Water-soluble silicon nanocrystals as NIR luminescent probes for time-gated biomedical imaging

Nanoscale ◽  
2020 ◽  
Vol 12 (14) ◽  
pp. 7921-7926 ◽  
Author(s):  
Francesco Romano ◽  
Sara Angeloni ◽  
Giacomo Morselli ◽  
Raffaello Mazzaro ◽  
Vittorio Morandi ◽  
...  
Keyword(s):  
Silicon Nanocrystals ◽  
Signal To Noise Ratio ◽  
Water Soluble ◽  
Signal To Noise ◽  
Luminescent Probes ◽  
Guided Surgery ◽  
Tumor Accumulation ◽  
Gated Imaging ◽  
Soluble Silicon

In vivo studies demonstrated tumor accumulation of luminescent SiNCs, 48 hours clearance and a 3-fold improvement of signal-to-noise ratio in time-gated imaging compared to steady-state acquisition, demonstrating their potentiality for luminescence guided surgery.

scholarly journals Signal-to-noise ratio in the membrane potential of the owl's auditory coincidence detectors

2012 ◽  
Vol 108 (10) ◽  
pp. 2837-2845 ◽  
Author(s):  
Go Ashida ◽  
Kazuo Funabiki ◽  
Paula T. Kuokkanen ◽  
Richard Kempter ◽  
Catherine E. Carr
Keyword(s):  
Neural Circuit ◽  
Signal To Noise Ratio ◽  
Phase Locking ◽  
Low Frequency ◽  
Membrane Potentials ◽  
Signal To Noise ◽  
Theoretical Predictions ◽  
Noise Ratio ◽  
Band Limited

Owls use interaural time differences (ITDs) to locate a sound source. They compute ITD in a specialized neural circuit that consists of axonal delay lines from the cochlear nucleus magnocellularis (NM) and coincidence detectors in the nucleus laminaris (NL). Recent physiological recordings have shown that tonal stimuli induce oscillatory membrane potentials in NL neurons (Funabiki K, Ashida G, Konishi M. J Neurosci 31: 15245–15256, 2011). The amplitude of these oscillations varies with ITD and is strongly correlated to the firing rate. The oscillation, termed the sound analog potential, has the same frequency as the stimulus tone and is presumed to originate from phase-locked synaptic inputs from NM fibers. To investigate how these oscillatory membrane potentials are generated, we applied recently developed signal-to-noise ratio (SNR) analysis techniques (Kuokkanen PT, Wagner H, Ashida G, Carr CE, Kempter R. J Neurophysiol 104: 2274–2290, 2010) to the intracellular waveforms obtained in vivo. Our theoretical prediction of the band-limited SNRs agreed with experimental data for mid- to high-frequency (>2 kHz) NL neurons. For low-frequency (≤2 kHz) NL neurons, however, measured SNRs were lower than theoretical predictions. These results suggest that the number of independent NM fibers converging onto each NL neuron and/or the population-averaged degree of phase-locking of the NM fibers could be significantly smaller in the low-frequency NL region than estimated for higher best-frequency NL.

scholarly journals Sequential average segmented microscopy for high signal-to-noise ratio motion-artifact-free in vivo heart imaging

2013 ◽  
Vol 4 (10) ◽  
pp. 2095 ◽  
Author(s):  
Claudio Vinegoni ◽  
Sungon Lee ◽  
Paolo Fumene Feruglio ◽  
Pasquina Marzola ◽  
Matthias Nahrendorf ◽  
...  
Keyword(s):  
Signal To Noise Ratio ◽  
Motion Artifact ◽  
High Signal ◽  
Signal To Noise ◽  
Heart Imaging ◽  
Noise Ratio

scholarly journals On the Reconstruction of Magnetic Resonance Current Density Images of the Human Brain: Pitfalls and Perspectives

