Biomedical Imaging Applications Research Articles

Synthesis of self-assembled hyaluronan based nanoparticles and their applications in targeted imaging and therapy

Hyaluronan (HA) is a polysaccharide consisting of repeating disaccharides of N-acetyl-d-glucosamine and d-glucuronic acid. There are increasing interests in utilizing self-assembled HA nanoparticles (HA-NPs) for targeted imaging and therapy. The principal endogenous receptor of HA, cluster of differentiation 44 (CD44), is overexpressed on many types of tumor cells as well as inflammatory cells in human bodies. Active targeting from HA-CD44 mediated interaction and passive targeting due to the enhanced permeability retention (EPR) effect could lead to selective accumulation of HA-NPs at targeted disease sites. This review focuses on the synthesis strategies of self-assembled HA-NPs, as well as their applications in therapy and biomedical imaging.

Mask-Guided Spatial–Temporal Graph Neural Network for Multifrequency Electrical Impedance Tomography

Multi-frequency Electrical Impedance Tomography (mfEIT) is an emerging biomedical imaging modality that exploits frequency-dependent electrical properties. The mfEIT-image-reconstruction problem for cell imaging is particularly challenging due to weak signals from miniaturized sensors and high sensitivity to modelling errors. Existing approaches are primarily based on the linearized model and few are applied to the miniaturized setup. Here we report a Mask-guided Spatial-Temporal Graph Neural Network (M-STGNN) to reconstruct mfEIT images in cell culture imaging. The M-STGNN captures simultaneously spatial and frequency correlations, and the spatial correlation is further constrained by geometric structures from auxiliary binary masks, such as CT or microscopic images. We validate the mfEIT approach through numerical simulations and experiments on MCF-7 human breast cancer cell aggregates. The results demonstrate the superiority of M-STGNN over the state of the art with an improvement of approximately 10.7% under the experimental setup. It can be readily extended to multi-modal biomedical imaging applications.

Graphene-Based Nanomaterials for Biomedical Imaging.

Graphene is sp2-hybridized carbon structure-based two-dimensional (2D) sheet. Graphene-based nanomaterials possess several features such as unique mechanical, electronic, thermal, and optical properties, high specific surface area, versatile surface functionalization, and biocompatibility, which attracted researcher's interests in various fields including biomedicine. In this chapter, we particularly focused on the biomedical imaging applications of graphene-based nanomaterials like graphene oxide (GO), reduced graphene oxide (rGO), graphene quantum dots (GQDs), graphene oxide quantum dots (GOQDs), and other derivatives, which utilize their outstanding optical properties. There are some biomedical imaging modalities using Graphene-based Nanomaterials, among which we will highlight fluorescence imaging, Raman imaging, magnetic resonance imaging, and photoacoustic imaging. We also discussed the brief perspectives and future application related to them.

Framelet transform and fuzzy clustering-based intelligent technique for speckle noise removal in ultrasound images

Purpose Speckle noise removal in ultrasound images is one of the important tasks in biomedical-imaging applications. Many filtering -based despeckling methods are discussed in many existing works. Two-dimensional (2-D) transforms are also used enormously for the reduction of speckle noise in ultrasound medical images. In recent years, many soft computing-based intelligent techniques have been applied to noise removal and segmentation techniques. However, there is a requirement to improve the accuracy of despeckling using hybrid approaches. Design/methodology/approach The work focuses on double-bank anatomy with framelet transform combined with Gaussian filter (GF) and also consists of a fuzzy kind of clustering approach for despeckling ultrasound medical images. The presented transform efficiently rejects the speckle noise based on the gray scale relative thresholding where the directional filter group (DFB) preserves the edge information. Findings The proposed approach is evaluated by different performance indicators such as the mean square error (MSE), peak signal to noise ratio (PSNR) speckle suppression index (SSI), mean structural similarity and the edge preservation index (EPI) accordingly. It is found that the proposed methodology is superior in terms of all the above performance indicators. Originality/value Fuzzy kind clustering methods have been proved to be better than the conventional threshold methods for noise dismissal. The algorithm gives a reconcilable development as compared to other modern speckle reduction procedures, as it preserves the geometric features even after the noise dismissal.

