Improving GAN Learning Dynamics for Thyroid Nodule Segmentation-Reference-Cited by-同舟云学术

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Improving GAN Learning Dynamics for Thyroid Nodule Segmentation

Published:2023-02 Issue:2 Volume:49 Page:416-430
ISSN:0301-5629
Container-title:Ultrasound in Medicine & Biology
language:en
Short-container-title:Ultrasound in Medicine & Biology

Author:

Kunapinun Alisa^ORCID,Dailey Matthew N.,Songsaeng Dittapong,Parnichkun Manukid,Keatmanee Chadaporn,Ekpanyapong Mongkol

Publisher

Elsevier BV

Subject

Acoustics and Ultrasonics,Radiology, Nuclear Medicine and imaging,Biophysics,Radiological and Ultrasound Technology

Reference42 articles.

1. Wasserstein generative adversarial networks;Arjovsky,2017

2. SegNet: A deep convolutional Encoder-Decoder architecture for image segmentation;Badrinarayanan;IEEE Trans. Pattern Anal. Mach. Intell.,2017

3. D. Bank, N. Koenigstein, R. Giryes, Autoencoders (2020). arXiv:2003.05991. 2003.05991

4. A. Bochkovskiy, C.-Y. Wang, H.-Y. M. Liao, YOLOv4: Optimal speed and accuracy of object detection (2020). arXiv:2004.10934. 2004.10934

5. Evaluation of a thyroid nodule;Bomeli;Otolaryngol. Clin. North Am.,2010

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3. Intelligent healthcare system for IoMT-integrated sonography: Leveraging multi-scale self-guided attention networks and dynamic self-distillation;Internet of Things;2024-04

4. Generative Adversarial Networks (GANs) in Medical Imaging: Advancements, Applications, and Challenges;IEEE Access;2024

5. Automatic Thyroid Nodule Detection in Ultrasound Imaging With Improved YOLOv5 Neural Network;IEEE Access;2024

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