2021 ◽  
Author(s):  
Hasan H. Eroğlu ◽  
Oula Puonti ◽  
Cihan Göksu ◽  
Fróði Gregersen ◽  
Hartwig R. Siebner ◽  
...  
Keyword(s):  
Magnetic Resonance ◽  
Human Brain ◽  
Current Density ◽  
Signal To Noise Ratio ◽  
Ground Truth ◽  
Statistical Testing ◽  
Signal To Noise ◽  
Testing Approach ◽  
Resonance Current

ABSTRACTMagnetic resonance current density imaging (MRCDI) of the human brain aims to reconstruct the current density distribution caused by transcranial electric stimulation from MR-based measurements of the current-induced magnetic fields. The reconstruction problem is challenging due to a low signal-to-noise ratio and a limited volume coverage of the MR-based measurements, the lack of data from the scalp and skull regions and because MRCDI is only sensitive to the component of the current-induced magnetic field parallel to the scanner field. Most existing reconstruction approaches have been validated using simulation studies and measurements in phantoms with simplified geometries. Only one reconstruction method, the projected current density algorithm, has been applied to human in-vivo data so far, however resulting in blurred current density estimates even when applied to noise-free simulated data.We analyze the underlying causes for the limited performance of the projected current density algorithm when applied to human brain data. In addition, we compare it with an approach that relies on the optimization of the conductivities of a small number of tissue compartments of anatomically detailed head models reconstructed from structural MR data. Both for simulated ground truth data and human in-vivo MRCDI data, our results indicate that the estimation of current densities benefits more from using a personalized volume conductor model than from applying the projected current density algorithm. In particular, we introduce a hierarchical statistical testing approach as a principled way to test and compare the quality of reconstructed current density images that accounts for the limited signal-to-noise ratio of the human in-vivo MRCDI data and the fact that the ground truth of the current density is unknown for measured data. Our results indicate that the statistical testing approach constitutes a valuable framework for the further development of accurate volume conductor models of the head. Our findings also highlight the importance of tailoring the reconstruction approaches to the quality and specific properties of the available data.

scholarly journals Self-Reset Image Sensor With a Signal-to-Noise Ratio Over 70 dB and Its Application to Brain Surface Imaging

2021 ◽  
Vol 15 ◽  
Author(s):  
Thanet Pakpuwadon ◽  
Kiyotaka Sasagawa ◽  
Mark Christian Guinto ◽  
Yasumi Ohta ◽  
Makito Haruta ◽  
...  
Keyword(s):  
Neural Activity ◽  
Signal To Noise Ratio ◽  
Image Sensor ◽  
Oxide Semiconductor ◽  
High Signal ◽  
Unstable State ◽  
Signal To Noise ◽  
Compact Size ◽  
Noise Ratio

In this study, we propose a complementary-metal-oxide-semiconductor (CMOS) image sensor with a self-resetting system demonstrating a high signal-to-noise ratio (SNR) to detect small intrinsic signals such as a hemodynamic reaction or neural activity in a mouse brain. The photodiode structure was modified from N-well/P-sub to P+/N-well/P-sub to increase the photodiode capacitance to reduce the number of self-resets required to decrease the unstable stage. Moreover, our new relay board was used for the first time. As a result, an effective SNR of over 70 dB was achieved within the same pixel size and fill factor. The unstable state was drastically reduced. Thus, we will be able to detect neural activity. With its compact size, this device has significant potential to become an intrinsic signal detector in freely moving animals. We also demonstrated in vivo imaging with image processing by removing additional noise from the self-reset operation.

scholarly journals Near-infrared turn-on fluorescent probe for discriminative detection of Cys and application in in vivo imaging

RSC Advances ◽  
2019 ◽  
Vol 9 (71) ◽  
pp. 41431-41437 ◽  
Author(s):  
Shaolong Qi ◽  
Lubao Zhu ◽  
Xinyu Wang ◽  
Jianshi Du ◽  
Qingbiao Yang ◽  
...  
Keyword(s):  
Fluorescent Probes ◽  
Biological Samples ◽  
In Vivo Imaging ◽  
Near Infrared ◽  
Signal To Noise Ratio ◽  
High Signal ◽  
Biological Detection ◽  
Signal To Noise ◽  
Turn On

Near-infrared (NIR) fluorescent probes are widely employed in biological detection because of their lower damage to biological samples, low background interference, and high signal-to-noise ratio.

