Philips XRES Pro features our next-generation high resolution image processing that elevates tissue definition and image quality to new levels.
XRES Pro
XRES Pro offers reduction of artifacts with excellent delineation of structural anatomy
XRES Pro is next-generation image processing
At real-time rates, XRES Pro uses multiple-parametric precision filters that subdivide image elements, analyze this data and then apply advanced algorithms to sharpen borders and interfaces and provides superb tissue conspicuity. XRES Pro also offers enhanced assessment of plaque morphology. XRES Pro allows you full adjustability to match the level of enhancement to clinical imaging requirements for elevated diagnostic confidence with virtually all patients.
Earlier versions of XRES imaging
XRES adaptive image processing
Variable XRES is an extension of Philips exclusive XRES speckle noise reduction feature that allows the user to select progressive amounts of noise reduction, edge enhancement and textural smoothing. Available with specific transducers under certain tissue-specific presets, users have the option to select the imaging characteristics of their choice from crisp to smooth tissue textures, providing enhanced visualization of target anatomic structures.
XRES adaptive image processing provides real-time image enhancement using proprietary contextural algorithms that reduce speckle, haze, and clutter artifacts. At the same time, XRES enhances edges by correcting discontinuities between textured regions, allowing improved visualization of real tissue information. Developed by Philips from MR research, this technology was based on years of extensive research on how humans perceive tissue patterns. XRES imaging is a true adaptive image-processing technique using an amazing 350 million calculations per frame of data. The appropriate processing sub-functions are constantly adapting for each pixel of the frame , for each frame in time. The result is images virtually free from noise, with extraordinary clarity and border definition
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