![]() |
市場調查報告書
商品編碼
1405226
病理檢測領域人工智慧的全球市場規模、佔有率和趨勢分析報告:按神經網路、應用、最終用戶、組成以及地區分類的展望和預測,2023-2030年Global AI in Pathology Market Size, Share & Trends Analysis Report By Neural Network, By Application (Drug Discovery, Disease Diagnosis & Prognosis, Clinical Workflow, and Others), By End User, By Component, By Regional Outlook and Forecast, 2023 - 2030 |
病理學人工智慧市場規模預計到2030年將達到 6,630 萬美元,預測期內年複合成長率為 15.8%。
取得和實施數位病理系統(包括整個幻燈片成像掃描儀、軟體平台和相關基礎設施)的初期成本可能很高。這樣的初始投資對醫療機構來說可能是一個財務挑戰,特別是那些規模較小或預算有限的醫療機構。培訓病理學家和實驗室工作人員有效使用數位病理學系統和人工智慧工具也會增加整體成本。由於上述因素,未來幾年市場成長可能會受到阻礙。
神經網路的觀點
依神經網路,市場分為生成對抗網路(GAN)、卷積類神經網路(CNN)、循環神經網路(RNN)等。生成對抗網路(GAN)領域在2022年獲得了可觀的市場收益佔有率。 GAN 廣泛用於產生逼真的影像。 GAN應用於高解析度影像生成、藝術生成、 深度偽造生成等。 GAN 用於各個領域的資料增強,以產生額外的訓練樣本以提高模型的穩健性。 GAN 可以提高影像解析度並從低解析度輸入影像產生高品質影像。 GAN 可以根據文字說明產生逼真的圖像,彌合自然語言和圖形內容之間的差距。
應用前景
依應用分類,市場分為藥物研發、疾病診斷/預後、臨床工作流程等。2022年,藥物研發發現市場收益佔有率最高。人工智慧演算法可以分析從高通量篩檢過程中獲得的大型資料集。這包括對細胞培養物、組織病理學影像以及藥物研發流程中產生的其他資料的分析。自動化分析任務可以加快潛在候選藥物的辨識速度。人工智慧可以檢查藥物和生物途徑之間的相互作用。了解藥物如何影響疾病病理背景下的特定途徑有助於合理化干預措施並確定潛在的協同效應或拮抗。
最終用戶前景
依最終用戶分類,市場分為製藥和生物技術公司、醫院和參考實驗室以及學術和研究機構。2022年,醫院和參考實驗室部門在市場中佔據了重要的收益佔有率。人工智慧支援引進數位病理學測試,將玻片數位化並遠端查看和分析。這有利於醫院內或不同地點的病理學家之間的協作、第二意見和諮詢。人工智慧是病理學家的決策支援系統,在診斷過程中提供即時幫助。人工智慧還可以用於病理學家的持續學習和培訓計畫。虛擬模擬、互動式學習模組和人工智慧輔助培訓有助於持續的專業發展。
組件前景
依組件分類,市場分為軟體和掃描器。到2022年,軟體部門將在市場中獲得可觀的收益佔有率。這一巨大佔有率歸因於病理學家對基於人工智慧的軟體的廣泛接受和使用。該軟體領域的一些優勢包括高適應性、互通性、各種病理測試的自動化,包括影像分析、資料提取和報告編寫。這些因素推動了人工智慧軟體在病理學領域的採用和發展,為疾病檢測、診斷和治療規劃的進步提供了廣闊的前景。
區域展望
從區域來看,對北美、歐洲、亞太地區和LAMEA的市場進行了分析。2022年,亞太地區在市場中佔據了重要的收益佔有率。該地區龐大且多樣化的患者群體為訓練和檢驗人工智慧演算法提供了豐富的資料。病理學中的人工智慧模型受益於患者人口統計和病理的多樣性,提高了其普遍性。醫療保健提供者和技術公司(包括專門從事人工智慧的公司)之間的合作將加速亞太地區病理學人工智慧解決方案的開發和部署。
市場領導者透過各種創新產品進行競爭,以保持市場競爭力。上圖顯示了同一市場主要企業的收益。市場領先公司採取不同的策略來滿足不同行業的需求。該市場的主要發展策略是收購、合作和合作。
The Global AI in Pathology Market size is expected to reach $66.3 million by 2030, rising at a market growth of 15.8% CAGR during the forecast period.
