Model based fitting of pattern reversal visually evoked potentials provides a reliable characterization of waveform components.

Objective: To introduce a novel approach to analyzing pattern reversal visual evoked potentials (prVEPs) using a difference-of-gammas model-based fitting method. Methods: prVEP was recorded from uninjured youth ages 11-19 years during pre- or postseason sports evaluation. A difference-of-gammas model fit was used to extract the amplitude, peak time, and peak width of each of four gamma components. The within session reliability and stability of fits across a 6-month period were determined. To demonstrate an application of this analysis, changes in parameters across age were determined. Results: A difference-of-gammas model consisting of four gamma functions was fit to the prVEP of 151 youth. Peak times and amplitudes of functions corresponded to standard measures of the N75, P100, and N135 components respectively, and a late gamma peak (mean peak time 219 ms). We extracted the peak width, which increased with each subsequent temporal peak. Parameter fits were reliable within sessions (correlation coefficient >0.92 for all measured parameters; good agreement on Bland-Altman calculation) and were stable between sessions separated by less than 6 months (correlation coefficient > 0.90). Standard peak analysis metrics extracted from the difference-of-gamma model fits were largely consistent with gold-standard peak analysis measurements. Conclusions: The difference-of-gammas model provides a stable and reliable within-participant representation of the global temporal variability of prVEP waveforms across a large sample of youth. Significance: Using difference-of-gammas model to characterize the global temporal variability of the prVEP waveform offers a promising direction to enhance analysis for identifying and following subtle changes in neurologic conditions.

A Novel Accurate Peak Extraction Algorithm of Mass Spectrometry Based on Iterative Adaptive Curve Fitting.

In the analysis of mass spectrometry, the peak identification from the overlapped region is necessary yet difficult. Although various methods have been developed to identify these peaks, especially the continuous wavelet transformation, their applications are still limited and it is hard to deal with the complex overlapped peaks. In this study, a novel peak extraction algorithm of mass spectrometry based on iterative adaptive curve fitting is proposed to address these challenges. It fully utilizes the global optimization characteristics of adaptive curve fitting. Initial peak parameters are obtained using a window searching method, and the residuals between the adaptive fitting peak and the original data indicate the fit's effectiveness and provide information about the peaks in overlap. Using this information, we performed iterative adaptive fitting, continuously updating the overlapped peaks until the residuals met the completion criteria. All of the peaks within the overlapped region can be successfully extracted by the final fitting. The proposed method is evaluated by the simulated data, the real signal from a public data set, and the spectra of two different mass spectrometry instruments. The results demonstrate that this method can more effectively extract peaks with severe overlap and multiple overlapped peaks, resist noise interference, and offer the potential to process peaks with a high dynamic range. More importantly, the proposed method accurately identifies overlapped peaks in the actual spectra from various mass spectrometry instruments, which helps the qualitative and quantitative analyses to a great extent.

TRU-IMP: techniques for reliable use of images in medical physics; a graphical user interface to analyze and compare segmentations in nuclear medicine.

BACKGROUND: In the context of pharmacokinetic analyses, the segmentation method one uses has a large impact on the results obtained, thus the importance of transparency. Innovation: This paper introduces a graphical user interface (GUI), TRU-IMP, that analyzes time-activity curves and segmentations in dynamic nuclear medicine. This GUI fills a gap in the current technological tools available for the analysis of quantitative dynamic nuclear medicine image acquisitions. The GUI includes various techniques of segmentations, with possibilities to compute related uncertainties. Results: The GUI was tested on image acquisitions made on a dynamic nuclear medicine phantom. This allows the comparison of segmentations via their time-activity curves and the extracted pharmacokinetic parameters. Implications: The flexibility and user-friendliness allowed by the proposed interface make the analyses both easy to perform and adjustable to any specific case. This GUI permits researchers to better show and understand the reproducibility, precision, and accuracy of their work in quantitative dynamic nuclear medicine. Availability and Implementation: Source code freely available on GitHub: https://github.com/ArGilfea/TRU-IMP and location of the interface available from there. The GUI is fully compatible with iOS and Windows operating systems (not tested on Linux). A phantom acquisition is also available to test the GUI easily. .

Automatic tiling method for mosaic ceramic art images based on subpixel edge fitting localization and collaborative operation of multiple manipulators.

Mosaic ceramics are not limited to use solely as building materials, they also possess artistic value. Artists can create images by arranging and combining mosaic ceramics, resulting in a perfect fusion of large-scale public art for external walls and ceramic materials. However, the current approach for artists to create mosaic ceramic exterior wall art images involves manual laying and assembling of individual mosaic ceramics. This manual process suffers from issues such as low efficiency, eye fatigue, selection errors, and the risk of high-altitude operations. These challenges significantly impact the quality and efficiency of creating mosaic ceramic exterior wall art image images. To address these problems, this paper proposes an automatic mosaic ceramic art image stitching method based on subpixel edge fitting positioning and collaborative operation of multiple robotic arms. Additionally, a new U + I type conveying method is designed for efficient and space-saving transportation of mosaic ceramics. Experimental results demonstrate a high success rate of recognition, absorption, and placement of multi-color mosaic ceramics using this method reaching 95.45%, with a positioning error within 0.5 mm. The method can also adapt to varying levels of light intensity or noise interference. This approach effectively enhances the quality and efficiency of creating mosaic ceramic exterior wall art images and promotes the development of mosaic ceramic exterior wall public art creation.

