Deep Learning Approaches for Gynaecological Ultrasound Image Segmentation: A Radio-Frequency vs B-mode Comparison

Author:

Carvalho Catarina,Marques Sónia,Peixoto Carla,Pignatelli Duarte,Beires Jorge,Silva Jorge,Campilho Aurélio

Publisher

Springer International Publishing

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. Attention-based Transfer Learning Approach using Spatial Pyramid Pooling for Diagnosis of Polycystic Ovary Syndrome;2023 9th International Conference on Signal Processing and Communication (ICSC);2023-12-21

2. Attention-Based Multiscale Deep Neural Network for Diagnosis of Polycystic Ovary Syndrome Using Ovarian Ultrasound Images;2023 15th International Congress on Ultra Modern Telecommunications and Control Systems and Workshops (ICUMT);2023-10-30

3. A Deep Learning Fusion Approach to Diagnosis the Polycystic Ovary Syndrome (PCOS);Applied Computational Intelligence and Soft Computing;2023-02-14

4. Evaluation of liver fibrosis based on ultrasound radio frequency signals;2021 14th International Congress on Image and Signal Processing, BioMedical Engineering and Informatics (CISP-BMEI);2021-10-23

5. Stent Deployment Detection Using Radio Frequency‐Based Sensor and Convolutional Neural Networks;Advanced Intelligent Systems;2020-07-20

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