KEYWORDS: Mammography, Reconstruction algorithms, Digital breast tomosynthesis, Sensors, Detection and tracking algorithms, Cancer, Data acquisition, Breast, Prototyping, Breast cancer
The promising increase in cancer detection rates1, 2 makes digital breast tomosynthesis (DBT) an interesting alternative to full-field digital mammography (FFDM) in breast cancer screening. However, this benefit comes at the cost of an increased average glandular dose in a combined DBT plus FFDM acquisition protocol. Synthetic mammograms, which are computed from the reconstructed tomosynthesis volume data, have demonstrated to be an alternative to a regular FFDM exposure in a DBT plus synthetic 2D reading mode.3 Besides weighted averaging and modified maximum intensity projection (MIP) methods,4, 5 the integration of CAD techniques for computing a weighting function in the forward projection step of the synthetic mammogram generation has been recently proposed.6, 7 In this work, a novel and computationally efficient method is presented based on an edge-retaining algorithm, which directly computes the weighting function by an edge-detection filter.
The development of new x-ray imaging techniques often requires prior knowledge of tissue attenuation, but the sources of such information are sparse. We have measured the attenuation of adipose breast tissue using spectral imaging, in vitro and in vivo. For the in-vitro measurement, fixed samples of adipose breast tissue were imaged on a spectral mammography system, and the energy-dependent x-ray attenuation was measured in terms of equivalent thicknesses of aluminum and poly-methyl methacrylate (PMMA). For the in-vivo measurement, a similar procedure was applied on a number of spectral screening mammograms. The results of the two measurements agreed well and were consistent with published attenuation data and with measurements on tissue-equivalent material.
Spectral X-ray imaging allows to differentiate between two given tissue types, provided their spectral absorption characteristics differ measurably. In mammography, this method is used clinically to determine a decomposition of the breast into adipose and glandular tissue compartments, from which the glandular tissue fraction and, hence, the volumetric breast density (VBD) can be computed. Another potential application of this technique is the characterization of lesions by spectral mammography. In particular, round lesions are relatively easily detected by experienced radiologists, but are often difficult to characterize. Here, a method is described that aims at discriminating cystic from solid lesions directly on a spectral mammogram, obtained with a calibrated spectral mammography system and using a hypothesis-testing algorithm based on a maximum likelihood approach. The method includes a parametric model describing the lesion shape, compression height variations and breast composition. With the maximum likelihood algorithm, the model parameters are estimated separately under the cyst and solid hypothesis. The resulting ratio of the maximum likelihood values is used for the final tissue characterization. Initial results using simulations and phantom measurements are presented.
In this study, we demonstrate that phase-resolved Doppler optical frequency domain imaging (OFDI) is very suitable to
quantify the pulsatile blood flow within a vasodynamic measurement in the in vivo mouse model. For this, an OFDI-system
with a read-out rate of 20 kHz and a center wavelength of 1320 nm has been used to image the time-resolved
murine blood flow in 300 μμm vessels. Because OFDI is less sensitive to fringe washout due to axial sample motion, it is
applied to analyze the blood flow velocities and the vascular dynamics in six-week-old C57BL/6 mice compared to one
of the LDLR knockout strain kept under sedentary conditions or with access to voluntary wheel running. We have shown
that the systolic as well as the diastolic phase of the pulsatile arterial blood flow can be well identified at each
vasodynamic state. Furthermore, the changes of the flow velocities after vasoconstriction and -dilation were presented
and interpreted in the entire physiological context. With this, the combined measurement of time-resolved blood flow
and vessel diameter provides the basis to analyze the vascular function and its influence on the blood flow of small
arteries of different mouse strains in response to different life styles.
We present a novel method to obtain optical angiographies (OAG) on a standard optical coherence tomography
(OCT) system. The moving reference arm is simulated by introducing a phase-shift at the post-processing stage.
The method can be applied bi-directionally from a single scan, one or more velocity-thresholds can be adjusted
during post-processing. First in-vivo results are shown.
KEYWORDS: Lung, Optical coherence tomography, 3D image processing, In vivo imaging, Tissues, Injuries, Imaging systems, 3D acquisition, Doppler tomography, Scanners
In this feasibility study we present a method for 4D imaging of healthy and injured subpleural lung tissue in a mouse
model. We used triggered swept source optical coherence tomography with an A-scan frequency of 20 kHz to image
murine subpleural alveoli during the ventilation cycle. The data acquisition was gated to the pulmonary airway pressure
to take one B-scan in each ventilation cycle for different pressure levels. The acquired B-scans were combined offline to
one C-scan for each pressure level. Due to the high acquisition rate of the used optical coherence tomography system, we
are also able to perform OCT Doppler imaging of the alveolar arterioles. We demonstrated that OCT is a useful tool to
investigate the alveolar dynamics in spatial dimensions and to analyze the alveolar blood flow by using Doppler OCT.
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