Medical image analysis is the computational analysis of medical images, most commonly with computed tomography (CT) and magnetic resonance imaging (MRI). There are many different types of medical images, such as diagnostic radiographs, fluoroscopic images, and ultrasound images. These differ in how they are acquired and what information they contain. Medical image analysis involves using computer algorithms to process these images for the purpose of diagnosing or monitoring a patient’s health status.
Process
It typically involves three steps:
1) collecting data;
2) analyzing the data;
3) communicating the findings.
Since images are often complex, exhaustive data collection is necessary to understand the problem at hand.
The next step involves identifying features in the image, such as pixels of a certain color or intensity level.
Finally, you must communicate your findings in an organized fashion to healthcare professionals, who will use them to diagnose patients or find solutions for issues relating to their care.
When medical images are acquired, raw data is obtained from CT scans or MRIs. That data is then processed into a format that software can use to create 3D images of the body.
The process of medical image processing begins when raw data is collected and converted into a format that software can read and use. A grid of colored pixels (voxels) forms the basis for the medical image processing.
Importance
Many areas of healthcare, including but not limited to neurology, cardiology, orthopaedics, dentistry, and oncology, benefit from medical image analysis solutions. They can read images produced by X-rays, MRIs, CT scans, PET scans, and ultrasounds. As a result, there is an opportunity for automation and acceleration of tasks that would otherwise take a long time to complete manually.