song Shaoli,Wang Xiuying,Wang Renzhen,Meng Deyu,Wang Lisheng

Publisher

Springer International Publishing

Link

https://link.springer.com/content/pdf/10.1007/978-3-030-71827-5_15

Reference8 articles.

1. https://www.btf-thyroid.org/what-is-thyroid-disorder

2. http://www.thyroid.org/wp-content/uploads/patients/brochures/Nodules_brochure.pdf

3. https://www.cancer.net/cancer-types/thyroid-cancer/statistics

4. https://tn-scui2020.grand-challenge.org/Home/

5. Lecture Notes in Computer Science;H Chen,2019

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1. Active Learning Strategies on a Real-World Thyroid Ultrasound Dataset;Lecture Notes in Computer Science;2024

2. Few-Shot Image Semantic Segmentation based on Contextual Information Encoding Strategy;2023 Asia Conference on Advanced Robotics, Automation, and Control Engineering (ARACE);2023-08-18

3. A New Fuzzy Smoothing Term Model For Stereo Matching;The Computer Journal;2023-03-10

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