Peptide Multimerization as Leads for Therapeutic Development

Multimerization of peptide structures has been a logical evolution in their development as potential therapeutic molecules. The multivalent properties of these assemblies have attracted much attention from researchers in the past and the development of more complex branching dendrimeric structures, with a wide array of biocompatible building blocks is revealing previously unseen properties and activities. These branching multimer and dendrimer structures can induce greater effect on cellular targets than monomeric forms and act as potent antimicrobials, potential vaccine alternatives and promising candidates in biomedical imaging and drug delivery applications. This review aims to outline the chemical synthetic innovations for the development of these highly complex structures and highlight the extensive capabilities of these molecules to rival those of natural biomolecules.

Ultra-Low Power and High Sensitivity of Joint Clock Gating Based Dual Feedback Edge Triggered Flip Flop for Biomedical Imaging Applications

To adapt to varied working situations, the latest biomedical imaging applications require low energy consumption, high performance, and extensive energy-performance scalability. State-of-the-art electronics with higher sensitivity, higher counting rate, and finer time resolution are required to create higher precision, higher temporal resolution, and maximum contrast biomedical images. In recent days, the system’s power consumption is important critically in modern VLSI circuits particularly for the low power application. In order to decrease the power, a power optimization technique must be used at various design levels. The low power use of logic cells is a proficient technique for decreasing the circuit level power. Dual Feedback edge triggered Flip Flop (DFETFF) is considered for biomedical imaging applications in the proposed system. Initially, the high dynamic range voltage is given as input signal. The comparator output is then retried at the comparator end. The integration capacitor is employed for storing remaining voltage signal. The comparator voltage is then given to the capacitor reset block. In the proposed work, a capacitor-reset block that employs clock signal takes up a dual-feedbackedge-triggered Flip-flop as an alternative of a conventional type for reducing the final output signals errors. Dual feedback loops assure that feedback loops do not tri-state at the time of SET restoration, a scheme that could lead to SEUs in latches if a single delay component and a single feedback loop are used. In digital system, Clock gating is a competent method of lessening the overall consumption of power along with deactivating the clock signal selectively and is useful for controlling the usage of clock signal asynchronously in reference to input-signal current. The integration-control (Vint) signal is employed in controlling the integration time. On the termination of integration, the signal level phase is kept, also similar one is send to arrangement all through read period. As a result, the simulation was carried out after the design layout and the estimations of performance were made and are compared with traditional approaches to prove the proposed mechanism effectiveness for future biomedical applications.

On the use of saliency maps and convolutional neural networks for improved Alzheimer's disease assessment

AbstractBackgroundAlzheimer’s disease (AD) is a progressive neurodegenerative disease accounting for 60–80∖% of dementia cases worldwide[2]. Early diagnosis can decrease the severity of the disorder in addition to improving the quality of life of patients. Biomarkers based on electroencephalography (EEG) have emerged as a promising tool in the study of AD, with the advantage of being non‐invasive, less expensive, and potentially portable when compared to other biomarkers. One such biomarker has been the so‐called "modulation‐spectral‐patch‐feature" proposed in [1]. Such features were found based on visual inspection of modulation spectra from healthy‐controls and age‐matched AD patients. Over the last few years, however, innovations in machine learning, in particular in deep‐neural‐networks, have revolutionized many biomedical image and signal processing applications[4,5,6]. In this paper, we explore their use in building better biomarkers for AD assessment. In particular, we explore the use of saliency‐maps(SM)[3] obtained from classification using convolutional‐neural‐networks(CNN) to extract optimal feature patches in a data‐driven sense.MethodThe study collected data from fifty‐four participants, including 20‐healthy‐controls, 19‐Mild‐Cognitive‐Impairment, and 15‐moderate‐to‐severe‐AD, all age‐matched. Twenty‐channel EEG signals were acquired during eyes‐closed‐resting‐state sessions of eight minutes. The EEG recordings were pre‐processed to remove artifacts. The model performance was evaluated using 5‐fold‐cross‐validation(CV). The average SM was extracted from the validation‐set in order to highlight the relevant modulation "patches" in a data‐driven manner. The CNN model has two convolutional‐layers and three fully‐connected‐layers.ResultThe tested CNN resulted in the following figures‐of‐merit over the 5‐fold‐CV: 89.4%+/‐2.3% for accuracy and 89.3%+/‐2.3% for f1. From the average SM of each fold, it can be seen that theta‐modulated‐by‐delta and beta‐modulated‐by‐theta were important modulation regions . Others regions such as beta‐modulated‐by‐alpha, alpha‐modulated‐by‐delta, and gamma‐modulated‐by‐beta were also important. While some of these regions match those found visually in[1], other provide more insights into AD assessment.ConclusionIn this paper, we show the efficacy of EEG modulation‐spectrograms coupled CNNs saliency‐maps to extract data specific features useful for Alzheimer's disease diagnosis. In particular, several main regions of interest were identified, thus building on previous work that relied on visual inspection. As future work, we will also explore the importance of each EEG channel, thus potentially leading to a more low‐cost and portable solution.

