In ultrasonic elastography, the exact estimation of temporal displacements between two signals is the key to estimating strain. An algorithm was previously proposed that estimates these displacements using phase differences of the corresponding base-band signals. A major advantage of these algorithms compared with correlation techniques is the computational efficiency. In this paper, an extension of the algorithm is presented that iteratively takes into account the time shifts of the signals to overcome the problems of aliasing and accuracy in the estimation of the phase shift. Thus, it can be proven that the algorithm is equivalent to the search of the maximum of the correlation function. Furthermore, a robust logarithmic compression is proposed that only compresses the envelope of the signal. This compression does not introduce systematic errors and significantly reduces decorrelation noise. The resulting algorithm is a computationally simple and very fast alternative to conventional correlation techniques, and the accuracy of strain images is improved.

The results show that it is possible to detect prostate cancer with a high degree of sensitivity using real-time elastography in conjunction with conventional diagnostic methods for guided prostate biopsies.

Two real-time strain imaging concepts and systems are presented. Both systems are based on a conventional ultrasound scanner that is connected to a PC with an A/D converter card for real-time data acquisition of rf data. Differential strain between successively acquired rf frames are estimated using phase root seeking. The first concept uses a special real-time implementation of manual elastography. In the second concept, denoted 'vibrography', the static compression is replaced by low-frequency axial vibration of the probe, still operating in quasistatic acquisition mode. The properties of both concepts are discussed with regard to noise and motion artefacts, and it is shown, using simulations and phantom experiments, that both imaging concepts yield the same kind of strain images. Vibrography has the advantage that no manual compression has to be applied, total compression can be very low and some motion artefacts are better suppressed.

Ultrasound transmission imaging is an alternative promising modality because unlike x-ray transmission this concept is not ionizing and has a good contrast in tissue imaging. Our concept enables also real time imaging.

The incidence of the prostate carcinoma is one of the highest cancer risks in men in the western world. Its position in cancer mortality statistics is also among the highest. The prostate carcinoma is only curable at an early stage. Therefore, early detection is extremely important. At an early stage the prostate carcinoma is limited to the prostate capsule and can hence be cured performing radical prostatectomy.The different types of diagnostics that are used today (digital rectal examination, transrectal ultrasound and PSA value analysis) lack reliability and are therefore not sufficient. Even a combination of these three methods is not sufficiently reliable.Diagnosis of the prostate carcinoma using multifeature tissue characterization in combination with ultrasound allows the detection of tumors at an early stage. Also biopsy guidance and planning can be improved. This results in reduced costs for cancer treatment. I. METHODS Data AcquisitionRadio-frequency (RF) ultrasonic echo data of the prostate is captured during the usual examination of the patient with standard ultrasound equipment (Kretz Combison 330, transrectal probe, 7.5 MHz center frequency). Patient compliance is high, as the new method does not extend the normal examination time when applying transrectal ultrasound and the system is operator-independent. The RF-data is directly transmitted to a PC, sampled at 33 MHz and 12 bits and subdivided into up to 1000 segments per prostate slice. Up to five datasets per patient are being recorded. Parameter ExtractionUp to 40 parameters are calculated for each segment. The extracted parameters do not claim to be independent of the ultrasound equipment. The parameters used for classification are calculated from the frequency spectrum and from the time domain. Spectrum parameters are calculated after applying a Hamming window to the RF data, computing the Fourier transform and converting the resultant power spectrum to dB. The primary set of spectrum parameters consists of measures of backscatter calculated for the signal bandwidth (slope, axis intercept, midband value, integrated power and deviation of the linear regression spectrum fit [1][3][5]). Parameters of an attenuation model (multi narrow band method [2][7][8]) are also included in the system. The texture parameters consist of first and second order (Cooccurrence) parameters. Common cooccurrence parameters are calculated for different distances [3][6].Initial results have shown that only a combination of these different fields of descriptors leads to adequate classification results. During the preselection procedure of parameters for the training process of the system, parameter vectors that are highly dependent on each other are found and discarded using covariance matrix analysis. Parameter vectors that have a small influence on the classification procedure are found and discarded using single classification. During the preselection the number of parameters is reduced from 40 to 16 for both fuzzy inference systems. As the number of segments used in...

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I aging system to support the tissue characterization of the Abstract ~ We implemented an ultrasonic strain imfemale breast. The breast is compressed between two plates of polyethylene and of steel, respectively. 3D elastographic raw data of the breast can he acquired. The displacement is estimated by finding the phase root of the cross-correlation between the pre-and post-compression complex base-band echoes. The estimation is enhanced by 3D "optical flow": we estimate transversal (lateral and out of plane) displacepost-compression image. In spite o f the low signal-to-noise ment which is used to correct the axial trajectories in the ratio o f single compression elastograms, transversal displacements, and motion artifacts, encouraging strain images are obtained. We will demonstrate the performance of this technique by phantom and in vivo results.