Ultrasound attenuation of breast tumors is related to their types and pathological states, and can be used to detect and characterize breast cancer. Particularly, ultrasound scattering attenuation can infer the margin properties of breast tumors. Ultrasound attenuation tomography quantitatively reconstructs the attenuation properties of the breast. Our synthetic-aperture breast ultrasound tomography system with two parallel transducer arrays records both ultrasound reflection and transmission signals. We develop an ultrasound attenuation tomography method using ultrasound energy-scaled amplitude decays of ultrasound transmission signals and conduct ultrasound attenuation tomography using a known sound-speed model. We apply our ultrasound transmission attenuation tomography method to a breast phantom dataset, and compare the ultrasound attenuation tomography results with conventional beamforming ultrasound images obtained using reflection signals. We show that ultrasound transmission attenuation tomography complements beamforming images in identifying breast lesions.
Frequency-space prediction filtering (FXPF), also known as FX deconvolution, is a technique originally developed for random noise attenuation in seismic imaging. FXPF attempts to reduce random noise in seismic data by modeling only real signals that appear as linear or quasilinear events in the aperture domain. In medical ultrasound imaging, channel radio frequency (RF) signals from the main lobe appear as horizontal events after receive delays are applied while acoustic clutter signals from off-axis scatterers and electronic noise do not. Therefore, FXPF is suitable for preserving only the main-lobe signals and attenuating the unwanted contributions from clutter and random noise in medical ultrasound imaging. We adapt FXPF to ultrasound imaging, and evaluate its performance using simulated data sets from a point target and an anechoic cyst. Our simulation results show that using only 5 iterations of FXPF achieves contrast-to-noise ratio (CNR) improvements of 67 % in a simulated noise-free anechoic cyst and 228 % in a simulated anechoic cyst contaminated with random noise of 15 dB signal-to-noise ratio (SNR). Our findings suggest that ultrasound imaging with FXPF attenuates contributions from both acoustic clutter and random noise and therefore, FXPF has great potential to improve ultrasound image contrast for better visualization of important anatomical structures and detection of diseased conditions.
Minimum variance beamforming (MVBF) is an adaptive beamforming technique, which aims to improve the lateral resolution by computing and applying signal-dependent apodization rather than predetermined apodization as typically done in conventional delay-and-sum (DAS) beamforming. Although studies have shown that the improvement in lateral resolution associated with MVBF is significant, the axial resolution remains unaffected. In this work, we combine MVBF and spiking deconvolution to improve both lateral and axial resolutions in synthetic aperture ultrasound imaging. We implement our new method and evaluate its performance using experimental datasets from a tissue-mimicking phantom. Our results show that our new method yields improved axial and lateral resolutions as well as image contrast.
Proc. SPIE. 9783, Medical Imaging 2016: Physics of Medical Imaging
KEYWORDS: Breast, Breast cancer, Signal attenuation, Ultrasonography, Tomography, Data acquisition, Transducers, Mammography, Ultrasound tomography, In vivo imaging, Algorithm development, Prototyping, Design for manufacturability
Breast ultrasound tomography is an emerging imaging modality to reconstruct the sound speed, density, and ultrasound attenuation of the breast in addition to ultrasound reflection/beamforming images for breast cancer detection and characterization. We recently designed and manufactured a new synthetic-aperture breast ultrasound tomography prototype with two parallel transducer arrays consisting of a total of 768 transducer elements. The transducer arrays are translated vertically to scan the breast in a warm water tank from the chest wall/axillary region to the nipple region to acquire ultrasound transmission and reflection data for whole-breast ultrasound tomography imaging. The distance of these two ultrasound transducer arrays is adjustable for scanning breasts with different sizes. We use our breast ultrasound tomography prototype to acquire phantom and in vivo patient ultrasound data to study its feasibility for breast imaging. We apply our recently developed ultrasound imaging and tomography algorithms to ultrasound data acquired using our breast ultrasound tomography system. Our in vivo patient imaging results demonstrate that our breast ultrasound tomography can detect breast lesions shown on clinical ultrasound and mammographic images.
The sound-speed distribution of the breast can be used for characterizing breast tumors, because they typically have a higher sound speed than normal breast tissue. This is understood to be the result of remodeling of the extracellular matrix surrounding tumors. Breast sound-speed distribution can be reconstructed using ultrasound bent-ray tomography (USRT). We have recently demonstrated that USRT, using arrival times of both transmission and reflection data, significantly improves image quality. To further improve the robustness of tomographic reconstructions, we develop a USRT method using a modified total-variation (MTV) regularization scheme. Regularization is often used in solving inverse problems by introducing restrictions such as for smoothness. Tikhonov regularization is a widely used regularization scheme that tends to smooth tomographic images, but oversmoothing can obscure critical diagnostic detail such as tumor margins. Total-variation (TV) regularization is another common regularization scheme that preserves tumor margins, but at the cost of increased image noise. Our new USRT with MTV regularization is a Tikhonov-TV hybrid, reducing image noise while preserving margins. We apply our new method to ultrasound transmission data from numerical phantoms, and compare the results with those obtained using Tikhonov regularization.
Ultrasound tomography has great potential to provide quantitative estimations of physical properties of breast tumors for accurate characterization of breast cancer. We design and manufacture a new synthetic-aperture breast ultrasound tomography system with two parallel transducer arrays. The distance of these two transducer arrays is adjustable for scanning breasts with different sizes. The ultrasound transducer arrays are translated vertically to scan the entire breast slice by slice and acquires ultrasound transmission and reflection data for whole-breast ultrasound imaging and tomographic reconstructions. We use the system to acquire patient data at the University of New Mexico Hospital for clinical studies. We present some preliminary imaging results of in vivo patient ultrasound data. Our preliminary clinical imaging results show promising of our breast ultrasound tomography system with two parallel transducer arrays for breast cancer imaging and characterization.