A Machine Learning-based Inverse Scattering Method for Biomedical Imaging Segmentation

被引：0

作者：

Du, Naike ^{[1
]}

Ye, Xiuzhu ^{[1
]}

机构：

[1] Beijing Inst Technol, Sch Elect & Informat, Beijing, Peoples R China

来源：

2024 IEEE INTERNATIONAL SYMPOSIUM ON ANTENNAS AND PROPAGATION AND INC/USNCURSI RADIO SCIENCE MEETING, AP-S/INC-USNC-URSI 2024 | 2024年

基金：

美国国家科学基金会;

关键词：

inverse scattering method; SOM; transformer-based network; imaging segmentation;

D O I：

10.1109/AP-S/INC-USNC-URSI52054.2024.10686379

中图分类号：

TM [电工技术]; TN [电子技术、通信技术];

学科分类号：

0808 ; 0809 ;

摘要：

This paper proposes a transformer-based neural network, for segmenting the images of human tissues obtained by inverse scattering method. Firstly, the distribution image of relative permittivity for the human tissue is obtained by the subspace-based optimization method (SOM). Then the obtained results are fed into a transformer-based network to output a segmentation mask. Numerical results verify that this method can get clear edges for different tissues, and it can achieve accurate classification for human tissue imaging.

引用

页码：251 / 252

页数：2

共 50 条

[21] nnU-Net: a self-configuring method for deep learning-based biomedical image segmentation
Fabian Isensee
Paul F. Jaeger
Simon A. A. Kohl
Jens Petersen
Klaus H. Maier-Hein
Nature Methods, 2021, 18 : 203 - 211
[22] Improving machine learning-based bitewing segmentation with synthetic data
Tolstaya, Ekaterina
Tichy, Antonin
Paris, Sebastian
Schwendicke, Falk
JOURNAL OF DENTISTRY, 2025, 156
[23] Deep learning-based inverse method for layout design
Zhang, Yujie
Ye, Wenjing
STRUCTURAL AND MULTIDISCIPLINARY OPTIMIZATION, 2019, 60 (02) : 527 - 536
[24] Learning-Based Sampling Method for Point Cloud Segmentation
An, Yi
Wang, Jian
He, Lijun
Li, Fan
IEEE SENSORS JOURNAL, 2024, 24 (15) : 24140 - 24151
[25] Machine Learning-based Diffractive Imaging with Subwavelength Resolution
Ghosh, Abantika
Roth, Diane J.
Nicholls, Luke H.
Wardley, William P.
Zayats, Anatoly
Podolskiy, Viktor A.
2020 CONFERENCE ON LASERS AND ELECTRO-OPTICS (CLEO), 2020,
[26] Probabilistic and machine learning-based retrieval approaches for biomedical dataset retrieval
Karisani, Payam
Qin, Zhaohui S.
Agichtein, Eugene
DATABASE-THE JOURNAL OF BIOLOGICAL DATABASES AND CURATION, 2018,
[27] Deep Learning-Based Image Segmentation on Multimodal Medical Imaging
Guo, Zhe
Li, Xiang
Huang, Heng
Guo, Ning
Li, Quanzheng
IEEE TRANSACTIONS ON RADIATION AND PLASMA MEDICAL SCIENCES, 2019, 3 (02) : 162 - 169
[28] Deep Learning-Based Inverse Scattering With Structural Similarity Loss Functions
Huang, Youyou
Song, Rencheng
Xu, Kuiwen
Ye, Xiuzhu
Li, Chang
Chen, Xun
IEEE SENSORS JOURNAL, 2021, 21 (04) : 4900 - 4907
[29] Machine learning-based inverse predictive model for AFP based thermoplastic composites
Wanigasekara, Chathura
Oromiehie, Ebrahim
Swain, Akshya
Prusty, B. Gangadhara
Nguang, Sing Kiong
JOURNAL OF INDUSTRIAL INFORMATION INTEGRATION, 2021, 22
[30] Compressed Machine Learning-Based Inverse Model for the Design of Microwave Filters
Sedaghat, Mostafa
Trinchero, Riccardo
Canavero, Flavio
2021 IEEE MTT-S INTERNATIONAL MICROWAVE SYMPOSIUM (IMS), 2021, : 13 - 15

← 1 2 3 4 5 →