Artifacts by Misalignment of Cardiac Magnetic Resonance Phased-array Coil Elements: From Simulation to In vivo Test

2019 ◽  
Vol 15 (3) ◽  
pp. 301-307
Author(s):  
Daniele De Marchi ◽  
Alessandra Flori ◽  
Nicola Martini ◽  
Giulio Giovannetti
Keyword(s):  
Cardiac Magnetic Resonance ◽  
Magnetic Resonance ◽  
Phased Array ◽  
Signal To Noise Ratio ◽  
Whole Body ◽  
Signal To Noise ◽  
Phased Array Coil ◽  
Noise Ratio ◽  
Array Coil

Background: Cardiac magnetic resonance evaluations generally require a radiofrequency coil setup comprising a transmit whole-body coil and a receive coil. In particular, radiofrequency phased-array coils are employed to pick up the signals emitted by the nuclei with high signal-tonoise ratio and a large region of sensitivity. Methods: Literature discussed different technical issues on how to minimize interactions between array elements and how to combine data from such elements to yield optimum Signal-to-Noise Ratio images. However, image quality strongly depends upon the correct coil position over the heart and of one array coil portion with respect to the other. Results: In particular, simple errors in coil positioning could cause artifacts carrying to an inaccurate interpretation of cardiac magnetic resonance images. Conclusion: This paper describes the effect of array elements misalignment, starting from coil simulation to cardiac magnetic resonance acquisitions with a 1.5 T scanner. </P><P> Phased-array coil simulation was performed using the magnetostatic approach; moreover, phantom and in vivo experiments with a commercial 8-elements cardiac phased-array receiver coil permitted to estimate signal-to-noise ratio and B1 mapping for aligned and shifted coil.

Development and Characterization of an Electrocochleography-Guided Robotics-Assisted Cochlear Implant Array Insertion System

2021 ◽  
pp. 019459982110492
Author(s):  
Allan M. Henslee ◽  
Christopher R. Kaufmann ◽  
Matt D. Andrick ◽  
Parker T. Reineke ◽  
Viral D. Tejani ◽  
...  
Keyword(s):  
Cochlear Implant ◽  
Real Time ◽  
Signal To Noise Ratio ◽  
Electrode Array ◽  
High Signal ◽  
Animal Testing ◽  
Signal To Noise ◽  
Noise Ratio ◽  
Hearing Outcomes

Objective Electrocochleography (ECochG) is increasingly being used during cochlear implant (CI) surgery to detect and mitigate insertion-related intracochlear trauma, where a drop in ECochG signal has been shown to correlate with a decline in hearing outcomes. In this study, an ECochG-guided robotics-assisted CI insertion system was developed and characterized that provides controlled and consistent electrode array insertions while monitoring and adapting to real-time ECochG signals. Study Design Experimental research. Setting A research laboratory and animal testing facility. Methods A proof-of-concept benchtop study evaluated the ability of the system to detect simulated ECochG signal changes and robotically adapt the insertion. Additionally, the ECochG-guided insertion system was evaluated in a pilot in vivo sheep study to characterize the signal-to-noise ratio and amplitude of ECochG recordings during robotics-assisted insertions. The system comprises an electrode array insertion drive unit, an extracochlear recording electrode module, and a control console that interfaces with both components and the surgeon. Results The system exhibited a microvolt signal resolution and a response time <100 milliseconds after signal change detection, indicating that the system can detect changes and respond faster than a human. Additionally, animal results demonstrated that the system was capable of recording ECochG signals with a high signal-to-noise ratio and sufficient amplitude. Conclusion An ECochG-guided robotics-assisted CI insertion system can detect real-time drops in ECochG signals during electrode array insertions and immediately alter the insertion motion. The system may provide a surgeon the means to monitor and reduce CI insertion–related trauma beyond manual insertion techniques for improved CI hearing outcomes.

