Systematic Evaluation of Loss Functions for Ovarian Tumors Segmentation from Ultrasound Images-Reference-Cited by-同舟云学术

Systematic Evaluation of Loss Functions for Ovarian Tumors Segmentation from Ultrasound Images

Published:2023-12-28 Issue: Volume:abs/2207.06799 Page:1-6
ISSN:
Container-title:2023 1st International Conference on Health Science and Technology (ICHST)
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Author:

Nguyen Thi-Huong¹,Pham Thi-Loan²,Tran Quoc-Vi²,Le Thi-Lan²,Tran Thanh-Hai²,Vu Hai²,Vu Duy-Hai³,Dang Hong-Thien⁴,Nguyen Van-Thang⁴,Pham Chi-Mai⁴,Nguven Phuong-Thao⁴

Affiliation:

1. School of Applied Mathematics and Informatics. Hanoi University of Science and Technology,Hanoi,Vietnam

2. School of Electrical and Electronic Engineering, Hanoi University of Science and Technology,Hanoi,Vietnam

3. Hai Duong University,Information Technology Department,HaiDuong,Vietnam

4. National hospital of obstetrics and gynecology,HaNoi,Vietnam

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx8/10565304/10565305/10565336.pdf?arnumber=10565336

Reference12 articles.

1. Subjective assessment of adnexal masses with the use of ultrasonography: an analysis of interobserver variability and experience

2. CR-Unet: A Composite Network for Ovary and Follicle Segmentation in Ultrasound Images

3. Ovarian Tumor Texture Classification Based on Sparse Auto-Encoder Network Combined with Multi-Feature Fusion and Random Forest in Ultrasound Image

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1. BKSeg-Net: Segmentation of Ovarian Tumors from Ultrasound Images with Boundary Keypoints Loss;2024 International Conference on Multimedia Analysis and Pattern Recognition (MAPR);2024-08-15

2. A Method for Ovarian Tumor Segmentation based on Segment Anything Model;2024 International Conference on Multimedia Analysis and Pattern Recognition (MAPR);2024-08-15