Calibrated parametric medical ultrasound imaging
| Autor: | A.J. Van Geemen, Jan J. Rotteveel, Reinier A. Mullaart, Frank M.J. Valckx, Johan M. Thijssen |
|---|---|
| Rok vydání: | 2000 |
| Předmět: |
On-line-real-time bewerking van echobeelden
Computer science Image processing On-line-real-time processing of echographic images 01 natural sciences Texture (geology) 030218 nuclear medicine & medical imaging 03 medical and health sciences 0302 clinical medicine Computer graphics (images) Parametric imaging 0103 physical sciences Image Processing Computer-Assisted Humans Radiology Nuclear Medicine and imaging Computer vision Ultrasonics 010301 acoustics Medical ultrasound Parametric statistics Radiological and Ultrasound Technology business.industry Phantoms Imaging Ultrasound Infant Newborn Acoustics Echoencephalography Calibration Artificial intelligence business |
| Zdroj: | Ultrasonic Imaging, 22, 57-72 Ultrasonic Imaging, 22, pp. 57-72 |
| ISSN: | 0161-7346 |
| DOI: | 10.1177/016173460002200104 |
| Popis: | The goal of this study was to develop a calibrated on-line technique to extract as much diagnostically-relevant information as possible from conventional video-format echograms. The final aim is to improve the diagnostic potentials of medical ultrasound. Video-output images were acquired by a frame grabber board incorporated in a multiprocessor workstation. Calibration images were obtained from a stable tissue-mimicking phantom with known acoustic characteristics. Using these images as reference, depth dependence of the gray level could fairly be corrected for the transducer performance characteristics, for the observer-dependent equipment settings and for attenuation in the examined tissues. Second-order statistical parameters still displayed some nonconsistent depth dependencies. The results obtained with two echoscanners for the same phantom were different; hence, an a posteriori normalization of clinical data with the phantom data is indicated. Prior to processing of clinical echograms, the anatomical reflections and echoless voids were removed automatically. The final step in the preprocessing concerned the compensation of the overall attenuation in the tissue. A ‘sliding window’ processing was then applied to a region of interest (ROI) in the ‘back-scan converted’ images. A number of first and second order statistical texture parameters and acoustical parameters were estimated in each window and assigned to the central pixel. This procedure results in a set of new ‘parametric’ images of the ROI, which can be inserted in the original echogram (gray value, color) or presented as a color overlay. A clinical example is presented for illustrating the potentials of the developed technique. Depending on the choice of the parameters, four full resolution calibrated parametric images can be calculated and simultaneously displayed within 5 to 20 seconds. In conclusion, an on-line technique has been developed to estimate acoustic and texture parameters with a reduced equipment dependence and to display acoustical and textural information that is present in conventional echograms. |
| Databáze: | OpenAIRE |
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