Question

2. In modem digital radiography, what types of image receptors are currently used, what does image display/correction/enhancement software do and what are object artifacts in digital radiography and how do they occur?. 3. What type of imaging (to include X-ray and nuclear medical and MRI imaging modalities) typically has the largest digital electronic file size and why? 4. What factors are required for optimal image quality in SPECT and PET nuclear medical scans?

Answer 1

2, During radiographic exposure different forms of image receptors, are used. digital radiography is an important framework to identify the patient's image. radiation exposure must produce quality images for diagnostic purposes. Digital radiography uses indirect conversion of photons to make visible light like a gadolinium-based detector with scintillation material.
Image display properties become the hallmark of modern digital imaging systems. image software help for making relevant anatomy, physiology, and pathology disappear. It enhances the right structure to provide the correct diagnostic presentation, it provides new benefits in the applications.
Object artifacts include radioopaque objects on the patient like jewelry, clothing, and hair that provide abnormal shadows to make degraded image quality, it occurs mostly by hardware failure, software artifacts, and operator error.
3, Radiological images like CT and MRI, PET and SPECT store 16 bits for as integers. This image data is complex type this information data allows the software to convert pixel values in standardized uptake values. different metadata between images produce powerful tools to exploit image information for clinical purposes. it has a specification of scale factors in the front end images.
4, Nuclear medicine images like PET and SPECT displayed with a color map. Pixel of the image associated with a color predefined color map. The images have pseudo-color. we need multiple samples per pixel and 8bit are reserved for each sample. The pixel depth calculated by multiplying the sample depth with the number of samples per pixel.