Knee Injury Research Paper

1.1 Overview Of Knee Injury

Knee organ is the largest joint in the human body, specifically in the leg and it is the easiest part of the body to be injured. Knee injuries can be caused by a sudden injury, an overused injury or by an underlying condition. The treatment depends on the cause and type of injury. Early symptoms of knee injury can include pain, swelling, and stiffness. Most people have had a minor knee problem at one time or another. Most of the time, normal body movements do not incur injuries. As a result, knee injuries are common in sports such as soccer, football, and basketball, most of which involve frequent sudden stop movements among athletes.

The Anterior Cruciate Ligament (ACL) has been studied in many different ways

Conservative treatment includes RICE (rest, immobilization, compression bandage and elevate) and pain- killers. Physiotherapy in the form of exercises, electrotherapy modalities, knee braces and sports taping can also aid in recovery. Operative management includes arthroscopic evaluation and specific treatment of individual pathology. Meniscus injuries can result in excruciating pain and locking of the joint. Clinical test can lead to provisional diagnosis of the meniscal injuries. Magnetic Resonance Image (MRI) will confirm the diagnosis. Whenever possible, that is, if the tear can be seen through light

Extract several features from knee Magnetic Resonance Image (MRI) for diagnosis.

3. Design artificial intelligent (AI) system to diagnosis injury type complies with a medical expert opinion.

This comprises a set of potentially useful features that are likely to be visible on knee radiographs and can be represented in a form suitable for machine learning (e.g. as categorical or numerical variables). Although other features such as the presence of sacral fracture are important in diagnosing knee injury, radiographs may not provide sufficient detail. This information is instead more likely to be obtained using a separate CT image analysis component.

It is vital to remember that the methods developed for these tasks must be fully automated if they are to be of use in a computerized anterior cruciate ligament (ACL) for knee injury. Furthermore, since different structures will be analyzed for different visual characteristics, segmentation must be performed before any other analysis can take place. This creates the need for an automated segmentation approach able to handle pathological cases and the complications inherent in magnetic resonance imaging, which will be described in Chapter