Fibre-Optic Hydrophone For Detection of High-Intensity Ultrasound Waves

Fibre-optic hydrophones (FOHs) are widely used to detect high-intensity focused ultrasound (HIFU) fields. The most common type consists of an uncoated singlemode fibre with a perpendicularly cleaved end face. The main disadvantage of these hydrophones is their low signal-to-noise ratio (SNR). To increase the SNR, signal averaging is performed, but the associated increased acquisition times hinder ultrasound field scans. In this study, with a view to increase SNR whilst withstanding HIFU pressures, the bare FOH paradigm is extended to include a partially-reflective coating on the fibre end face. Here, a numerical model based on the general transfer-matrix method was implemented. Based on the simulation results, a single-layer, 172 nm TiO2-coated FOH was fabricated. The frequency range of the hydrophone was verified from 1 to 30 MHz. The SNR of the acoustic measurement with the coated sensor was 21 dB higher than of the uncoated one. The coated sensor successfully withstood a peak-positive pressure of 35 MPa for 6000 pulses

Comparison of Fabrication Methods for Fiber‐Optic Ultrasound Transmitters Using Candle‐Soot Nanoparticles

Candle-soot nanoparticles (CSNPs) have shown great promise for fabricating optical ultrasound (OpUS) transmitters. They have a facile, inexpensive synthesis whilst their unique, porous structure enables a fast heat diffusion rate which aids high-frequency ultrasound generation necessary for high-resolution clinical imaging. These composites have demonstrated high ultrasound generation performance showing clinically relevant detail, when applied as macroscale OpUS transmitters comprising both concave and planar surfaces, however, less research has been invested into the translation of this material's technology to fabricate fiber-optic transmitters for image guidance of minimally invasive interventions. Here, are reported two fabrication methods of nanocomposites composed of CSNPs embedded within polydimethylsiloxane (PDMS) deposited onto fiber-optic end-faces using two different optimized fabrication methods: “All-in-One” and “Direct Deposition.” Both types of nanocomposite exhibit a smooth, black domed structure with a maximum dome thickness of 50 µm, broadband optical absorption (>98% between 500 and 1400 nm) and both nanocomposites generated high peak-to-peak ultrasound pressures (>3 MPa) and wide bandwidths (>29 MHz). Further, high-resolution (<40 µm axial resolution) B-mode ultrasound imaging of ex vivo lamb brain tissue demonstrating how CSNP-PDMS OpUS transmitters can allow for high fidelity minimally invasive imaging of biological tissues is demonstrated

Placenta Imaging Workshop 2018 report:Multiscale and multimodal approaches

The Centre for Medical Image Computing (CMIC) at University College London (UCL) hosted a two-day workshop on placenta imaging on April 12th and 13th 2018. The workshop consisted of 10 invited talks, 3 contributed talks, a poster session, a public interaction session and a panel discussion about the future direction of placental imaging. With approximately 50 placental researchers in attendance, the workshop was a platform for engineers, clinicians and medical experts in the field to network and exchange ideas. Attendees had the chance to explore over 20 posters with subjects ranging from the movement of blood within the placenta to the efficient segmentation of fetal MRI using deep learning tools. UCL public engagement specialists also presented a poster, encouraging attendees to learn more about how to engage patients and the public with their research, creating spaces for mutual learning and dialogue

Comparison of noise reduction methods in photoacoustic microscopy

Photoacoustic microscopy (PAM) is classified as a hybrid imaging technique based on the photoacoustic effect and has been frequently studied in recent years. Photoacoustic (PA) signals are inherently recorded in a noisy environment and are also exposed to noise by system components. Therefore, it is essential to reduce the noise in PA signals to reconstruct images with less error. In this study, an image reconstruction algorithm for PAM system was implemented and different filtering approaches for denoising were compared. Studies were carried out in three steps: simulation, experimental phantom and blood cell studies. FIR low-pass and band-pass filters and Discrete Wavelet Transform (DWT) based filters (mother wavelets: “bior3.5″, “bior3.7″, “sym7″) with four different thresholding techniques were examined. For the evaluation purposes, Root Mean Square Error (RMSE), Signal to Noise Ratio (SNR) and Contrast to Noise Ratio (CNR) metrics were calculated. In the simulation studies, the most effective methods were obtained as: sym7/heursure/hard thresh. combination (low and medium level noise) and bior3.7/sqtwolog/soft thresh. combination (high-level noise). In experimental phantom studies, noise was classified into five levels. Different filtering approaches perform better depending on the SNR of PA images. For the blood cell study, based on the standard deviation in the background, sym7/sqtwolog/soft thresh. combination provided the best improvement and this result supported the experimental phantom results