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What is new in computer vision and artificial intelligence in medical image analysis applications

机译:在医学图像分析应用中的计算机视觉和人工智能中是什么新的

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Computer vision and artificial intelligence applications in medicine are becoming increasingly important day by day, especially in the field of image technology. In this paper we cover different artificial intelligence advances that tackle some of the most important worldwide medical problems such as cardiology, cancer, dermatology, neurodegenerative disorders, respiratory problems, and gastroenterology. We show how both areas have resulted in a large variety of methods that range from enhancement, detection, segmentation and characterizations of anatomical structures and lesions to complete systems that automatically identify and classify several diseases in order to aid clinical diagnosis and treatment. Different imaging modalities such as computer tomography, magnetic resonance, radiography, ultrasound, dermoscopy and microscopy offer multiple opportunities to build automatic systems that help medical diagnosis, taking advantage of their own physical nature. However, these imaging modalities also impose important limitations to the design of automatic image analysis systems for diagnosis aid due to their inherent characteristics such as signal to noise ratio, contrast and resolutions in time, space and wavelength. Finally, we discuss future trends and challenges that computer vision and artificial intelligence must face in the coming years in order to build systems that are able to solve more complex problems that assist medical diagnosis.
机译:医学中的计算机视觉和人工智能应用日益越来越重要,特别是在图像技术领域。在本文中,我们涵盖了不同的人工智能推进,以解决一些最重要的全球医疗问题,如心脏病,癌症,皮肤病学,神经退行性障碍,呼吸问题和胃肠病学。我们展示了两个领域如何导致各种各样的方法,这些方法范围从解剖结构和病变对自动识别和分类几种疾病的完整系统的增强,检测,分割和表征,以帮助临床诊断和治疗。不同的成像模式,如计算机断层扫描,磁共振,射线照相,超声,Dermoscopy和显微镜,为构建有助于医疗诊断的自动系统提供多种机会,可利用自己的物理性质。然而,由于其固有的特性,这些成像方式对诊断辅助的自动图像分析系统的设计进行了重要限制,这是由于它们的噪声比,对比度,空间和波长的噪声比,对比度和分辨率。最后,我们讨论了未来几年的计算机视觉和人工智能必须面临的未来趋势和挑战,以建立能够解决更多复杂问题的系统,可以帮助辅助医疗诊断。

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