These clinical images illustrate the versatility of the Planmed Verity® extremity CT scanner. 3D images with isotropic voxels enable the analysis of even the most complex situations where traditional imaging is inadequate. Data can be presented in the multiplanar reconstruction (MPR) view as well as in the 3D rendered format. For more information about clinical examples, please contact Planmed.
Image resolution up to 200um provides excellent diagnostic value to even the smallest suspected fractures as well as cartilage imaging with contrast media. The weight-bearing imaging of foot, ankle, and knee reveals problems otherwise non-discernible.
The head and neck imaging option for Planmed Verity extends the use to wider applications. ENT, maxillofacial traumas, and basic dental imaging needs can be covered with this field-upgradeable addition.
Patient movement can deteriorate image quality and lead to additional scans. The Planmed Verity extremity CT scanner solves this problem with the intelligent Planmeca CALM™ algorithm, which can compensate for slight movements and provide improved, diagnostic-quality images.
The feature is particularly beneficial when imaging restless or lively patients such as children, individuals with special needs, or elderly patients. In addition, the algorithm can add value to any image by improving its quality. Planmeca CALM can be applied after an image has been captured for all anatomies and voxel sizes. The feature not only saves time for clinicians but also guards patients from unnecessary exposure.
Metal objects such as plates, inserts, and artificial joints can cause shadows and streaks in 3D images. Our intelligent algorithm suppresses these artifacts efficiently and reliably. The artifact removal algorithm is very flexible to use – you can either activate it before imaging or utilize it manually after the exposure.
With metal artifact reduction
Without metal artifact reduction
The noise filtration protocol of Planmed Verity is a fantastic tool for achieving noise-free images without losing valuable details. The algorithm improves image quality when using small voxel sizes and allows lowering exposure values by reducing noise. It can be included in the imaging protocol or applied to the image after acquisition.