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市场调查报告书
商品编码
1371935
到 2030 年医疗影像处理人工智慧市场预测:按产品、模式、技术、用途、最终用户和地区进行的全球分析Artificial Intelligence in Medical Imaging Market Forecasts to 2030 - Global Analysis By Offering, Modality, Technology, Application, End User and By Geography |
根据Stratistics MRC预测,2023年全球医疗影像诊断人工智慧市场规模将达到10.011亿美元,并在预测期内以32.8%的年复合成长率成长,到2030年将达到72.928亿美元。
医学影像中的人工智慧是利用先进的电脑方法,特别是机器学习和深度学习演算法,借助该技术来分析和解释医学影像,例如X光、MRI扫描、CT扫描等。借助技术,医疗专业人员可以更准确、更快速地辨识疾病、异常和异常现象。它有潜力彻底改变医疗诊断领域,并透过早期疾病检测、治疗计划和个人化医疗显着影响患者的治疗结果和医疗保健效果。
根据美国癌症协会总合,今年美国将新增 236,740 例肺癌和支气管癌罹患。
世界各国政府都知道人工智慧有潜力改善病患治疗结果并减少医疗支出。此外,支持人工智慧在医学影像处理中道德和安全应用的配合措施包括研究经费、税收优惠和法律规范。这些鼓励创新、奖励对人工智慧解决方案的投资以及为技术公司、医疗保健组织和法规机构之间的合作创造友好环境的政策将加速人工智慧在医学影像处理领域的成长和发展。因此,各国政府正在实施政策、融资和法规,以鼓励人工智慧技术在医疗保健领域的创建和使用。
市场扩张受到用于医学影像样本和其他设备诊断各种疾病的各种人工智慧方法高成本。此外,不发达国家和贫穷国家的大多数医疗机构和研究机构目前无法支付与医学影像处理人工智慧研发相关的高额成本。因此,这些问题阻碍了市场的拓展。
超音波、电脑断层扫描和磁振造影(MRI) 是取得重大进展的医学影像技术的例子。这些尖端影像技术提供了大量复杂的资料,可以透过人工智慧演算法进行有效评估,实现更个体化的治疗方案。因此,影像成像方式的技术开拓将促进市场扩张。
由于缺乏在医学影像处理和人工智慧方面经验丰富的训练有素的人员,市场扩张受到阻碍。此外,这种短缺可能会阻碍人工智慧解决方案的开发和部署,因为医疗保健组织经常难以吸引和培养能够管理人工智慧演算法、医疗资料和临床程序复杂性的人才。因此,这些问题限制了市场的拓展。
医学影像处理领域的人工智慧市场受到了 COVID-19大流行的各种负面影响。供应链中断延迟了人工智慧医疗影像处理解决方案的开发和实施。医疗保健资源的转变以及对流行病相关问题的关注进一步阻碍了人工智慧技术的使用。此外,由于医学影像处理中的人工智慧应用依赖一致的资料流进行训练和检验,因此非紧急医疗程序和影像检查的可用性的降低推动了市场的成长。因此,疫情突然阻止了该产业人工智慧应用的快速成长。
由于使用 C 型臂等介入性 X 光技术的影像导引手术的增加,预计 X 光领域将占据最大份额。此外,C 型臂(尤其是具有平板检测器的紧凑型 C 型臂)和数数位放射线摄影设备的发展显着增加了所需的 X 射线量。因此,将人工智慧纳入 X 光影像诊断可以增加疾病的早期诊断,减少人为错误,最终改善患者的治疗结果,同时降低成本。
由于使用人工智慧技术,特别是机器学习和深度学习演算法来分析大脑和脊髓的 MRI 和 CT影像等复杂的影像资料,预计神经病学领域在预测期内将具有最高的年复合成长率。此外,透过检测微小的结构和功能异常,这些人工智慧系统可以帮助识别和诊断阿兹海默症、中风和脑肿瘤等神经系统疾病。因此,人工智慧还可以帮助预测疾病进展并规划治疗,为神经系统疾病患者提供早期疗育和个人化护理,推动神经病学领域的发展并改善患者的治疗效果。
由于最尖端科技的普及、网路连接的增强和政府倡议的扩大,亚太地区在预测期内占据了最大的市场占有率。进一步的推动力是投资的快速成长、使用人工智慧(AI)的公司数量不断增加(特别是在中国和印度),以及人工智慧在提高图像品质和缩小该地区医疗基础设施差距方面的巨大潜力。 。此外,医疗保健产业的数位化正在加速,包括使用人工智慧进行机器人测试和医学影像处理。
预计北美在预测期内的年复合成长率最高。这是由于对先进诊断技术的需求不断增长,以提高医学影像的准确性、效率和速度。此外,基于人工智慧的解决方案有可能帮助放射科医生和其他医疗保健专业人员呈现复杂的医学影像、提高诊断准确性并促进改进决策。因此,在对更好的诊断工具的需求不断增长的推动下,区域市场扩张和资金筹措也是医学影像领域区域AI(人工智慧)的关键促进因素。
According to Stratistics MRC, the Global Artificial Intelligence in Medical Imaging Market is accounted for $1,001.1 million in 2023 and is expected to reach $7,292.8 million by 2030 growing at a CAGR of 32.8% during the forecast period. Artificial intelligence in medical imaging is the analysis and interpretation of medical images such as X-rays, MRI scans, and CT scans using sophisticated computer approaches, especially machine learning and deep learning algorithms, with the help of this technology, medical personnel can identify diseases, anomalies, and abnormalities more precisely and quickly. It has the potential to revolutionize the area of medical diagnostics and have a profound impact on patient outcomes and healthcare effectiveness through early disease identification, treatment planning, and personalized medicine.
