School of Electrical Engineering, VIT Chennai, Chennai 600127, Tamil Nadu, India.
Centre for Automation, School of Electrical Engineering, VIT Chennai, Chennai 600127, Tamil Nadu, India.
Int J Environ Res Public Health. 2023 Jan 10;20(2):1273. doi: 10.3390/ijerph20021273.
In developing countries, there is more concern for Alzheimer's disease (AD) by public health professionals due to its catastrophic effects on the elderly. Early detection of this disease helps in starting the therapy soon and slows down the progression of the disease. Imaging techniques are considered to be the best solutions for its detection. Brain imaging was initially used to diagnose AD. Different techniques for identifying protein accumulation in the nervous system, a sign of Alzheimer's disease, are identified by MRI imaging. Although they were initially attributed to cortical dysfunction, visual system impairments in Alzheimer's patients were also found in the early 1970s. Several non-invasive approaches reported for screening, prevention, and therapy were unsuccessful. It is vitally necessary to develop new diagnostic methods in order to accurately identify patients who are in the early stages of this disease. It would be wonderful to have a quick, non-invasive, affordable, and easily scalable Alzheimer's disease screening. Researchers may be able to identify biomarkers for Alzheimer's disease and understand more about its aetiology with imaging and data processing. This study clarifies the need for medical image processing and analysis strategies which aid in the non-invasive diagnosis of AD.
在发展中国家,由于阿尔茨海默病(AD)对老年人的灾难性影响,公共卫生专业人员更加关注这种疾病。早期发现这种疾病有助于尽早开始治疗,并减缓疾病的进展。成像技术被认为是检测它的最佳方法。脑成像最初用于诊断 AD。MRI 成像可以识别出不同的技术,用于识别神经系统中蛋白质的积累,这是阿尔茨海默病的一个标志。尽管它们最初归因于皮质功能障碍,但在 20 世纪 70 年代早期也发现了阿尔茨海默病患者的视觉系统损伤。已经报道了几种用于筛查、预防和治疗的非侵入性方法,但都没有成功。为了准确识别处于疾病早期的患者,迫切需要开发新的诊断方法。如果有一种快速、非侵入性、经济实惠且易于扩展的阿尔茨海默病筛查方法就好了。研究人员可能能够识别出阿尔茨海默病的生物标志物,并通过成像和数据处理更好地了解其病因。这项研究阐明了需要医疗图像处理和分析策略来帮助对 AD 进行非侵入性诊断。