Collaborations enable the seamless integration of these technologies into pathology workflows for enhanced diagnostics. Healthcare companies provide valuable clinical data and pathology images, while tech companies offer data management, analytics, and artificial intelligence expertise. Consequently, the disease diagnosis & prognosis segment would generate approximately 25.12% share of the market by 2030. Leveraging advanced machine learning algorithms, AI systems analyze vast amounts of pathological data with unprecedented speed and accuracy, aiding pathologists in identifying and classifying diseases. Some of the factors affecting the market are growing digitalization of pathology, increasing demand for personalized medicine, and high cost of digital pathology systems.
Digital pathology provides high-resolution digital images that can be analyzed more efficiently than traditional microscopy. AI algorithms leverage these images to identify patterns, anomalies, and specific features relevant to disease diagnosis. The digitalization of pathology generates large datasets. AI excels in analyzing big data, extracting patterns, and identifying correlations that may not be easily discernible through traditional methods. Thus, the growing digitalization of pathology will expand the market growth in the coming years. Moreover, AI algorithms analyze pathological data to identify and validate biomarkers associated with specific diseases. These biomarkers serve as indicators for personalized treatment strategies, allowing for more targeted and effective interventions. Thus, the increasing need for personalized medicine is a driving force behind the expansion of market.
The upfront cost of acquiring and implementing digital pathology systems, including whole-slide imaging scanners, software platforms, and associated infrastructure, can be substantial. This initial investment may pose financial challenges for healthcare institutions, particularly smaller laboratories or those with limited budgets. Training pathologists and laboratory staff to effectively use digital pathology systems and AI tools adds to the overall cost. Due to the above factors, market growth will be hampered in the coming years.
Neural Network Outlook
Based on neural network, the market is fragmented into generative adversarial networks (GANs), convolutional neural networks (CNNs), recurrent neural networks (RNNs), and others. The generative adversarial networks (GANs) segment garnered a significant revenue share in the market in 2022. GANs are widely utilized for generating realistic images. They have been applied in creating high-resolution images, art generation, and deepfake generation. GANs are employed for data augmentation in various domains, generating additional training samples to enhance model robustness. They can enhance the resolution of images, generating high-quality versions of low-resolution input images. GANs can generate realistic images from textual descriptions, bridging the gap between natural language and graphic content.
Application Outlook
By application, the market is categorized into drug discovery, disease diagnosis & prognosis, clinical workflow, and others. In 2022, drug discovery registered the highest revenue share in the market. AI algorithms can analyze large-scale datasets resulting from high-throughput screening processes. This includes the analysis of cell cultures, histopathological images, and other data generated in drug discovery pipelines. The automation of analysis tasks expedites the identification of potential drug candidates. AI can examine the interactions between drugs and biological pathways. Understanding how drugs affect specific pathways in the context of disease pathology helps rationalize interventions and identify potential synergies or antagonisms.
End User Outlook
On the basis of end user, the market is classified into pharmaceutical & biotechnology companies, hospitals & reference laboratories, and academic & research institutes. The hospitals & reference laboratories segment covered a considerable revenue share in the market in 2022. AI supports the implementation of digital pathology, where glass slides are digitized for remote viewing and analysis. This facilitates collaboration, second opinions, and consultations among pathologists within the hospital or across different locations. AI is a decision support system for pathologists, providing real-time assistance during the diagnostic process. AI can be used for continuous learning and training programs for pathologists. Virtual simulations, interactive learning modules, and AI-assisted training contribute to ongoing professional development.
Component Outlook
On the basis of component, the market is segmented into software and scanners. The software segment acquired a substantial revenue share in the market in 2022. This significant share can be attributed to pathologists' widespread acceptance and utilization of AI-based software. High adaptability, interoperability, and the automation of a variety of pathology responsibilities, including image analysis, data extraction, and report generation, are a few of the benefits of the software segment. The adoption and development of AI software in pathology are propelled by these factors, which offer significant prospects for progress in disease detection, diagnosis, and treatment planning.
Regional Outlook
Region-wise, the market is analysed across North America, Europe, Asia Pacific, and LAMEA. The Asia Pacific region acquired a substantial revenue share in the market in 2022. The region's large and diverse patient population provides a wealth of data for training and validating AI algorithms. AI models in pathology benefit from the diversity of patient demographics and disease presentations, enhancing their generalizability. Collaboration between healthcare providers and technology companies, including those specializing in AI, accelerates developing and deploying AI solutions in pathology across the Asia Pacific region.
The leading players in the market are competing with diverse innovative offerings to remain competitive in the market. The above illustration shows the percentage of revenue shared by some of the leading companies in the market. The leading players of the market are adopting various strategies in order to cater demand coming from the different industries. The key developmental strategies in the market are Acquisitions, and Partnerships & Collaborations.
