A CT (computerized tomography) scan combines several X-rays taken from different angles and uses computer processing to create a cross-sectional image of bones, soft tissues, and organs in the human body. A CT scan provides far superior images than regular x-rays and thus allows for better diagnosis and treatment of patients.
CT open data provides doctors, medical students, imaging students, and researchers with publically available CT scan images of normal and abnormal samples to study, compare, and use in making a diagnosis. There are notable examples of CT scan databases available, but they lack in CT scan dataset for healthy brain CT scan images. Brain image data from CT scans are valuable. A CT brain image provides doctors with indicators of tumors, aneurysms, brain damage, swelling, and abnormal blood vessels. Data is often collected with the use of an MRI (magnetic resonance imaging). But because of radiation exposure from a CT scan, healthy volunteers are not often recruited for a CT scan database. Therefore, much of the available open data comes from clinical trials.
CT Brain Images
Collecting images of the brain from a CT scan is noninvasive and often more comfortable for patients than a traditional MRI. Patients generally lay down comfortably on a table, and the CT “camera” uses a special x-ray beam that moves around the head in a circle. Many different angles and views of the brain are collected. Brain CT scans are much more detailed than an X-ray, and the scan usually takes 15-30 minutes to complete. The data from completed scans are sent to a computer. The computer compiles the data into 2-D images that are saved and then displayed for a doctor to interpret or “read.” Each picture is viewed carefully by a radiologist. A radiologist is a specialist trained to detect any abnormalities in the scan.
CT Open Data and Machine Learning
As mentioned, CT open data is a valuable resource for students, doctors and researchers. However, trials using Machine Learning models to interpret medical imaging data show great promise and could transform healthcare.
In many hospitals or radiology settings, a high volume of cases prevents doctors from reading scans in the most timely manner. Unfortunately, this results in delayed diagnosis and thus treatment for some patients. Considering nearly half of Intracranial hemorrhage (ICH) patients die within 24 hours of diagnosis, early detection is essential for prompt life-saving interventions and treatment. Doctors in hospitals and clinics can perform a large CT scan data download of many patients’ images. Then the data is interpreted using ML. Machine Learning models can identify patients with life-threatening conditions or injuries much more quickly.
Because open data is used for teaching, research, and making diagnoses, CT open data must be of excellent quality. Scan quality depends on four factors: spatial resolution, image contrast, image noise, and artifacts. The imaging technician provides quality pictures with contrast and resolution, but image noise and artifacts degrade the image quality. Artifacts and noise result from patient movement during the scan, dentures, earrings, or any metal in the body. Artifacts obscure the pathology of the scan, making it difficult for the radiologist to read the images. The technician can correct some image “noise” and artifacts, but the doctor must note any of these inaccuracies when reading in the brain image scan.
Purchase CT Open Data
The benefits of CT open data, particularly a brain CT scan image database, are clear. The data improves patient outcomes and provides image data for use in Machine Learning Trials and teaching. Purchase information on a brain image database is available on our website.