Atiya Nisan, Shemer Amir, Schwarz Ariel, Beiderman Yevgeny, Danan Yossef
Department of Electrical and Electronics Engineering, Azrieli College of Engineering, Jerusalem 9103501, Israel.
Faculty of Electrical and Electronics Engineering, Holon Institute of Technology, Holon 5810201, Israel.
Sensors (Basel). 2025 Aug 12;25(16):4977. doi: 10.3390/s25164977.
Non-invasive diagnostics play a crucial role in medicine, and they ensure both contamination safety and patient comfort. The proposed study integrates hyperspectral imaging with advanced image fusion, enabling non-invasive, diagnostic procedure within tissue. It utilizes near-infrared (NIR) wavelength vision that is suitable for reflections from objects within a dispersive layer, enabling the reconstruction of internal tissue layers images. It can detect objects, including cancerous tumors (presented as phantoms), inside human tissue. This involves processing data from multiple images taken in different NIR bands and merging them through image fusion techniques. Our research demonstrates evident data about objects within the diffusive media, visible only in the reconstructed images. The experimental results demonstrate a significant correlation with the samples employed in the study's experimental design.
非侵入性诊断在医学中发挥着至关重要的作用，它既能确保无污染安全又能让患者感到舒适。拟议的研究将高光谱成像与先进的图像融合技术相结合，能够在组织内进行非侵入性诊断程序。它利用近红外（NIR）波长视觉，适用于色散层内物体的反射，从而能够重建内部组织层图像。它可以检测人体组织内的物体，包括癌性肿瘤（以体模形式呈现）。这涉及处理在不同近红外波段拍摄的多个图像的数据，并通过图像融合技术将它们合并。我们的研究展示了关于扩散介质内物体的明显数据，这些数据仅在重建图像中可见。实验结果表明与该研究实验设计中使用的样本有显著相关性。