Watt-level 743 nm source by second-harmonic generation of a cascaded phosphosilicate Raman fiber amplifier

We demonstrate a nanosecond pulsed 743 nm source through second-harmonic generation of a cascaded phosphosilicate Raman fiber amplifier system operating at 1485 nm. The amplifier is pumped by a 1240 nm phosphosilicate Raman fiber amplifier and seeded with a continuous-wave 1485 nm diode. This 1485 nm light is used for second-harmonic generation in periodically poled lithium niobate. Greater than 1 W of average power is generated at 743 nm with a corresponding pulse energy of 220 nJ at a repetition rate of 5 MHz. The source displays excellent beam quality (M x , y 2 ≤ 1.18) with ideal parameters for biomedical imaging applications.

Magnetite-Silica Core/Shell Nanostructures: From Surface Functionalization towards Biomedical Applications—A Review

The interconnection of nanotechnology and medicine could lead to improved materials, offering a better quality of life and new opportunities for biomedical applications, moving from research to clinical applications. Magnetite nanoparticles are interesting magnetic nanomaterials because of the property-depending methods chosen for their synthesis. Magnetite nanoparticles can be coated with various materials, resulting in “core/shell” magnetic structures with tunable properties. To synthesize promising materials with promising implications for biomedical applications, the researchers functionalized magnetite nanoparticles with silica and, thanks to the presence of silanol groups, the functionality, biocompatibility, and hydrophilicity were improved. This review highlights the most important synthesis methods for silica-coated with magnetite nanoparticles. From the presented methods, the most used was the Stöber method; there are also other syntheses presented in the review, such as co-precipitation, sol-gel, thermal decomposition, and the hydrothermal method. The second part of the review presents the main applications of magnetite-silica core/shell nanostructures. Magnetite-silica core/shell nanostructures have promising biomedical applications in magnetic resonance imaging (MRI) as a contrast agent, hyperthermia, drug delivery systems, and selective cancer therapy but also in developing magnetic micro devices.

X-ray dark field imaging: a tool for early diagnosis of emphysema in chronic obstructive pulmonary disease?

Grating-based x-ray dark-field imaging is a novel imaging modality that has been refined during the past decade for applications in biomedical imaging.1 This technique exploits the wave-like behaviour of x-rays to detect, quantify, and visualise small-angle x-ray scattering. The strength of the dark-field signal reflects the amount of small-angle x-ray scattering that cannot be detected with conventional x-ray devices. Small-angle x-ray scattering occurs at interfaces between structures of different electron density—eg, at air and tissue interfaces in the lung, making the lung an organ of special interest for x-ray dark-field imaging.

Self-powered and broadband germanium/PEDOT:PSS heterojunction photodetectors for near-infrared biomedical imaging applications

Self-powered and broadband germanium/PEDOT:PSS heterojunction photodetectors for near-infrared biomedical imaging applications

Temperature monitoring through nanoparticle-activated proton relaxation for magnetic resonance imaging application

An effect of temperature on the proton relaxation times in aqueous suspensions of solid-state nanoparticles (NPs) is comparatively investigated for the NPs’ composition varied from pure silicon (Si) with natural isotope content to Si with iron impurities as well as for Si NPs enriched with Si-29 isotope. For all types of the investigated NPs both the longitudinal and transverse relaxation times become shorter compared with that for pure water because of the interaction of electron spin centers in those NPs with nuclear spins of the protons in water molecules. The obtained results allow us to evaluate the temperature sensitivity of NP-based systems for their biomedical applications in magnetic resonance imaging (MRI).

Investigation of the effective aperture: towards high-resolution Fresnel incoherent correlation holography.

