Flexible fiber-laser ultrasound sensor for multiscale photoacoustic imaging

Photoacoustic imag ing(PAI)is a nonin vasive biomedical imag ing tech no logy capable of multiscale imag ing of biological samples from orga ns dow n to cells.Multiscale PAI requires differe nt ultraso und tra nsducers that are flat or focused because the current widely-used piezoelectric transducers are rigid and lack the flexibility to tune their spatial ultrasound responses.Inspired by the rapidly-developing flexible photonics,we exploited the inherent flexibility and low-loss features of optical fibers to develop a flexible fiber-laser ultrasound sensor(FUS)for multiscale PAI.By simply bending the fiber laser from straight to curved geometry,the spatial ultraso und resp onse of the FUS can be tuned for both wide-view optical-resolution photoacoustic microscopy at optical diffraction-limited depth(~1 mm)and photoacoustic computed tomography at optical dissipation-limited depth of several centimeters.A radio-frequency demodulation was employed to get the readout of the beat frequency variation of two orthogonal polarization modes in the FUS output,which ensures low-noise and stable ultrasound detection.Compared to traditional piezoelectrical transducers with fixed ultrasound responses once manufactured,the flexible FUS provides the freedom to design multiscale PAI modalities including wearable microscope,intravascular endoscopy,and portable tomography system,which is attractive to fundamental biologic-al/medical studies and clinical applications.

A PIID-DTBT based semi-conducting polymer dots with broad and strong optical absorption in the visible-light region： Highly effective contrast agents for multiscale and multi-spectral photoacoustic imaging

As a hybrid imaging technique, photoacoustic imaging （PAI） can provide multiscale morphological information of tissues, and the use of multi-spectral PAI （MSPAI） can recover the spatial distribution of chromophores of interest, such as hemoglobin within tissues. Herein, we developed a contrast agent that can very effectively combine multiscale PAI with MSPAI for a more comprehensive characterization of complex biological tissues. Specifically, we developed novel PIID-DTBT based semi-conducting polymer dots （Pdots） that show broad and strong optical absorption in the visible-light region （500-700 nm）. The performances of gold nanoparticles （GNPs） and gold nanorods （GNRs）, which have been verified as excellent photoacoustic contrast agents, were compared with that of the Pdots based on the multiscale PAI system. Both ex vivo and in vivo experiments demonstrated that the Pdots have better photoacoustic conversion efficiency at 532 nm than GNPs and showed similar photoacoustic performance with GNRs at 700 nm at the same mass concentration. Photostability and toxicity tests demonstrated that the Pdots are photostable and biocompatible. More importantly, an in vivo MSPAI experiment indicated that the Pdots have better photoacoustic performance than the blood and therefore the signals can be accurately extracted from the background of vascular-rich tissues. Our work demonstrates the great potential of Pdots as highly effective contrast agents for the precise localization of lesions relative to the blood vessels based on multiscale PAI and MSPAI.

Towards in vivo photoacoustic human imaging:Shining a new light on clinical diagnostics

Multiscale visualization of human anatomical structures is revolutionizing clinical diagnosis and treatment.As one of the most promising clinical diagnostic techniques,photoacoustic imaging(PAI),or optoacoustic imaging,bridges the spatial-resolution gap between pure optical and ultrasonic imaging techniques,by the modes of optical illumination and acoustic detection.PAI can non-invasively capture multiple optical contrasts from the endogenous agents such as oxygenated/deoxygenated hemoglobin,lipid and melanin or a variety of exogenous specific biomarkers to reveal anatomy,function,and molecular for biological tissues in vivo,showing significant potential in clinical diagnostics.In 2001,the worldwide first clinical prototype of the photoacoustic system was used to screen breast cancer in vivo,which opened the prelude to photoacoustic clinical diagnostics.Over the past two decades,PAI has achieved monumental discoveries and applications in human imaging.Progress towards preclinical/clinical applications includes breast,skin,lymphatics,bowel,thyroid,ovarian,prostate,and brain imaging,etc.,and there is no doubt that PAI is opening new avenues to realize early diagnosis and precise treatment of human diseases.In this review,the breakthrough researches and key applications of photoacoustic human imaging in vivo are emphatically summarized,which demonstrates the technical superiorities and emerging applications of photoacoustic human imaging in clinical diagnostics,providing clinical translational orientations for the photoacoustic community and clinicians.The perspectives on potential improvements of photoacoustic human imaging are finally highlighted.

Multiresolution image fusion scheme based on fuzzy region feature

This paper proposes a novel region based image fusion scheme based on multiresolution analysis. The low frequency band of the image multiresolution representation is segmented into important regions, sub-important regions and background regions. Each feature of the regions is used to determine the region’s degree of membership in the multiresolution representation, and then to achieve multiresolution representation of the fusion result. The final image fusion result can be obtained by using the inverse multiresolution transform. Experiments showed that the proposed image fusion method can have better performance than existing image fusion methods.

PAN-DeSpeck:A Lightweight Pyramid and Attention-Based Network for SAR Image Despeckling

SAR images commonly suffer fromspeckle noise,posing a significant challenge in their analysis and interpretation.Existing convolutional neural network(CNN)based despeckling methods have shown great performance in removing speckle noise.However,these CNN-basedmethods have a fewlimitations.They do not decouple complex background information in amulti-resolutionmanner.Moreover,they have deep network structures thatmay result in many parameters,limiting their applicability tomobile devices.Furthermore,extracting key speckle information in the presence of complex background is also a major problem with SAR.The proposed study addresses these limitations by introducing a lightweight pyramid and attention-based despeckling(PAN-Despeck)network.The primary objective is to enhance image quality and enable improved information interpretation,particularly on mobile devices and scenarios involving complex backgrounds.The PAN-Despeck network leverages domainspecific knowledge and integrates Gaussian Laplacian image pyramid decomposition for multi-resolution image analysis.By utilizing this approach,complex background information can be effectively decoupled,leading to enhanced despeckling performance.Furthermore,the attention mechanism selectively focuses on key speckle features and facilitates complex background removal.The network incorporates recursive and residual blocks to ensure computational efficiency and accelerate training speed,making it lightweight while maintaining high performance.Through comprehensive evaluations,it is demonstrated that PAN-Despeck outperforms existing image restoration methods.With an impressive average peak signal-to-noise ratio(PSNR)of 28.355114 and a remarkable structural similarity index(SSIM)of 0.905467,it demonstrates exceptional performance in effectively reducing speckle noise in SAR images.The source code for the PAN-DeSpeck network is available on GitHub.