According to the American Cancer Society, a total of 236,740 new cases of lung and bronchus cancer are estimated this year in the United States.
Governments all over the world have knowledge of how AI has the potential to improve patient outcomes and lower healthcare expenditures. Moreover, initiatives that support the ethical and safe application of AI in medical imaging include funding for research, tax breaks, and regulatory frameworks. The growth and development of AI in medical imaging is accelerated by these policies, which encourage innovation, reward investment in AI solutions, and create a friendly climate for cooperation among technology companies, healthcare organizations, and regulatory agencies. Therefore, governments have implemented policies, financing, and regulations to promote the creation and use of AI technologies in healthcare.
The expansion of the market is constrained by the high cost of various artificial intelligence approaches used in medical imaging samples and other equipment to diagnose a wide range of disorders. Additionally, the majority of healthcare facilities and research institutions in undeveloped and poor countries are unable to pay the higher costs associated with R&D for artificial intelligence in medical imaging at the moment. The market expansion is therefore hampered by these issues.
Ultrasound, computed tomography, and magnetic resonance imaging (MRI) are examples of medical imaging technologies that have made major improvements. These cutting-edge imaging techniques provide enormous amounts of complicated data, which have been effectively evaluated by AI algorithms to allow for more individualized treatment programs. Therefore, technological developments in imaging modalities promote market expansion.
The expansion of the market is hampered by the lack of trained personnel with experience in both medical imaging and artificial intelligence. Furthermore, as healthcare organizations frequently struggle to locate and train individuals who can manage the intricacies of AI algorithms, medical data, and clinical procedures, this shortage could impede the development and deployment of AI solutions. Therefore, these problems restrict the market's expansion.
The artificial intelligence in medical imaging market has been negatively impacted by the COVID-19 pandemic in a number of ways. Supply chains were upset, which delayed the development and implementation of AI-driven medical imaging solutions. The use of AI technologies was further hindered by the shift in healthcare resources and focus to pandemic-related issues. Additionally, as AI applications in medical imaging depend on a consistent stream of data for training and validation, the decreased availability of non-urgent medical procedures and imaging studies had an impact on the market's growth. Therefore, the pandemic suddenly stopped the rapid growth of AI deployment in this industry.
The X-ray segment is estimated to hold the largest share, due to the rise in image-guided procedures using interventional x-ray technology, such as C-arms and other models. Moreover, the requirement for X-rays has substantially increased due to the development of C-arms, particularly small C-arms with flat panel detectors and digital radiography. Therefore, by incorporating AI into X-ray imaging, it is possible to increase the early diagnosis of disease, lessen human error, and eventually improve patient outcomes while also saving money.
The Neurology segment is anticipated to have highest CAGR during the forecast period, due to complex neuroimaging data, such as those from MRI and CT images of the brain and spinal cord, are analyzed using AI technology, notably machine learning and deep learning algorithms. Moreover, by detecting small structural and functional anomalies, these AI systems assist in the identification and diagnosis of neurological illnesses like Alzheimer's disease, stroke, and brain tumors. Therefore, AI can also help with disease progression prediction and therapy planning, enabling early intervention and individualized care for patients with neurological diseases, progressing the area of neurology, and increasing patient outcomes.
Asia Pacific commanded the largest market share during the extrapolated period owing to the widespread use of cutting-edge technologies, improved network connectivity, and expanded government initiatives. Moreover, the exponential growth in investment, the rise in artificial intelligence (AI)-using businesses, particularly in China and India, and the great potential for AI to reduce the region's healthcare infrastructure gap by enhancing image quality are further motivating drivers. Furthermore, digitization is speeding up in the healthcare industry, including robotic testing and medical image processing powered by AI.
North America is expected to witness highest CAGR over the projection period; owing to advanced diagnostic technologies with increased accuracy, efficiency, and speed in medical imaging are becoming more and more necessary. Additionally, AI-based solutions have the potential to assist radiologists and other healthcare workers in presenting complex medical pictures, improving diagnostic precision, and facilitating improved decision-making. Therefore, regional market expansion and funding are also key drivers for regional AI (artificial intelligence) in the medical imaging sector, which is driven by the increasing demand for better diagnostic tools.
Some of the key players in the Artificial Intelligence in Medical Imaging Market include: Aitia, Arterys Inc., BenevolentAI, Digital Diagnotics Inc., EchoNous, GE Healthcare, IBM Watson Health, Intel Corporation, Lunit Inc., Nanox Imaging LTD., OrCam, Prognos Health, Qventus, Siemens Healthcare GmbH and ZealthLife technologies Pte. Ltd
In September 2022, IBM announced its intent to acquire Dialexa, a prominent U.S. digital product engineering services firm. This acquisition will strengthen the company's product engineering expertise while offering end-to-end digital transformation services for clients.
In August 2022, GE Healthcare unveiled Definium™ 656 HD, a next-generation X-ray system in its fixed X-ray products portfolio. This product offers in-room workflows and motorization with an intelligent workflow suite, flashpad detectors, and AI-driven helix advanced image processing software.
In June 2021, VUNO Inc., a South Korean AI business, announced a strategic partnership with Samsung Electronics for the incorporation of the AI-powered mobile digital X-ray system VUNO Med-Chest X-ray within the GM85. This partnership is projected to bring VUNO closer to the expansion of AI applications that are market-ready due to its access to the global market.