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市場調查報告書

醫療圖像分析人工智能 (AI):行動提醒 (CTA) 2018年

Artificial Intelligence for Medical Image Analysis - Companies-to-Action, 2018

出版商 Frost & Sullivan 商品編碼 689267
出版日期 內容資訊 英文 119 Pages
商品交期: 最快1-2個工作天內
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醫療圖像分析人工智能 (AI):行動提醒 (CTA) 2018年 Artificial Intelligence for Medical Image Analysis - Companies-to-Action, 2018
出版日期: 2018年08月21日 內容資訊: 英文 119 Pages
簡介

本報告以在醫療圖像分析人工智能 (AI) 市場上活動的企業為焦點加以分析,提供 嚐試開發、上市醫療圖像分析AI型解決方案的企業,供應商注目的模式·內臟器官·疾病領域,競爭·合作等動向,創新的企業之獨家方法·利用案例等調查。

第1章 摘要整理

第2章 行動提醒 (CTA) :概要

第3章 醫療圖像分析的人工智能 (AI) :市場概要

  • 醫療圖像的AI的利用案例
  • 調查簡介
  • 影像鏈中AI型分析的應用
  • 醫療圖像AI技術的炒作循環
  • AI型影像分析多元使用概況
  • 醫療圖像AI的價值命題:主要相關利益者

第4章 醫療圖像分析的人工智能 (AI) :生態系統·競爭情形

  • 醫療圖像AI:競爭情形
  • 醫療圖像AI生態系統的動態發展
  • 醫療圖像AI上新興企業的創設時間軸
  • 新興企業數量連貫增加
  • 醫療圖像AI開發的主要里程碑
  • 重要的監管批准里程碑
  • 持續學習,下一個監管境界
  • 數位病理AI
  • AI型內視鏡影像分析,急速成長的領域

第5章 醫療圖像分析的人工智能 (AI) :地區模式

  • 各國的各種AI獎勵·願景
  • 全球醫療圖像AI解決方案的發展
  • 醫療圖像AI企業的全球性擴展
  • 分析:前2名國家、其他地區

第6章 醫療圖像分析的人工智能 (AI) :新興企業的資金趨勢

  • 全球資金來源
  • 全球資金來源的相關討論
  • 全球投資目標
  • 全球投資目標的相關討論

第7章 醫療圖像分析的人工智能 (AI) :環境評估

  • 主要的臨床用途領域
  • 主要的臨床用途領域的相關討論
  • 目標的疾病領域
  • 目標的內臟器官
  • 疾病·內臟器官的焦點相關討論
  • 顯像模式的焦點
  • 顯像模式的焦點的相關討論、其他

第8章 行動提醒 (CTA)

  • 影像AI的開發:主要影像各供應商
  • 對影像設備OEM的前四大公司:AI的著重度
  • 醫療圖像分析的IBM Watson Health
  • Aidoc
  • Arterys
  • Brainomix
  • Enlitic
  • EnvoyAI
  • Huiying Medical Tech Co.
  • IDx
  • Imagen Technologies
  • MaxQ-AI (formerly MedyMatch Technology)
  • Quantitative Insights
  • Riverain Tech
  • Viz.AI
  • Vuno

第9章 成長機會

第10章 展望:AI型醫療圖像分析的10大預測

第11章 附錄

第12章 FROST & SULLIVAN

目錄
Product Code: K27C-50

Lay of the Land, Growth Opportunities and Future Direction

Medical imaging has become the bellwether application for artificial intelligence (AI) technologies in healthcare. From deep learning and machine learning approaches, to cognitive computing, to even natural language processing, several AI approaches are now being incorporated in the field of radiology. Apart from academic research groups, almost all major manufacturers and vendors in the medical imaging space have or are developing initiatives to bring automation, augmentation or acceleration to medical imaging, cognitive computing for imaging informatics applications and even intelligent machines. There are several startups as well which continue to advance the development of solutions.

In the medical imaging workflow, from ordering of imaging studies all the way up to follow-up post imaging, artificial intelligence could play a role. Of course, current efforts are mostly concentrated in analyzing the medical images. These solutions have been deployed on premises, but there is a gradual adoption of cloud technologies too. As applications evolve and are developed further, AI is moving to the edge, and might also become embedded in imaging equipment as the next frontier. However, at the global level, countries look up to AI to address very different and systemic challenges - while some such as the United States require higher productivity and standardization, the United Kingdom needs to address shortages and higher wait time, whereas others such as China need it to build access and expertize to improve diagnosis rates. This has naturally resulted in a continuous growth in the number of startups emerging in this field, globally. Funding too, has flowed in to support the momentum. Crucial regulatory milestones have been achieved, but many more are likely to be reached as well.

This study is a focused analysis to highlight all of the companies active in this space, and to analyze their solutions to get a sense of the trends in the industry. Aptly called the Companies-to-Action, a comprehensive analysis of ~100 AI companies currently offering medical image analysis solutions provides an in-depth insight in to several key questions, as outlined below. Competitive landscape, evolving partnerships, regional analysis to identify conducive factors for development of AI solutions, funding trends for the 80+ startups, a landscape assessment, and finally, a list of top ten predictions for the coming 5 years are covered in this study. It also highlights a curated list of companies along with our perspective on their uniqueness, potential opportunities, and threats.

Key Issues Addressed:

  • Who are the companies that have set out to develop and commercialize artificial intelligence-based solutions for medical image analysis?
  • Which modalities, organs and disease areas have vendors focused on during the inception phase 2011-2018?
  • What kind of competitive and partnership dynamics are taking place across the vendor, provider and investor ecosystems?
  • What are some unique approaches and use cases addressed by some of the most innovative companies vested in AI-based medical image analysis?
  • How do various regions fare in the adoption of, and investment in AI based technologies for medical image analysis?

