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市場調查報告書
商品編碼
1371935
到 2030 年醫療影像處理人工智慧市場預測:按產品、模式、技術、用途、最終用戶和地區進行的全球分析Artificial Intelligence in Medical Imaging Market Forecasts to 2030 - Global Analysis By Offering, Modality, Technology, Application, End User and By Geography |
根據Stratistics MRC預測,2023年全球醫療影像診斷人工智慧市場規模將達到10.011億美元,並在預測期內以32.8%的年複合成長率成長,到2030年將達到72.928億美元。
醫學影像中的人工智慧是利用先進的電腦方法,特別是機器學習和深度學習演算法,借助該技術來分析和解釋醫學影像,例如X光、MRI掃描、CT掃描等。借助技術,醫療專業人員可以更準確、更快速地辨識疾病、異常和異常現象。它有潛力徹底改變醫療診斷領域,並透過早期疾病檢測、治療計劃和個人化醫療顯著影響患者的治療結果和醫療保健效果。
根據美國癌症協會總合,今年美國將新增 236,740 例肺癌和支氣管癌罹患。
世界各國政府都知道人工智慧有潛力改善病患治療結果並減少醫療支出。此外,支持人工智慧在醫學影像處理中道德和安全應用的配合措施包括研究經費、稅收優惠和法律規範。這些鼓勵創新、獎勵對人工智慧解決方案的投資以及為技術公司、醫療保健組織和法規機構之間的合作創造友好環境的政策將加速人工智慧在醫學影像處理領域的成長和發展。因此,各國政府正在實施政策、融資和法規,以鼓勵人工智慧技術在醫療保健領域的創建和使用。
市場擴張受到用於醫學影像樣本和其他設備診斷各種疾病的各種人工智慧方法高成本。此外,不已開發國家和貧窮國家的大多數醫療機構和研究機構目前無法支付與醫學影像處理人工智慧研發相關的高額成本。因此,這些問題阻礙了市場的拓展。
超音波、電腦斷層掃描和磁振造影(MRI) 是取得重大進展的醫學影像技術的例子。這些尖端影像技術提供了大量複雜的資料,可以透過人工智慧演算法進行有效評估,實現更個體化的治療方案。因此,影像成像方式的技術開拓將促進市場擴張。
由於缺乏在醫學影像處理和人工智慧方面經驗豐富的訓練有素的人員,市場擴張受到阻礙。此外,這種短缺可能會阻礙人工智慧解決方案的開發和部署,因為醫療保健組織經常難以吸引和培養能夠管理人工智慧演算法、醫療資料和臨床程序複雜性的人才。因此,這些問題限制了市場的拓展。
醫學影像處理領域的人工智慧市場受到了 COVID-19大流行的各種負面影響。供應鏈中斷延遲了人工智慧醫療影像處理解決方案的開發和實施。醫療保健資源的轉變以及對流行病相關問題的關注進一步阻礙了人工智慧技術的使用。此外,由於醫學影像處理中的人工智慧應用依賴一致的資料流進行訓練和檢驗,因此非緊急醫療程序和影像檢查的可用性的降低推動了市場的成長。因此,疫情突然阻止了該產業人工智慧應用的快速成長。
由於使用 C 型臂等介入性 X 光技術的影像導引手術的增加,預計 X 光領域將佔據最大佔有率。此外,C 型臂(尤其是具有平板檢測器的緊湊型 C 型臂)和數位放射線攝影設備的發展顯著增加了所需的 X光量。因此,將人工智慧涵蓋 X 光影像診斷可以增加疾病的早期診斷,減少人為錯誤,最終改善患者的治療結果,同時降低成本。
由於使用人工智慧技術,特別是機器學習和深度學習演算法來分析大腦和脊髓的 MRI 和 CT影像等複雜的影像資料,預計神經病學領域在預測期內將具有最高的年複合成長率。此外,透過檢測微小的結構和功能異常,這些人工智慧系統可以幫助識別和診斷阿茲海默症、中風和腦腫瘤等神經系統疾病。因此,人工智慧還可以幫助預測疾病進展並規劃治療,為神經系統疾病患者提供早期療育和個人化護理,推動神經病學領域的發展並改善患者的治療效果。
由於最尖端科技的普及、網路連接的增強和政府舉措的擴大,亞太地區在預測期內佔據了最大的市場佔有率。進一步的推動力是投資的快速成長、使用人工智慧(AI)的公司數量不斷增加(特別是在中國和印度),以及人工智慧在提高圖像品質和縮小該地區醫療基礎設施差距方面的巨大潛力。 。此外,醫療保健產業的數位化正在加速,包括使用人工智慧進行機器人測試和醫學影像處理。
預計北美在預測期內的年複合成長率最高。這是由於對先進診斷技術的需求不斷成長,以提高醫學影像的準確性、效率和速度。此外,基於人工智慧的解決方案有可能幫助放射科醫生和其他醫療保健專業人員呈現複雜的醫學影像、提高診斷準確性並促進改進決策。因此,在對更好的診斷工具的需求不斷成長的推動下,區域市場擴張和資金籌措也是醫學影像領域區域AI(人工智慧)的關鍵促進因素。
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.