The market research report covers the analysis of key stake holders of the market. Key companies profiled in the report include Koninklijke Philips N.V., F. Hoffmann-La Roche Ltd., Hologic, Inc., Visiopharm A/S, Paige AI, Inc., PathAI, Inc., Aiforia Technologies Plc, Indica Labs, Inc., Optrascan, Inc. (Optra Ventures, LLC), MindPeak GmbH.
Recent Strategies Deployed in AI in Pathology Market
Partnerships, Collaborations & Agreements:
Oct-2023: F. Hoffmann-La Roche Ltd. has entered into a collaboration with Ibex Medical Analytics Ltd. to provide AI-powered solutions for cancer detection, along with the support of Amazon Web Services, Inc., a cloud service provider. This collaboration aims to give pathology laboratories access to Ibex's AI-driven decision support tools through the navify Digital Pathology software platform. Through this integration, clinicians can receive assistance in the diagnosis of breast and prostate cancer.
Sep-2023: Hologic, Inc. has partnered with Bayer AG to introduce contrast-enhanced mammography (CEM) solutions for improved breast cancer detection in European, Canadian, and Asia Pacific regions. The partnership aims to combine Bayer and Hologic's technologies to facilitate contrast media application in mammography examinations. The partnership focuses on providing radiologists with comprehensive product packages, hands-on training, and seamless integration of CEM into their workflows.
Jul-2023: Aiforia Technologies Plc and Orion Corporation, a Finnish pharmaceutical company, have entered into a collaboration to jointly create artificial intelligence (AI)-driven image analysis solutions for preclinical research and product development. Through this collaboration, Aiforia gains valuable insights from Orion regarding the specific needs of its preclinical customer base. This collaboration empowers Aiforia to refine and customize its product portfolio, ensuring a more targeted approach to meet the unique requirements of the preclinical research community.
Jun-2023: Visiopharm A/S has entered into a collaboration with Minerva Imaging, a preclinical Contract Research Organization (CRO) that specializes in molecular imaging services. Within this collaboration, the two companies will focus on developing AI-based image analysis applications in histology. The collaboration between Minerva and Visiopharm aims to expedite the creation of a toolbox for AI-driven precision pathology. This advancement will empower pharmaceutical companies to enhance clinical development by improving both quantitative and qualitative assessments, particularly in challenging-to-treat cancers.
Jun-2023: Visiopharm A/S has formed a partnership with Grundium Ltd., a well-known provider of high-quality imaging solutions for digital pathology. Through this partnership, the companies aim to broaden the accessibility of digital pathology solutions for clinics and laboratories globally. Within this partnership, Visiopharm will make Grundium's Ocus scanners available alongside its Qualitopix solution. This integration allows labs to automatically upload images for processing. The Qualitopix solution provides labs with the capability to improve staining quality and standardization by monitoring staining consistency.
Jun-2023: MindPeak GmbH has established a partnership with Proscia Inc., a U.S.-based provider of digital and computational pathology solutions. This partnership aims to provide closely integrated AI-powered workflows, supporting pathologists in making more efficient, informed, and reproducible clinical decisions. The goal is to broaden access to improved diagnoses for cancer patients.
Apr-2023: Optrascan, Inc. has formed a collaboration with Lumea Inc., a global leader in integrated digital pathology solutions. This collaboration combines Lumia's comprehensive digital pathology platform with diverse digital scanning solutions, aiming to facilitate the efficient and cost-effective adoption of digital pathology by providers.
Apr-2023: Indica Labs, Inc. and Lunit Inc., a medical software company, have entered into an agreement. As part of this agreement, the two companies will offer a completely interoperable solution, connecting Indica Labs' HALO AP image management software platform with Lunit's suite of AI pathology products. The Collaboration facilitates the smooth integration of Lunit's AI pathology solutions, including Lunit SCOPE PD-L1 designed for non-small cell lung cancer, into the HALO AP platform. It's worth noting that HALO AP holds CE-IVD certification as a clinical image management platform.
Apr-2023: PathAI, Inc. has partnered with ConcertAI LLC, a leading provider of AI software-as-a-service (SaaS) for life sciences and healthcare. The partnership aims to introduce an innovative solution that combines PathAI's PathExplore tumor microenvironment panel with ConcertAI's Patient360 and RWD360 products. This partnership will result in a groundbreaking quantitative histopathology and curated clinical real-world data (RWD) solution. The goal is to offer researchers access to a unique quantitative pathology dataset, allowing exploration beyond the limitations of small, controlled datasets. This includes identifying and analyzing novel histological biomarkers correlated with patient treatment and outcomes.
