Samuel John 17:52 on Jul 30, 2024

Healthcare is a critically important area that constantly needs to evolve. Meanwhile, it relies not only on the expertise of medical professionals but also on advanced technologies. Cutting-edge tools assist with a wide range of tasks, from everyday administrative functions to vital processes such as diagnostics, treatment, and surgery. Computer vision in healthcare is leveraging the power of AI to enhance medical care and patient outcomes. 

Healthcare institutions, technology companies, and research organizations are seeking to pool resources and corporate. Such cooperation fosters knowledge exchange and drives innovation in computer vision applications.

This article reveals major computer vision applications in healthcare and their benefits for patients and medical professionals. For a deeper dive into the subject, you can explore this guide from OpenCV.ai about AI in health and personalized medicine.

Medical imaging for precise and efficient diagnostics

Medical image analysis is one of the most significant applications of computer vision in healthcare. It has a direct impact on the accuracy, efficiency, and speed of diagnostics. This is especially vital for complex and severe diseases where early detection is crucial. AI algorithms can analyze different types of medical images. These are X-rays, CT scans, MRIs, ultrasound scans, ophthalmic and dermatological images, endoscopy and fluoroscopy videos, and more.

Traditional analysis methods are time-consuming and require manual examination of each image. Moreover, the specialist may not see what the computer sees. For example, Google Health has developed an AI model for breast cancer detection. In their study, they used 28,000 mammograms. Their algorithm reduced false positive results by 5.7% and false negatives by 9.4% compared to radiologists. This result highlights the value of computer vision for improving diagnostic accuracy and reliability.

Transformative approach in surgery for better outcomes 

Computer vision in surgical practices revolutionizes the planning and execution of surgeries. Technology can enhance the precision, safety, and efficiency of operations. We can define the following key applications of computer vision in surgery:

• Training of surgeons: In combination with Virtual Reality (VR), computer vision creates realistic surgical simulations. Surgeons can practice complex procedures in a controlled environment. Such a system tracks all their movements and provides feedback for efficient training.
• Monitoring during operations: Computer vision systems can analyze video streams to detect abnormalities and potential threats right during operations. In real-time, they alert the surgical team about issues like excessive bleeding or unintended tissue damage.
• Robotic surgery: Computer vision is a part of robotic surgery systems and is responsible for advanced imaging techniques. It provides high-fidelity 3D visuals of human anatomy. Operators can control the movement of instruments during procedures with greater precision. In addition, these robots can automate certain surgical tasks, such as suturing and other simple manipulations.

Health monitoring for more efficient patient care

Computer vision is expanding the abilities of health monitoring both at the facility and at home. In intensive care units (ICUs), it can detect vital signs and changes in patient conditions, sending real-time alerts to healthcare providers. This immediate feedback is crucial for timely interventions. The result is potentially saving lives and improving patient outcomes.

With remote patient monitoring medical care has become more accessible. Patients can undergo examinations at home. Just need devices with cameras. Computer vision applications analyze their movements and appearance. The state of skin, eyes, ears, and everything that the therapist can assess online visually. It’s a good assistance in diagnosis, enhancing the quality of remote consultations.

There are a variety of examples. The application can see subtle changes in a patient’s skin that might indicate the onset of infections. Eye images can show signs of diseases like diabetic retinopathy or glaucoma early on. Analyzing facial expressions and body movements app can detect symptoms of disorders such as Parkinson’s disease or epilepsy.

Extended capabilities of medical research

This advantage mainly relates to the pharmaceutical sector. Computer vision can be involved in their two main processes. These are drug discovery and clinical trials.

In drug discovery, the system conducts fast and accurate analyses of cell cultures, tissue samples, and other biological data. High-throughput screening (HTS) involves thousands to millions of compounds to identify potential drug candidates. Computer vision can detect changes at the cellular level, identify active compounds, and evaluate their effectiveness. That significantly accelerates and improves the discovery process. 

Thus, McKinsey report stated that AI has been shown to increase the performance of chemical compound activity models by up to 2.5 times and reduce the time needed to identify new leads from months to weeks according 

Clinical trials also benefit from advanced analyses. Based on the large volumes of medical profiles, computer vision can identify suitable candidates with specific disease characteristics. It improves the validity of trials and reduces the time required for recruitment. Clinicians can get more efficient trials, ultimately speeding up the development of new treatments.

Patient identification and enhanced safety

Computer vision technology has big potential for safety, in our case within medical facilities. Computer vision systems can utilize facial recognition to accurately identify patients, ensuring that their medical records are correctly matched. This reduces the risk of incorrect treatments or medications due to misidentification. Obviously, such mistakes are extremely harmful to health. But they also lead to financial and reputational losses for the institutions.

Another example is compliance with safety protocols. The system can monitor whether all healthcare workers are wearing the appropriate personal protective equipment (PPE) and following hygiene practices. This helps to reduce related risks. In general, it can send alerts about unwelcome events, ensuring immediate response.

Final words

The future of computer vision projects in healthcare is shaped by advancements in AI and the integration of emerging technologies. These developments are set to enhance diagnostics, treatment, and patient care significantly. As AI algorithms evolve, they will provide more accurate and faster medical image analysis, enabling complex diagnoses.

Robotic systems with AI and 3D computer vision will offer surgeons greater precision and control, expanding their capabilities across various surgical procedures. Computer vision also can be integrated with wearable devices, offering enhanced patient monitoring. This enables continuous tracking of vital signs and early detection of health issues. Together, all these tools create a more efficient patient-centric system.