Table of Contents

1. EXECUTIVE SUMMARY

  • Key Findings
  • Key Findings (continued)
  • Key Findings (continued)
  • Scope and Segmentation
  • Key Questions this Study will Answer

2. COMPANIES-TO-ACTION OVERVIEW

  • Companies-To-Action (C2A) Value Creators
  • Threats & Opportunities
  • Study Methodology

3. ARTIFICIAL INTELLIGENCE IN MEDICAL IMAGE ANALYSISMARKET OVERVIEW

  • Medical Imaging AI Use Cases
  • Study Introduction
  • Application of AI-Based Analysis Across the Imaging Chain
  • Application of AI-Based Analysis Across the Imaging Chain (continued)
  • Medical Imaging AI Technology Hype Cycle
  • Diverse Usage Scenarios for AI-Based Image Analysis
  • Diverse Usage Scenarios for AI-Based Imaging Analytics
  • Medical Imaging AI Value Propositions to Key Stakeholders
  • Medical Imaging AI Value Propositions to Key Stakeholders (continued)

4. ARTIFICIAL INTELLIGENCE FOR MEDICAL IMAGE ANALYSIS ECOSYSTEM & COMPETITIVE LANDSCAPE

  • Medical Imaging AI Competitive Landscape
  • Developing Dynamics in the Medical Imaging AI Ecosystem
  • Developing Dynamics in the Medical Imaging AI Ecosystem (continued)
  • Timeline of Founding of Medical Imaging AI Start-ups
  • Consistent Growth in Start-up Numbers During 2009-2017
  • Timeline of Industry-Firsts For Medical Imaging AI Start-ups
  • Select Milestones in Medical Imaging AI Development
  • Select Significant Regulatory Approval Milestones
  • Continuous Learning, the Next Regulatory Frontier
  • Digital Pathology AI, a Tangential Area to Medical Imaging AI
  • AI-Based Endoscopy Image Analysis a Burgeoning Field

5. GEOGRAPHICAL PATTERNS FOR ARTIFICIAL INTELLIGENCE IN MEDICAL IMAGE ANALYSIS

  • Different Incentives and Vision for AI Across Countries
  • Global Deployments of Medical Imaging AI Solutions
  • Global Spread of Medical Imaging AI Companies
  • Regional Analysis-Top Two Countries
  • Regional Analysis-Top Two Countries (continued)
  • Regional Analysis-Next Two Countries
  • Regional Analysis-Next Three Countries
  • Regional Analysis-Emerging Hotbeds

6. FUNDING TRENDS FOR ARTIFICIAL INTELLIGENCE IN MEDICAL IMAGE START-UPS

  • Global Funding Sources for Medical Image Analysis AI
  • Global Funding Sources for Medical Image Analysis AI-Discussion
  • Global Targets for Medical Image Analysis AI Investments
  • Global Targets for Medical Image Analysis AI Investments-Discussion

7. ARTIFICIAL INTELLIGENCE IN MEDICAL IMAGE ANALYSISLANDSCAPE ASSESSMENT

  • Top Clinical Application Areas
  • Top Clinical Application Areas-Discussion
  • Target Disease Areas
  • Target Organs
  • Disease and Organ Focus-Discussion
  • Imaging Modality Focus
  • Imaging Modality Focus-Discussion
  • Overlaps in Imaging Modality Focus
  • Overlaps in Imaging Modality Focus-Insights

8. COMPANIES-TO-ACTION

  • Imaging AI Developments by Major Imaging Vendors
  • Top 4 Imaging Equipment OEMs by Intensity of AI Efforts
  • IBM Watson Health in Medical Image Analysis
  • Aidoc
  • Aidoc (continued)
  • Arterys
  • Arterys (continued)
  • Brainomix
  • Brainomix (continued)
  • Enlitic
  • Enlitic (continued)
  • EnvoyAI
  • EnvoyAI (continued)
  • Huiying Medical Tech Co.
  • Huiying Medical Tech Co. (continued)
  • IDx
  • IDx (continued)
  • Imagen Technologies
  • Imagen Technologies (continued)
  • MaxQ-AI (formerly MedyMatch Technology)
  • MaxQ-AI (formerly MedyMatch Technology) (continued)
  • Quantitative Insights
  • Quantitative Insights (continued)
  • Riverain Tech
  • Riverain Tech (continued)
  • Viz.AI
  • Viz.AI (continued)
  • Vuno
  • Vuno (continued)

9. GROWTH OPPORTUNITIES

  • 5 Major Growth Opportunities
  • Strategic Imperatives for AI Medical Image Analysis Solutions

10. OUTLOOK-TOP TEN PREDICTIONS FOR AI-BASED MEDICAL IMAGE ANALYSIS

  • Top 10 Predictions for 2018-2022
  • Top 10 Predictions for 2018-2022(continued)
  • Legal Disclaimer

11. APPENDIX

  • Imaging Modality Focus for Medical Imaging AI Companies
  • Which Modalities have been Tackled by Imaging AI Vendors?
  • Coverage of Companies
  • Universe of Medical Image Analysis AI Companies
  • Universe of Imaging Modality Companies
  • Universe of Clinical Specialty Focus Companies
  • Universe of Disease Focus Companies
  • List of Exhibits
  • List of Exhibits (continued)
  • List of Exhibits (continued)

12. THE FROST & SULLIVAN STORY

  • The Frost & Sullivan Story
  • Value Proposition-Future of Your Company & Career
  • Global Perspective
  • Industry Convergence
  • 360° Research Perspective
  • Implementation Excellence
  • Our Blue Ocean Strategy
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