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| A Self-Supervised Learning Approach for High-Resolution Diffuse Optical Tomography Using Neural Fields | |
| 2023 | |
| 会议录名称 | PROCEEDINGS OF SPIE - THE INTERNATIONAL SOCIETY FOR OPTICAL ENGINEERING |
| ISSN | 0277-786X |
| 卷号 | 12753 |
| 发表状态 | 已发表 |
| DOI | 10.1117/12.2691305 |
| 摘要 | Diffuse optical tomography (DOT) has shown promise in biomedical research, such as breast cancer diagnostics and brain imaging, by reconstructing hidden objects within scattering media. However, the conventional reconstruction framework faces challenges due to the highly ill-posed inverse problem of reconstructing optical properties. This work introduces a novel approach, neural field-based diffuse optical tomography (NeuDOT), which leverages a multi-layer perceptron (MLP) to learn an implicit function that maps spatial coordinates to their corresponding optical absorption coefficients. The performance of the NeuDOT method has been evaluated through several phantom studies, demonstrating its potential for high spatial resolution DOT reconstruction. © 2023 SPIE. |
| 关键词 | Brain mapping Inverse problems Light absorption Light scattering Optical properties Optical tomography Supervised learning Adaptive meshing Biomedical research Brain imaging Breast cancer diagnostics Diagnostic imaging Diffuse optical tomography High resolution Images reconstruction Neural fields Supervised learning approaches |
| 会议名称 | 2nd Conference on Biomedical Photonics and Cross-Fusion, BPC 2023 |
| 会议地点 | Shanghai, China |
| 会议日期 | June 8, 2023 - June 10, 2023 |
| 收录类别 | EI |
| 语种 | 英语 |
| 出版者 | SPIE |
| EI入藏号 | 20233814733637 |
| EI主题词 | Image reconstruction |
| EISSN | 1996-756X |
| EI分类号 | 461.1 Biomedical Engineering ; 741.1 Light/Optics ; 741.3 Optical Devices and Systems ; 746 Imaging Techniques |
| 原始文献类型 | Conference article (CA) |
| 文献类型 | 会议论文 |
| 条目标识符 | https://kms.shanghaitech.edu.cn/handle/2MSLDSTB/335599 |
| 专题 | 信息科学与技术学院 物质科学与技术学院 信息科学与技术学院_PI研究组_虞晶怡组 信息科学与技术学院_硕士生 信息科学与技术学院_博士生 物质科学与技术学院_PI研究组_朱幸俊组 信息科学与技术学院_PI研究组_任无畏组 数学科学研究所_PI研究组(P)_姜嘉骅组 |
| 通讯作者 | Jiang, Jiahua; Yu, Jingyi; Ren, Wuwei |
| 作者单位 | 1.School of Information Science and Technology, ShanghaiTech University, Shanghai; 201210, China; 2.School of Physical Science and Technology, ShanghaiTech University, Shanghai; 201210, China; 3.Institute of Mathematical Science, ShanghaiTech University, Shanghai; 201210, China; 4.School of Mathematics, University of Birmingham, Edgbaston; B15 2QN, United Kingdom |
| 第一作者单位 | 信息科学与技术学院 |
| 通讯作者单位 | 上海科技大学; 信息科学与技术学院 |
| 第一作者的第一单位 | 信息科学与技术学院 |
| 推荐引用方式 GB/T 7714 | Li, Linlin,Shen, Siyuan,Gao, Shengyu,et al. A Self-Supervised Learning Approach for High-Resolution Diffuse Optical Tomography Using Neural Fields[C]:SPIE,2023. |
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