Automatic evaluation of endometrial receptivity in three-dimensional transvaginal ultrasound images based on 3D U-Net segmentation
Author:
Publisher
AME Publishing Company
Subject
Radiology, Nuclear Medicine and imaging
Link
https://qims.amegroups.com/article/download/95173/pdf
Cited by 5 articles. 订阅此论文施引文献 订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献
1. An Overview on Diagnosis of Endometriosis Disease Based on Machine Learning Methods;Lecture Notes in Networks and Systems;2024
2. Evolving the Era of 5D Ultrasound? A Systematic Literature Review on the Applications for Artificial Intelligence Ultrasound Imaging in Obstetrics and Gynecology;Journal of Clinical Medicine;2023-10-29
3. End-to-end deep learning radiomics: development and validation of a novel attention-based aggregate convolutional neural network to distinguish breast diffuse large B-cell lymphoma from breast invasive ductal carcinoma;Quantitative Imaging in Medicine and Surgery;2023-10
4. 3D PET/CT tumor segmentation based on nnU-Net with GCN refinement;Physics in Medicine & Biology;2023-09-12
5. Automated Detection of Endometrial Polyps from Hysteroscopic Videos Using Deep Learning;Diagnostics;2023-04-13
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