Fresnel incoherent correlation holography (FINCH) shows great advantages of coherent-light-source-free, high lateral resolution, no scanning, and easy integration, and has exhibited great potential in recording three-dimensional information of objects. Despite the rapid advances in the resolution of the FINCH system, little attention has been paid to the influence of the effective aperture of the system. Here, the effective aperture of the point spread function (PSF) has been investigated both theoretically and experimentally. It is found that the effective aperture is mainly restricted by the aperture of the charge-coupled device (CCD), the pixel size of the CCD, and the actual aperture of the PSF at different recording distances. It is also found that the optimal spatial resolution exists only for a small range of recording distance, while this range would become smaller as the imaging wavelength gets longer, leading to the result that the optimal spatial resolution is solely determined by the actual aperture of the PSF. By further combining the FINCH system with a microscopy system and optimizing the recording distance, a spatial resolution as high as 0.78 μm at the wavelength of 633 nm has been obtained, enabling a much higher quality imaging of unstained living biological cells compared to the commercial optical microscope. The results of this work may provide some helpful insights into the design of high-resolution FINCH systems and pave the way for their application in biomedical imaging.

Preparation Fe3O4@chitosan-graphene quantum dots nanocomposites for fluorescence and magnetic resonance imaging

The recent development of nanoprobes with multiple biomolecular detection functionalities have attracted considerable interests in various biomedical imaging applications. Herein, we have designed and prepared Fe3O4@chitosan-graphene quantum dots (Fe3O4@CS-GQDs) nanocomposites for fluorescence and magnetic resonance imaging (MRI). The photoluminescent spectra of Fe3O4@CS-GQDs nanocomposites exhibit an emission peak at 434 nm under the ultraviolet excitation light of 330 nm. Fe3O4@CS-GQD nanocomposites show the excellent MRI results in aqueous solution. The cytotoxicity of Fe3O4@CS-GQDs nanocomposites is observed low cytotoxicity in Hela cells. Based on the results, Fe3O4@CS-GQDs nanocomposites are confirmed as promising fluorescence and MRI imaging contrast agents for tumor detection.

Color centers in wide-bandgap semiconductors for subdiffraction imaging: a review

Solid-state atomic-sized color centers in wide-bandgap semiconductors, such as diamond, silicon carbide, and hexagonal boron nitride, are important platforms for quantum technologies, specifically for single-photon sources and quantum sensing. One of the emerging applications of these quantum emitters is subdiffraction imaging. This capability is provided by the specific photophysical properties of color centers, such as high dipole moments, photostability, and a variety of spectral ranges of the emitters with associated optical and microwave control of their quantum states. We review applications of color centers in traditional super-resolution microscopy and quantum imaging methods, and compare relative performance. The current state and perspectives of their applications in biomedical, chemistry, and material science imaging are outlined.

LOW POWER VERY LARGE SCALE INTEGRATION (VLSI) DESIGN OF FINITE IMPULSE RESPONSE (FIR) FILTER FOR BIOMEDICAL IMAGING APPLICATION

Nowadays, the medical image processing techniques are using Very Large Scale Integrated (VLSI) designs for improving the availability and applicability. The digital filters are important module of Digital Signal Processing (DSP) based systems. Existing Finite Impulse Response (FIR) design approach performed with Partial Full Adder (PFA) based Carry Lookahead Adder (CLA) and parallel prefix adder logic in Vedic multiplier. Objective of this approach is to improve the performance of VLSI circuit by obtaining the result of area, power and delay, also, effective incorporation between VLSI circuit and image processing approach makes improved application availability. The design of high speed digital FIR filter is designed with various adders and multipliers. The incorporation of VLSI design and image processing techniques are used on biomedical imaging applications. The Enhanced FIR filter design utilized the hybrid adder and adaptive Vedic multiplier approaches for increasing the performance of VLSI part and the image processing results are taken from Matrix Laboratory tool. This proposed FIR filter design helps to perform the biomedical imaging techniques. The simulation result obtains the performance of enhanced FIR with area, delay and power; for biomedical imaging, Mean Square Error (MSE) and Peak Signal to Noise Ratio (PSNR) is obtained. Comparing with existing and proposed method, the proposed FIR filter for biomedical imaging application obtains the better result. Thus the design model states with various application availability of VLSI image processing approaches and it obtains the better performance results of both VLSI and image processing applications. Overall, the proposed system is designed by Xilinx ISE 14.5 and the synthesized result is done with ModelSim. Here the biomedical image performance is done by using MATLAB with the adaptation of 2018a. Keywords- Enhanced FIR filter; Adaptive vedic multiplier; Hybrid adder; Biomedical imaging; power delay product;

Imaging through dynamical scattering media by two-photon absorption detectors.

