One of the most promising and rapidly advancing healthcare technologies is computer vision. In the case of medical images and videos, it's the application of artificial intelligence (AI) algorithms to analyse these images and videos to help clinicians make faster, more accurate diagnoses and better treatment decisions. The global computer vision in healthcare market size is projected to reach USD 15.86 billion by 2030, from a reported value of USD 2.6 billion in 2024, at a CAGR of 23.2%.
Applications of computer vision span across healthcare, including medical imaging analysis and robotic surgery assistance. This article explores the top 5 major use cases that are driving adoption and seeing the most impact currently:
- Automated Analysis of Medical Imaging
- Assisted and Robotic Surgery
- Early Disease Detection and Diagnosis
- Patient Monitoring and Care
- Health Data Analytics
For each use case, we will analyse key applications, benefits provided, major players and innovations, market outlook and future growth opportunities. By understanding these top use cases, healthcare providers, medical technology companies, investors, and young startups can understand where computer vision technology can add the most value in terms of improving patient outcomes.
Use Case #1: Automated Analysis of Medical Imaging
Medical imaging like X-rays, CT scans, MRI scans and ultrasound imaging generate a vast amount of visual data that physicians must analyse to detect issues and diseases. Manual analysis is tedious, time-consuming, and prone to error and fatigue of the human. The analysis of anatomical scans can be automated using computer vision algorithms to quantify biomarkers rapidly and provide insights that can help clinicians make faster and more accurate diagnoses.
More info about computer vision development from professionals: https://spd.tech/computer-vision-development-services/.
Key Applications:
- Quantifying lung damage from diseases like pneumonia or COVID-19
- Identifying malignant tumours and measuring growth over time
- Diagnosing eye diseases from retinal scans
- Detecting fractures, foreign objects or anatomical abnormalities
Benefits:
- Faster and more consistent analysis of scans
- Reduces radiologist workload and burnout
- Enables more preventative screening
- Assists less experienced clinicians
Major Players & Innovations:
- Arterys - FDA-cleared solutions for cardiac MRI and CT scan analysis
- Zebra Medical - Algorithms for bone health, liver lesions, lung nodules
- Enlitic - Detects fractures from X-rays with over 99% accuracy
- VUNO - Analyses CT scans to quantify COVID-19 lung damage
- Quibim - Quantifies biomarkers of cancer, liver disease and more
Market Outlook:
- The medical imaging analysis software market is expected to reach $6.6 billion by 2028 (CAGR of 11.4%)
- Increasing adoption of quantitative imaging biomarkers in oncology, neurology, cardiology, etc.
Future Opportunities:
- Expanding analysis from individual images to video feeds from endoscopies, surgeries, etc.
- Leveraging AI to generate synthetic scans for comparison to real scans
- Integrating computer vision insights directly into clinical workflows and EHRs
- Expanding from diagnostic assistance to also providing treatment insights
Use Case #2: Assisted and Robotic Surgery
The visual analysis of a surgeon is dependent on surgery. For instance, computer vision can help it by processing surgical microscopes and endoscope video feeds. It enables AI algorithms to follow the surgical field, anatomical structures and medical tools so surgeons can be better visualised, get alerted when potential problems arise and be aided semi-automatically.
Key Applications:
- Augmented reality surgery navigation overlays on goggles/scopes
- Tremor cancellation - stabilise images to offset natural hand-shaking
- Automate camera positioning and zoom-in/out functions
- Detect bleeders and anatomical structures for the surgeon
- Enable shared live-stream viewing of surgeries for training
Benefits:
- Improves accuracy and minimises risks in complex, long surgeries
- Expands access to top surgeons through remote expertise-sharing
- Consistent visualisation reduces mental fatigue for surgeons
- Democratises surgical expertise for less experienced surgeons
Major Players & Innovations:
- Intuitive Surgical - Autonomous camera control and enhanced visualisation for da Vinci robotic surgery systems
- Augmedics - xvision Spine System utilises AR for accurate placement of implants using 3D CT overlay
- Medtronic - AI-assisted surgical video capture and analytics for procedural insights
- Caresyntax - Surgical activity recognition and workflow analytics for operating rooms
- Activ Surgical - AI-based intraoperative risk detection and surgical video management
Market Outlook:
- The global surgical robotics market is projected to reach $188 billion by 2030 (CAGR of 20.5%)
- The surgical data analytics and visualisation software market is poised for a 6.5% CAGR
Future Opportunities:
- Fully autonomous robotic surgery systems
- Integration of pre-op medical imaging, surgical plans and patient vitals into unified AR views
- Predictive analytics to alert surgeons of potential intraoperative and post-op complications
- Automated video indexing and analytics of surgeries at a massive scale for insights
Use Case #3: Early Disease Detection and Diagnosis
Finding diseases early significantly raises the chances of successful treatment and recovery. However, many devastating diseases display subtle early warning signs that the human eye can miss. Computer vision analysis applied to medical scans and physical patient images/videos can often detect anomalies at the earliest stages, enabling early intervention.