Method to Determine Tissue Fluorescence Efficiency in vivo and Predict Signal-to-Noise Ratio for Spectrometers

1998 ◽  
Vol 52 (7) ◽  
pp. 943-951 ◽  
Author(s):  
E. V. Trujillo ◽  
D. R. Sandison ◽  
U. Utzinger ◽  
N. Ramanujam ◽  
M. Follen Mitchell ◽  
...  
Keyword(s):  
Signal To Noise Ratio ◽  
Optical Design ◽  
Tissue Type ◽  
Excitation Wavelength ◽  
Cervical Tissue ◽  
Signal To Noise ◽  
Fluorescence Efficiency ◽  
Tissue Fluorescence ◽  
Noise Ratio

Recent clinical trials have demonstrated the potential of fluorescence spectroscopy for in vivo diagnosis of pathology. There is significant potential to reduce the cost and complexity of instrumentation to measure tissue spectra; however, careful analysis is required to maximize performance and minimize cost. One measure of performance is the signal-to-noise ratio (SNR) of the resulting data. This paper describes a method to predict the SNR of a given optical design for a particular tissue application. In order to calculate the expected SNR, two pieces of information are required: (1) the throughput and inherent noise of the system and (2) a quantitative relationship between the illumination energy and the resulting tissue fluorescence available for collection, which we define as the tissue fluorescence efficiency (FE). We present a method to calculate the fluorescence efficiency of tissue from in vivo measurements of tissue fluorescence. We report FE measurements of the normal and precancerous human cervix in vivo at 337, 380, and 460 nm excitation. We also present and evaluate a method to estimate the throughput and noise of various spectrometers and predict the expected SNR for tissue spectra by using the measured tissue FE. For squamous cervical tissue, as the degree of the disease increases, FE decreases, and as the excitation wavelength increases, FE decreases. Cervical tissue FE varies more than two orders of magnitude, depending on the tissue type and on the excitation wavelength used. Our SNR calculations, based on measured values of tissue FE, demonstrate agreement within a factor of 1.3 of the measured SNR on average. This method can be used to estimate the performance of different spectrometer designs for clinical use.

scholarly journals DISPOSABLE SYSTEM FOR IN-VIVO MECHANICAL CHARACTERIZATION OF SOFT TISSUES BASED ON VOLUME MEASUREMENT

2018 ◽  
Vol 18 (04) ◽  
pp. 1850037 ◽  
Author(s):  
SEYED ALI ELAHI ◽  
NATHANAEL CONNESSON ◽  
YOHAN PAYAN
Keyword(s):  
Mechanical Properties ◽  
Soft Tissues ◽  
Signal To Noise Ratio ◽  
Volume Measurement ◽  
Optical Measurements ◽  
Signal To Noise ◽  
Noise Ratio ◽  
Apex Height

In-vivo characterization of soft tissues is a key step toward biomechanical simulation and planning of intra-operative assisted surgery. To achieve this, aspiration method is a standard technique: tissue is aspirated through a hole while measuring the pressure and associated apex height. An inverse problem is then solved to identify the material mechanical properties. In the literature, the apex height is usually measured using a camera, which induces design difficulties, in particular in regards on the required sterilization process for in-vivo measurements. In this paper, the idea is to replace the apex height optical measurement by the measurement of the aspirated tissue volume. The proposed method enables to reduce the system head to a simple tube: sterilizations becomes easy and the system is disposable after use. The proposed system is thus the simplest, lightest and cheapest one could achieve. It is also to the authors knowledge the first time ever in aspiration method that the aspired volume is the extracted data. As the data signal-to-noise ratio is the main factor impacting any applied inverse method when extracting the mechanical properties, the aim of this work is to assess and compare the experimental signal-to-noise ratio in the raw volume measurements obtained either optically or with the method proposed. Explicit results of inverse methods using volumes as input data are not presented in this paper for concision purpose. The effects on accuracy of various experimental parameters has been investigated and quantified: the volume measurement has proved to present a same order or even better signal-to-noise ratio compared to optical measurements.

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