29 research outputs found

    Machine Independence of Ultrasound-Based Quantification of Vitreous Echodensities

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    PURPOSE: Quantitative ultrasound (QUS) provides objective indices of Vision Degrading Myodesopsia (VDM) that correlate with contrast sensitivity (CS). To date, QUS methods were only tested on a single ultrasound machine. Here, we evaluate whether QUS measurements are machine independent. METHODS: In this cross-sectional study, 47 eyes (24 subjects; age = 53.2 ± 14.4 years) were evaluated with Freiburg acuity contrast testing (%Weber), and ultrasonography using 2 machines: one with a 15-MHz single-element transducer and one with a 5-ring, 20-MHz annular-array. Images were acquired from each system in sequential scans. Artifact-free, log-compressed envelope data were processed to yield three parameters (mean amplitude, M; energy, E; and percentage filled by echodensities, P50) and a composite score (C). A B-mode normalization method was applied to the 20-MHz datasets to match QUS parameters at both frequencies. Statistical analyses were performed to evaluate correlations among CS, E, M, P50, and C for both machines. RESULTS: QUS parameters from each machine correlated with CS (R ≥ 0.57, P \u3c 0.001) and there was correlation between machines (R ≥ 0.84, P \u3c 0.001). Correlations between CS and QUS parameters were statistically similar for both machines (P ≥ 0.14) except when the 20-MHz data were normalized (P = 0.04). Reproducibility of QUS parameters computed from 20-MHz data were satisfactory (52.3%-96.3%) with intraclass correlation values exceeding 0.80 (P \u3c 0.001). CONCLUSIONS: The high correlation between QUS parameters from both machines combined with a statistically similar correlation to CS suggests QUS is an effective, machine-independent, quantitative measure of vitreous echodensities. TRANSLATIONAL RELEVANCE: QUS may be applied across clinical ophthalmic ultrasound scanners and imaging frequencies to effectively evaluate VDM

    High-speed, high-frequency ultrasound, \u3ci\u3ein utero\u3c/i\u3e vector-flow imaging of mouse embryos

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    Real-time imaging of the embryonic murine cardiovascular system is challenging due to the small size of the mouse embryo and rapid heart rate. High-frequency, linear-array ultrasound systems designed for small-animal imaging provide high-frame-rate and Doppler modes but are limited in regards to the field of view that can be imaged at fine-temporal and -spatial resolution. Here, a plane-wave imaging method was used to obtain high-speed image data from in utero mouse embryos and multi-angle, vector-flow algorithms were applied to the data to provide information on blood flow patterns in major organs. An 18-MHz linear array was used to acquire plane-wave data at absolute frame rates ≥10 kHz using a set of fixed transmission angles. After beamforming, vector-flow processing and image compounding, effective frame rates were on the order of 2 kHz. Data were acquired from the embryonic liver, heart and umbilical cord. Vector-flow results clearly revealed the complex nature of blood-flow patterns in the embryo with fine-temporal and -spatial resolution

    Correspondence - Characterization of the effective performance of a high-frequency annular-array-based imaging system using anechoic-pipe phantoms

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    A resolution integral (RI) method based on anechoic-pipe, tissue-mimicking phantoms was used to compare the detection capabilities of high-frequency imaging systems based on a single-element transducer, a state-of-the-art, 256-element linear array or a 5-element annular array. All transducers had a central frequency of 40 MHz with similar conventionally measured axial and lateral resolutions (about 50 and 85 μm, respectively). Using the RI metric, the annular array achieved the highest performance (RI = 60), followed by the linear array (47) and the single-element transducer (24). Results showed that the RI metric could be used to efficiently quantify the effective transducer performance and compare the image quality of different systems

    Deep Mouse: An End-to-end Auto-context Refinement Framework for Brain Ventricle and Body Segmentation in Embryonic Mice Ultrasound Volumes

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    High-frequency ultrasound (HFU) is well suited for imaging embryonic mice due to its noninvasive and real-time characteristics. However, manual segmentation of the brain ventricles (BVs) and body requires substantial time and expertise. This work proposes a novel deep learning based end-to-end auto-context refinement framework, consisting of two stages. The first stage produces a low resolution segmentation of the BV and body simultaneously. The resulting probability map for each object (BV or body) is then used to crop a region of interest (ROI) around the target object in both the original image and the probability map to provide context to the refinement segmentation network. Joint training of the two stages provides significant improvement in Dice Similarity Coefficient (DSC) over using only the first stage (0.818 to 0.906 for the BV, and 0.919 to 0.934 for the body). The proposed method significantly reduces the inference time (102.36 to 0.09 s/volume around 1000x faster) while slightly improves the segmentation accuracy over the previous methods using slide-window approaches.Comment: Full Paper Submission to ISBI 202

    High-Frame-Rate Doppler Ultrasound Using a Repeated Transmit Sequence

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    The maximum detectable velocity of high-frame-rate color flow Doppler ultrasound is limited by the imaging frame rate when using coherent compounding techniques. Traditionally, high quality ultrasonic images are produced at a high frame rate via coherent compounding of steered plane wave reconstructions. However, this compounding operation results in an effective downsampling of the slow-time signal, thereby artificially reducing the frame rate. To alleviate this effect, a new transmit sequence is introduced where each transmit angle is repeated in succession. This transmit sequence allows for direct comparison between low resolution, pre-compounded frames at a short time interval in ways that are resistent to sidelobe motion. Use of this transmit sequence increases the maximum detectable velocity by a scale factor of the transmit sequence length. The performance of this new transmit sequence was evaluated using a rotating cylindrical phantom and compared with traditional methods using a 15-MHz linear array transducer. Axial velocity estimates were recorded for a range of ± 300 mm/s and compared to the known ground truth. Using these new techniques, the root mean square error was reduced from over 400 mm/s to below 50 mm/s in the high-velocity regime compared to traditional techniques. The standard deviation of the velocity estimate in the same velocity range was reduced from 250 mm/s to 30 mm/s. This result demonstrates the viability of the repeated transmit sequence methods in detecting and quantifying high-velocity flow
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