Automated, Reproducible, and Reconfigurable Human Head Phantom for Experimental Testing of Microwave Systems for Stroke Classification

IF 3 4区计算机科学 Q2 ENGINEERING, ELECTRICAL & ELECTRONIC

International Journal of Imaging Systems and Technology Pub Date : 2024-10-26 DOI:10.1002/ima.23200

Tomas Pokorny, Tomas Drizdal, Marek Novak, Jan Vrba

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Abstract

Microwave systems for prehospital stroke classification are currently being developed. In the future, these systems should enable rapid recognition of the type of stroke, shorten the time to start treatment, and thus significantly improve the prognosis of patients. In this study, we realized a realistic and reconfigurable 3D human head phantom for the development, testing, and validation of these newly developed diagnostic methods. The phantom enables automated and reproducible measurements for different positions of the stroke model. The stroke model itself is also interchangeable, so measurements can be made for different types, sizes, and shapes of strokes. Furthermore, an extensive series of measurements was performed at a frequency of 1 GHz, and an SVM classification algorithm was deployed, which successfully identified ischemic stroke in 80% of the corresponding measured data. If similar classification accuracy could be achieved in patients, it would lead to a dramatic reduction in the consequences of strokes.

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用于中风分类微波系统实验测试的自动化、可重现和可重构的人体头部模型

目前正在开发用于院前中风分类的微波系统。未来，这些系统应能快速识别中风类型，缩短开始治疗的时间，从而显著改善患者的预后。在本研究中，我们实现了一个逼真且可重新配置的三维人体头部模型，用于开发、测试和验证这些新开发的诊断方法。该模型可对中风模型的不同位置进行自动和可重复的测量。中风模型本身也可以互换，因此可以对不同类型、大小和形状的中风进行测量。此外，还在 1 GHz 频率下进行了一系列广泛的测量，并采用 SVM 分类算法，在 80% 的相应测量数据中成功识别出缺血性中风。如果能在患者身上实现类似的分类准确性，将大大减少脑卒中的后果。

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来源期刊

International Journal of Imaging Systems and Technology 工程技术-成像科学与照相技术

CiteScore

6.90

自引率

6.10%

发文量

138

审稿时长

3 months

期刊介绍： The International Journal of Imaging Systems and Technology (IMA) is a forum for the exchange of ideas and results relevant to imaging systems, including imaging physics and informatics. The journal covers all imaging modalities in humans and animals. IMA accepts technically sound and scientifically rigorous research in the interdisciplinary field of imaging, including relevant algorithmic research and hardware and software development, and their applications relevant to medical research. The journal provides a platform to publish original research in structural and functional imaging. The journal is also open to imaging studies of the human body and on animals that describe novel diagnostic imaging and analyses methods. Technical, theoretical, and clinical research in both normal and clinical populations is encouraged. Submissions describing methods, software, databases, replication studies as well as negative results are also considered. The scope of the journal includes, but is not limited to, the following in the context of biomedical research: Imaging and neuro-imaging modalities: structural MRI, functional MRI, PET, SPECT, CT, ultrasound, EEG, MEG, NIRS etc.; Neuromodulation and brain stimulation techniques such as TMS and tDCS; Software and hardware for imaging, especially related to human and animal health; Image segmentation in normal and clinical populations; Pattern analysis and classification using machine learning techniques; Computational modeling and analysis; Brain connectivity and connectomics; Systems-level characterization of brain function; Neural networks and neurorobotics; Computer vision, based on human/animal physiology; Brain-computer interface (BCI) technology; Big data, databasing and data mining.