TMJ contrast enhancement in CBCT images using a new algorithm.
María Florinda OteroPablo García TahocesAntonio MeraJorge MiraPublished in: Acta radiologica open (2022)
Magnetic resonance imaging (MRI) is considered the gold standard to reliably diagnose inflammation in the temporomandibular joint (TMJ) of patients with juvenile idiopathic arthritis (JIA). However, even MRI imaging is dependent on the familiarity of the radiologist with the normal appearance of the TMJ; therefore, new approaches are needed. Our purpose here is to improve imaging quality of cone beam computed tomography (CBCT) as a tool to help in the diagnosis of JIA in the TMJ. We have designed and applied a filter (the Stacking Enhancement Filter) over a stock of CBCT images from the TMJs of two patients with JIA. We then made a visual comparison of the results with archival images from MRI of the same patients, to show that the filter substantially improves the visual quality of the image. The work on the image contrast and the increase of the difference of appearance between tissues of different densities (all the anatomical structures that are present within the joint) leads to an improvement of the resulting images of the TMJ without the use of a chemical contrast agent. We conclude that CBCT could be used as a filter tool for the analysis of the TMJs affected by arthritis. Our image processing technique yields images that possible improve the range of use of CBCT.
Keyphrases
- cone beam computed tomography
- deep learning
- juvenile idiopathic arthritis
- contrast enhanced
- magnetic resonance imaging
- convolutional neural network
- image quality
- magnetic resonance
- high resolution
- machine learning
- optical coherence tomography
- computed tomography
- end stage renal disease
- diffusion weighted imaging
- disease activity
- rheumatoid arthritis
- oxidative stress
- gene expression
- newly diagnosed
- ejection fraction
- chronic kidney disease
- peritoneal dialysis
- fluorescence imaging