Mar-2023: Paige AI, Inc. has expanded its Partnership with Leica Biosystems Nussloch GmbH, a leading cancer diagnostics firm. The primary goal of this enhanced partnership is to further progress the adoption of digital pathology workflows across hospitals and laboratories worldwide. As part of this Partnership, Paige will provide software-as-a-service (SaaS) solutions for managing and viewing digital pathology images. Additionally, Paige will integrate various artificial intelligence (AI) solutions directly into the Aperio GT 450 digital pathology slide scanners within Leica Biosystems' product range.
Feb-2022: MindPeak GmbH and Crosscope Inc. have entered into an partnership, integrating MindPeak's image analysis tools into Crosscope's Digital Pathology platform. This partnership enhances Crosscope's AI capabilities, enabling them to provide comprehensive digital pathology solutions. By seamlessly integrating advanced AI tools, the partnership aims to optimize Histopathology workflows, supporting pathologists in improving lab efficiency and delivering timely and impactful diagnoses for ER, PR, and Ki-67 IHC stainings. The integration promises to positively influence patient treatment outcomes.
Oct-2021: F. Hoffmann-La Roche Ltd. and PathAI, Inc. have entered into an agreement to work on the development and distribution of an integrated image analysis workflow tailored for pathologists. Under this agreement, the objective is to jointly create a seamless workflow that incorporates PathAI's AI-powered image analysis algorithms into NAVIFY Digital Pathology, which is Roche's cloud-based iteration of the uPath enterprise software.
Aug-2020: Hologic, Inc. has entered into a collaboration with RadNet, Inc., a leading provider of high-quality outpatient diagnostic imaging services. The collaboration aims to promote the utilization of artificial intelligence (AI) in breast health. As part of this collaboration, RadNet plans to upgrade all its Hologic mammography systems to incorporate Hologic's 3DQuorum imaging technology, which is powered by Genius AI. This technology, working in conjunction with Clarity HD high-resolution imaging technology, significantly reduces tomosynthesis image volume for radiologists by 66 percent.
Product Launches & Product Expansions:
May-2022: Koninklijke Philips N.V. has introduced its state-of-the-art AI-driven enterprise imaging portfolio for complex clinical and operational tasks. Philips unveiled the MR 5300 imaging system, integrating AI-driven technologies designed to automate challenging clinical and operational tasks. This innovative technology from Philips empowers patients and healthcare professionals to harness the power of data for advanced analytics. This development sets the stage for a streamlined and precise diagnostic platform, enhancing both patient and healthcare provider experiences.
Mar-2022: Paige AI, Inc. has launched Paige Breast Lymph Node, an innovative AI medical software aiding pathologists in detecting the spread of breast cancer to lymph nodes. The product enhances efficiency and accuracy, utilizing AI to identify at-risk metastases, including small micrometastases, aiming for over 98% slide-level sensitivity. This advancement seeks to improve diagnostic accuracy for subtle metastatic foci.
Nov-2021: Hologic, Inc. has launched its newest product, the Genius Digital Diagnostics System, now available in Europe. This system integrates deep learning-based AI with advanced volumetric imaging technology to advance cervical cancer screening. The primary goal is to assist in detecting pre-cancerous lesions and cervical cancer cells in women. Using advanced image analysis, the system thoroughly evaluates each cell in a ThinPrep Pap test image, offering a comprehensive view of clinically relevant objects.
Oct-2021: Koninklijke Philips N.V. has introduced its newest digital pathology platform called IntelliSite, designed to cover the entire enterprise. IntelliSite includes a suite of scalable software tools aimed at enhancing workflows, increasing diagnostic confidence, promoting collaboration, incorporating artificial intelligence (AI), and enhancing the overall efficiency of pathology laboratories. Additionally, Philips emphasizes outstanding image quality and advanced algorithms that assist pathologists in both diagnosis and the development of care pathways.
May-2021: Optrascan, Inc. has launched CytoSiA, an intelligent solution for quick and cost-effective scanning and analysis of liquid-based cytology slides and Pap smears. CytoSiA includes OptraSCAN's digital pathology scanner, storage, and advanced AI algorithms, assisting pathologists in screening and detecting cervical cancer, pre-cancerous lesions, atypical cells, and various cytologic categories. It has been adopted globally by many hospitals and pathology labs, leading to improved patient outcomes, increased efficiency, and enhanced productivity in handling cytology cases.
Market Segments covered in the Report:
By Neural Network
By Application
By End User
By Component
By Geography
Companies Profiled
Unique Offerings from KBV Research