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首页> 外文期刊>Procedia Computer Science >Dendritic Cell Recognition in Computer Aided System for Cancer Immunotherapy
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Dendritic Cell Recognition in Computer Aided System for Cancer Immunotherapy

机译:肿瘤免疫治疗计算机辅助系统中的树突状细胞识别

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摘要

Immunotherapy is an entirely advanced class of cancer treatment which has been highly active and exciting field in clinical therapeutics. In numerous procedures, cancer immunotherapy demands a laborious practice to recognise and count Dendritic Cells (DCs) in the vaccine preparation. Conventionally, the laser-based technologythat provides a rapid analysis such as Flow Cytometrycan affect the DCs viability as the staining procedure is involved. Another highly promising method which is Phase Contrast Microscopy (PCM) involves experienced pathologists to visually examine the respective microscopy images. In facts, PCM confronts complex issues regarding to imaging artifacts which can deteriorate the recognition process.As the DCs counting is crucial in cancer treatment procedures, this paper proposes a pioneering system called CasDC which implement an image processing algorithm to recognise and count DCs with a label-free method. The aim of developing this system is to establish a reliable and time saving-tool as a second reader in the clinical practice. In the meantime, the treatment procedure can be administered and therefore, improve the patient's survival rate. Our proposed system has an enormous potential towards helping Cancer Research Institute in which the system offers rapid and high throughput cancer immunotherapy vaccine preparation and automated live cell investigation.
机译:免疫疗法是一门完全先进的癌症治疗方法,在临床治疗中一直是非常活跃和令人兴奋的领域。在许多程序中,癌症免疫疗法需要费力的操作来识别和计数疫苗制剂中的树突状细胞(DC)。传统上,基于激光的技术可提供快速分析,例如流式细胞术,因为涉及染色过程,因此会影响DC的生存能力。另一极有前途的方法是相差显微镜(PCM),它由经验丰富的病理学家目视检查相应的显微镜图像。实际上,PCM面临着与成像伪影有关的复杂问题,这可能会使识别过程恶化。由于DC计数在癌症治疗程序中至关重要,因此,本文提出了一种称为CasDC的先驱系统,该系统实现了一种图像处理算法,可利用图像识别算法对DC进行识别和计数。无标签方法。开发该系统的目的是建立一种可靠且省时的工具,作为临床实践中的第二读者。同时,可以实施治疗程序,因此可以提高患者的生存率。我们提出的系统在帮助癌症研究所方面具有巨大的潜力,该系统提供快速和高通量的癌症免疫疗法疫苗制备和自动活细胞研究。

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