Key Applications:
- Identify malignant lesions and microcalcifications in mammograms
- Detect diabetic retinopathy conditions from retinal scans
- Surface abnormalities in skin images that may indicate cancer
- Subtle gait changes, tremors and physical signs from the patient video
- Ophthalmology - detect eye diseases from anterior/posterior eye scans
Benefits:
- Improves early detection beyond human visualisation limitations
- Enable low-cost mass screening to expand patient access
- Detect conditions before patients themselves notice any symptoms
- Dramatically increases treatment success rates of cancers, blindness, etc.
Major Players & Innovations:
- Lunit Insight - Detect cancers from chest X-rays with 97% accuracy
- Viz.ai - Identify stroke biomarkers in CT scans in under 6 minutes
- MobileODT - Cervical cancer screening integrated with colposcope devices
- Caption Health - Detects cardiac abnormalities using ultrasound AI.
- IDx-DR - Autonomous AI diagnostic system for diabetic retinopathy
Market Outlook:
- Global AI in medical imaging market to reach $20 billion by 2031
- Significant cost savings - up to $630 billion in the U.S. alone through early cancer detection
Future Opportunities:
- Expanding screening programmes to broader demographics and conditions
- Fusing visual data with genomic family history for composite risk analysis
- Low-cost at-home screening devices (IoT, wearables, mobile) with computer vision algorithms
- Longitudinal analysis across historical patient images to predict risk trajectories
Use Case #4: Patient Monitoring and Care
Hospitals and senior care facilities require constant patient monitoring, which is expensive, labour-intensive, and limited in capacity. Computer vision offers the scalability to remotely monitor many patients simultaneously. Algorithms can analyse both live and recorded video feeds to detect patient issues or risky situations without requiring bedside staff intervention.
Key Applications:
- Fall detection in hospitals, homes and senior facilities
- Identify high-risk situations like patients leaving beds unattended
- Monitor patients for pain, agitation and other signs needing attention
- Analyse gait and mobility to assess rehabilitation progress
- Detect secondary health events like pressure injuries before they escalate
Benefits:
- 24/7 automated monitoring without added staff
- Rapid emergency response times and proactive interventions
- Reduces patient sitter costs
- Earlier hospital discharge while still monitoring at home
- Optimises staff allocation and enhances caregiver productivity
Major Players & Innovations:
- DeepMind - Algorithms to detect acute kidney injury from medical records
- TensorMark - In-hospital patient, staff and equipment tracking
- CarePredict - Wearables with fall detection and insight analytics
- Qventus - Optimises patient care operations and nurse workflows
- Perceptive Vision - Fall risk analysis integrated with nurse call systems
Market Outlook:
- The patient monitoring market is projected to reach $88.9 billion by 2030
- High demand from cost pressures and aging global demographics
Future Opportunities:
- Expanding to wearables, in-home cameras and ambient IoT sensors
- Combined analysis with electronic health records (EHRs)
- Predictive analytics to detect risks and deterioration trajectories
- Voice analysis to assess mood, pain levels and conversational health
Use Case #5: Health Data Analytics
The healthcare industry produces massive amounts of unstructured data from medical images, lab tests, genomics sequencing, doctor notes and more. This data holds invaluable insights, but analysing it all is impossible for humans. Computer vision and AI solutions can extract insights at a massive scale - from personalised care to public health policy.
Key Applications:
- Population health analysis of medical images for research studies
- Anonymised analysis of X-rays CT scans for disease identification
- Medical claims analysis to detect fraud, errors and abuse patterns
- Automated extraction of insights from doctor notes, clinical trial data
- Analyse microscopy images to accelerate pharmaceutical R&D
Benefits:
- Rapid analysis of terabytes of medical data that is impossible manually
- Uncover public health insights from the general population
- Accelerate clinical trials and scientific breakthroughs
- Identify billing errors and fraudulent claims, saving millions
- Personalise care pathways based on insights from similar patients
Major Players & Innovations:
- PathAI - Research lab for disease detection in cell and tissue samples
- Seqster - Finds medically relevant genetic variants from genome datasets
- Zebra Medical - 10 billion medical images annotated by algorithms
- Arterys - Biobank of 40,000+ cardiac MRI scans for research
- Qventus - Optimises health system operations using AI-based analytics
Market Outlook:
- Health data analytics market to reach $168 billion by 2030
- High demand from pharma R&D, public health agencies, health systems
Future Opportunities:
- Federated learning for privacy-preserved shared analytics
- Hybrid analysis across imaging, EHR and genomic data sources
- Blockchain-based health data exchanges to further pool datasets
- Causal analysis to derive personalised treatments from insights
Conclusion
Computer vision has demonstrated tremendous potential to solve critical problems across modern healthcare - from enhancing diagnoses and surgeries to enabling proactive monitoring and unlocking data insights. As algorithms continue to advance in accuracy, adoption by healthcare providers is accelerating rapidly.
Incumbent healthcare companies, insurers, medical device firms and startups are all investing heavily in this technology. Computer vision will increasingly provide physicians with a scalable 'extra set of eyes' while also benefiting patients through more affordable, accessible and early testing. Exciting innovations lie ahead as researchers expand this artificial intelligence into new frontiers like robotic surgery, early disease detection and health data analytics at population scale.
This article is part of the HealthManagement.org Point-of-View Programme.
