The intravenous (IV) injection procedure can be a challenging task, especially for individuals with thin veins, obesity, or patients with damaged and pigmented skin. Therefore, the IV procedure necessitates a portable medical device that can be used for academic demonstrations to train medical students or by health care professionals to perform venipuncture. Vein visualization with a vein detector is principally based on the interaction of blood components with wavelengths of the electromagnetic spectrum (EMS). In this paper, we first present the process of image formation in the spectral band of the near‐infrared region (NIR) of EMS. Then, we introduce the image acquisition system with image processing to extract the veins as a noninvasive vein detection method. A Raspberry Pi (Model 4B), along with a night vision camera, serves as an image acquisition tool to capture skin area illuminated by NIR. Following this, the data is transferred to the laptop where it can be filtered and processed using Python image processing tools before being viewed on the monitor. The results achieved through the device are quite encouraging, as the image recognition between veins and adjacent tissues from the skin sample can be clearly marked. The functionality, accuracy, and simplicity associated with this vein detection system make it a potential device for IV placement and the morphological study of disease detection.

中文翻译：

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简化静脉手术的静脉检测：通过近红外成像系统进行比较评估

静脉 (IV) 注射过程可能是一项具有挑战性的任务，特别是对于静脉细、肥胖或皮肤受损和色素沉着的患者而言。因此，静脉注射手术需要一种便携式医疗设备，可用于学术演示以培训医学生或由医疗保健专业人员进行静脉穿刺。使用静脉检测器进行的静脉可视化主要基于血液成分与电磁波谱 (EMS) 波长的相互作用。在本文中，我们首先介绍了 EMS 近红外区域 (NIR) 光谱带中的图像形成过程。然后，我们介绍了通过图像处理提取静脉的图像采集系统作为一种无创静脉检测方法。 Raspberry Pi（型号 4B）与夜视摄像头一起作为图像采集工具来捕获近红外照明的皮肤区域。此后，数据被传输到笔记本电脑，在显示器上查看之前，可以使用 Python 图像处理工具对其进行过滤和处理。通过该设备取得的结果非常令人鼓舞，因为可以清楚地标记皮肤样本中静脉和邻近组织之间的图像识别。该静脉检测系统的功能性、准确性和简单性使其成为静脉注射和疾病检测形态学研究的潜在设备。