Imaging through a dynamical opaque scattering medium is an almost impossible task, where strong multiple light scattering from moving scatters dynamically prevents imaging formations even with state-of-art techniques like correlation imaging or adaptive optics. Meanwhile, a small number of ballistic photons can still penetrate through but require demanding detection in terms of a ultrashort time gate and high sensitivity. However, visible light is strongly scattered for most of scattering media. Here we experimentally demonstrate a non-invasive coherent imaging scheme based on two-photon absorption capable of imaging through dynamical scattering media with a length equivalent to 28 times mean free paths for single photon transport, where two-photon absorption in a conventional semiconductor photodetector when phase matching is not required works over a wide bandwidth so it can support a fast time gate down to femtosecond level, short enough to distinguish ballistic photons from scattering background, and allows accessing longer wavelengths for deeper penetration. This technique combined with successful optical coherence tomography may pave a new way for imaging through fog, storm, and rain as well as biomedical imaging applications.

Iterative Imaging through Strong Dynamic Turbulence Media

An iterative computation technique is proposed to realize high-quality imaging through strong and rapidly changing turbulence media, where the wave-front of light cannot be sufficiently corrected by common adaptive optics. Raw images of both object under observation and reference point object are sequentially recorded for many times, and the clear image of the object under observation can be reconstructed rapidly from these distorted raw images using a Wiener filter based iterative computation strategy. Both numerical simulations and proof-of-principle-experiments have been carried out to demonstrate the feasibility this proposed method. Since it requires no adaptive optics, this proposed method has advantages of simple optical setup and convenient operation, and accordingly can find lots of applications in astronomical observation and biomedical imaging.

A novel family of non-symmetric benzothieno[7,6-b]-fused BODIPYs: Synthesis, structures, photophysical properties and lipid droplet-specific imaging in vitro

The synthesis of near-infrared emitting BODIPY fluorophore is a key requirement for biomedical imaging applications. Herein, a series of non-symmetric benzothieno[7,6-b]-fused BODIPY dyes were efficiently synthesized. All of them have been well characterized by NMR (1H, 13C, 11B, 19F), HRMS, UV–vis, Emission, and X-ray crystal analysis. These dyes exhibit effective planar expansion of π-conjugation on the BODIPY core. The absorption from 540 to 700 nm and emission from 620 to 780 nm are effectively tuned by benzothieno[7,6-b] fusion or Knoevenagel condensation reaction. More importantly, these developed dyes showed high specificity for staining lipid droplets. Cell imaging experiments demonstrated that a benzothieno[7,6-b]-fused BODIPY with para-dimethylaminophenyl group exhibited high photo-stability for imaging in living cell. The synthesis and functional modification for the benzothieno[7,6-b]-fused BODIPY dye provided an effective way for generating BODIPY-based near-infrared dyes in medical and biological applications.

Optical-Property-Enhancing Novel Near-Infrared Active Niosome Nanoformulation for Deep-Tissue Bioimaging.

Indocyanine green (ICG) is a clinically approved near-infrared (NIR) contrast agent used in medical diagnosis. However, ICG has not been used to its fullest for biomedical imaging applications due to its low fluorescence quantum yield, aqueous instability, concentration-dependent aggregation, and photo and thermal degradations, leading to quenching of its fluorescence emission. In the present study, a nanosized niosomal formulation, ICGNiosomes (ICGNios), is fabricated to encapsulate and protect ICG from degradation. Interestingly, compared to free ICG, the ICGNios exhibited higher fluorescence quantum yield and fluorescence emission with a bathochromic shift. Also, ICGNios nanoparticles are biocompatible, biodegradable, and readily uptaken by the cells. Furthermore, ICGNios show more enhanced fluorescence intensity through ∼1 cm thick chicken breast tissue compared to free ICG, which showed minimal emission through the same thickness of tissue. Our results suggest that ICGNios could offer a promising platform for deep-tissue NIR in vivo imaging to visualize inaccessible tissue microstructures for disease diagnosis and therapeutics.