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In today’s healthcare industry, digital transformation and innovative technologies are actively implemented. Business Wire estimates the global digital health market will grow from $183.30 billion in 2020 to $201.24 billion in 2021, growing at a compound annual growth rate (CAGR) of 9.79%. Computer Vision (CV) is an example of such a tool that can help healthcare professionals provide better medical care and make medicine more affordable and accessible.

How does Computer Vision affect the healthcare industry?

Artificial Intelligence focuses on Computer Vision, which helps to analyze and understand images and videos. The concept of CV is based on intelligent computer algorithms that train machines to see the world visually and provide valuable insights.

Approximately 90% of all health information is composed of image information, according to Engineer researchers. It means that computer vision algorithms can be used to improve the efficiency of medical personnel and improve the quality of patient care in the healthcare industry.

As a result of automating processes based on image recognition, routine tasks will also be performed by machines without human intervention. Therefore, this method will help eliminate errors caused by fatigue and inattention of doctors and allow them to focus on more complex problems.

In what ways can Computer Vision be used in healthcare?

Computer Vision is used in a wide variety of medical fields today, making significant contributions to healthcare. Where does CV find application in healthcare?

    Detecting organ damage

    Algorithms used in imaging can detect abnormalities or damage to organs. Medical professionals can use Computer Vision to identify fractures, dislocations, and soft tissue injuries and quickly and effectively relieve patients from pain.

  Computer Vision algorithms are extending the capabilities of radiologists and making medical image interpretation cheaper, faster, and more accurate. In addition, this approach is much safer for patients since it limits their exposure to radiation.

    Oncology identification

    Healthcare professionals can identify cancerous cells and tumors at an early stage with the help of algorithms for analyzing medical images. The use of computer diagnostics can detect malignancies such as lung cancer, breast cancer, and prostate cancer.

    Virtual biopsies have the advantage of being accurate, cost-effective, convenient for patients, and quick to complete. By utilizing CV algorithms, patients have a greater chance of surviving and recovering from their injuries.

    Heart disease analysis

    Using Computer Vision techniques in cardiology, medical specialists can:

  1. Implement automated segmentation for MRI, PET, and SPECT scans, as well as ultrasound (US);
  2. Examine cardiac images;
  3. Predict how heart disease will develop.

    By using imaging algorithms, you can diagnose cardiac pathology early and detect anomalies, as well as develop new treatments.

    Furthermore, Computer Vision systems play an important role in cardiology education. The explanation of surgery procedures becomes easier and more understandable with the aid of visualization tools.

    The implementation of Computer Vision includes the use of a cardiology platform for ECG digitization to facilitate the exchange of information and professional experience among cardiologists.

    The software solution allows the digitization of a graphical scanned ECG into a digital data storage format without losing any diagnostic information.

    In this way, the platform facilitates the exchange of information about heart examinations so that doctors can seek recommendations from colleagues or perform additional automatic or manual analyses.

    Dermatological examination

    Using high-precision computer diagnostic systems, doctors can analyze the condition of a patient’s skin and make better decisions.

    The computerized analysis of skin images ensures personalized skincare, including recommendations for makeup, creams, and gels. Computer Vision can also identify skin diseases and recommend treatment options.

    Testing in laboratories

    In addition to blood analysis, tissue cell evaluation, and other laboratory tests, Computer Vision algorithms are also used. A special camera is attached to a conventional microscope in order to conduct such an analysis.

    Computer vision technology is used to examine the resulting photos and automatically detect certain anomalies in the blood samples.

    Through automated image analysis, doctors can perform laboratory tests more quickly and get a better understanding of a person’s health.

The Computer Vision industry is growing today, CV image analysis is used in a variety of medical fields, which is undeniably beneficial to patients and medical specialists.

Medical research is more accurate and reliable when using Computer Vision, doctors are able to work faster, and hospital costs are reduced. Additionally, these technologies are constantly improving, which will lead to new opportunities for Computer Vision and, as a result, to better medical care.

 

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