Healthcare

Vision Apps are used across wide range of industries to reduce defects, improve quality, maximize efficiencies, lower costs – and even save lives.

Cancer Detection

Vision applications and machine learning are used widely throughout the medical field, particularly in areas such as breast and skin cancer detection. For instance, image recognition allows scientists to detect slight differences between cancerous and non-cancerous images and diagnose data from magnetic resonance imaging (MRI) scans and photos.

COVID-19 diagnosis

Computer Vision can be used for coronavirus control. Multiple deep learning computer vision models exist for x-ray based COVID-19 diagnosis. The most popular one for detecting COVID-19 cases with digital chest x-ray radiography (CXR) images is named COVID-Net and was developed by Darwin AI, Canada.

Cell Classification

Machine Learning in medical use cases was used to classify T-lymphocytes against colon cancer epithelial cells with high accuracy. Thus, ML is expected to significantly accelerate the process of disease identification regarding colon cancer efficiently and at little to no cost post-creation.

Movement Analysis

Neurological and musculoskeletal diseases such as oncoming strokes, balance, and gait problems can be detected using deep learning models and computer vision even without doctor analysis. Pose Estimation computer vision applications that analyze patient movement assist doctors in diagnosing a patient with ease and increased accuracy.

Mask Detection

Masked Face Recognition is used to detect the use of masks and protective equipment to limit the spread of coronavirus. Likewise, computer Vision systems help countries implement masks as a control strategy to contain the spread of coronavirus disease.

For this reason, private companies such as Uber have created computer vision features such as face detection to be implemented in their mobile apps to detect whether passengers are wearing masks or not. Programs like this make public transportation safer during the coronavirus pandemic.

Tumor Detection

Brain tumors can be seen in MRI scans and are often detected using deep neural networks. Tumor detection software utilizing deep learning is crucial to the medical industry because it can detect tumors at high accuracy to help doctors make their diagnoses.

New methods are constantly being developed to heighten the accuracy of these diagnoses.

Disease Progression Score

Computer vision can be used to identify critically ill patients to direct medical attention (critical patient screening). People infected with COVID-19 are found to have more rapid respiration.

Deep Learning with depth cameras can be used to identify abnormal respiratory patterns to perform an accurate and unobtrusive yet large-scale screening of people infected with the COVID-19 virus.

Healthcare and Rehabilitation

Physical therapy is important for the recovery training of stroke survivors and sports injury patients. The main challenges are related to the costs of supervision by a medical professional, hospital or agency.

Home training with a vision-based rehabilitation application is preferred because it allows people to practice movement training privately and economically. In computer-aided therapy or rehabilitation, human action evaluation can be applied to assist patients in training at home, guide them to perform actions properly, and prevent further injuries.

Medical Skill Training

Computer Vision applications are used for assessing the skill level of expert learners on self-learning platforms. For example, simulation-based surgical training platforms have been developed for surgical education.

In addition, the technique of action quality assessment makes it possible to develop computational approaches that automatically evaluate the surgical students’ performance. Accordingly, meaningful feedback information can be provided to individuals and guide them to improve their skill levels.

Transportation
Learn how Vision Apps are transforming the transportation industry!

Automotive companies and their suppliers are increasingly using vision technologies to fundamentally transform the automotive industry. Indeed, driverless cars, visual tracking and visual route mapping are just a few of the countless opportunities that existing for vision apps in the Transportation industry - learn more!

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