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Clinical ultrasound image quality is degraded by tissue velocity inhomogeneities that distort the phase of the traveling ultrasonic wavefronts. degrading image resolution and contrast. This paper investigates an entirely new approach for aberration measurement that uses a modified DORT (French acronym for decomposition of the time reversal operator) method, which uses imaging transmission schemes to acquire the time reversal operator. In this novel scheme, the aberration profile is directly estimated from the unwrapped phase of the first DORT eigenvectcr. We term this method focused DORT (FDORT). We compared the FDORT method with a correlation-based, least-mean-squares (LMS) method using 1D arrays on: simulated data; experimental phantom data with a thin-film rubber aberrator; and in-vivo breast data. Measurements were carried out in regions of speckle and point-like scatterers, and corrections were performed using a near-field phase screen aberration model. In simulation, the residual rms error (between applied and estimated aberrator) was 12.5ns with FDORT and 19.5ns with LMS; the point target brightness improvement was 122% (±29%) for FDORT and 132% (±20%) for LMS. The phantom experiments showed 46% (±25%) and 48% (±22%) improvements in point target brightness for FDORT and LMS, respectively. In clinical data, microcalcifications were identified and used to estimate the aberrations. FDORT measured an average 65ns rms, 6.5mm FWHM aberrator with an average brightness improvement of 58% (n=3). LMS measured an average 50.2ns rms, 5.7mm FWHM aberrator with an average improvement of 61% (n=3). FDORT is observed to follow wavefront variations, even where LMS does not perform well due to low correlation values. This is particularly evident in the breast data where coherent wavefronts do not extend across the entire aperture. The initial results presented here indicate that FDORT is a useful method to estimate aberration profiles for adaptive imaging. LMS breaks down in the presence of interfering wavefronts from off-axis and multiple strong scatterers. MORT is able to identify this situation since the individual wavefronts are associated with different eigenvectors. We see the potential for FDORT - to cope with these conditions and thereby estimate aberrations with greater robustness.