Evaluation of a semi-supervised self-adjustment fine-tuning procedure for hearing aids for asymmetrical hearing loss.

OBJECTIVE: This study investigated a previously evaluated self-adjustment procedure with respect to its applicability for asymmetrical hearing loss (AHL). Self-adjusted settings were evaluated for speech recognition in noise and sound preference. DESIGN: Participants were given the possibility to adjust the left and right hearing aid separately using a two-dimensional user interface. Two different adjustment sequences were tested. Realistic everyday sound scenes in a laboratory environment were presented. The difference between the ears regarding their speech recognition in noise was tested with two spatial conditions, unaided as well as with the prescriptive formula and the self-adjusted setting. STUDY SAMPLE: Nineteen experienced hearing aid users (median age 76 years) with different degrees of AHL were invited to participate in this study. RESULTS: Participants adjusted a higher gain slope across frequency in the worse ear than in the better one. The two adjustment sequences resulted in significantly different adjustment durations and gain settings. The difference between the ears regarding speech recognition in noise did not change with the self-adjustment. Overall, group-mean effect sizes were small compared to the parameter space. CONCLUSIONS: The adjustment procedure can be used also by hearing aid users with AHL to find a possibly preferred gain setting.

Constant head-transient method using pressure and flow data for determining permeability and specific storage of tight rocks.

This paper describes a 'constant head-transient method' for estimating permeability and specific storage of tight rock samples, such as shale and crystalline rocks. Experimental tests are conducted using a cylindrical rock sample subjected to confining pressure, through which pressure diffusion occurs from a constant upstream pressure (or constant head) to a finite downstream storage. Unlike the pulse-transient method, the upstream fluid flow into the sample can be measured using a syringe pump because of no change in upstream pressure. By minimizing the downstream storage, the test time can be significantly reduced, but only the downstream pressure transient data do not yield accurate results on permeability and specific storage estimations. By combining the flow data with the pressure data, the proposed method aims at saving the test time and improving the accuracy of their estimations in extremely low permeability rock samples.•A constant head-transient method for measuring the hydraulic properties of tight rocks was developed with a boundary condition of constant upstream pressure and finite downstream storage.•The test time can be saved by minimizing the downstream storage, and the upstream flow can be measured to improve the accuracy in measuring the hydraulic properties.•Combining the flow and pressure objective functions yields the best curve fitting for both pressure and flow curves.

Equation-of-motion orbital-optimized coupled-cluster doubles method with the density-fitting approximation: An efficient implementation.

Orbital-optimized coupled-cluster methods are very helpful for theoretical predictions of the molecular properties of challenging chemical systems, such as excited states. In this research, an efficient implementation of the equation-of-motion orbital-optimized coupled-cluster doubles method with the density-fitting (DF) approach, denoted by DF-EOM-OCCD, is presented. The computational cost of the DF-EOM-OCCD method for excitation energies is compared with that of the conventional EOM-OCCD method. Our results demonstrate that DF-EOM-OCCD excitation energies are dramatically accelerated compared to EOM-OCCD. There are almost 17-fold reductions for the C 5 H 12 $$ {\mathrm{C}}_5{\mathrm{H}}_{12} $$ molecule in an aug-cc-pVTZ basis set with the RHF reference. This dramatic performance improvement comes from the reduced cost of integral transformation with the DF approach and the efficient evaluation of the particle-particle ladder (PPL) term, which is the most expensive term to evaluate. Further, our results show that the DF-EOM-OCCD approach is very helpful for the computation of excitation energies in open-shell molecular systems. Overall, we conclude that our new DF-EOM-OCCD implementation is very promising for the study of excited states in large-sized challenging chemical systems.

Target Fitting Method for Spherical Point Clouds Based on Projection Filtering and K-Means Clustered Voxelization.

Industrial computed tomography (CT) is widely used in the measurement field owing to its advantages such as non-contact and high precision. To obtain accurate size parameters, fitting parameters can be obtained rapidly by processing volume data in the form of point clouds. However, due to factors such as artifacts in the CT reconstruction process, many abnormal interference points exist in the point clouds obtained after segmentation. The classic least squares algorithm is easily affected by these points, resulting in significant deviation of the solution of linear equations from the normal value and poor robustness, while the random sample consensus (RANSAC) approach has insufficient fitting accuracy within a limited timeframe and the number of iterations. To address these shortcomings, we propose a spherical point cloud fitting algorithm based on projection filtering and K-Means clustering (PK-RANSAC), which strategically integrates and enhances these two methods to achieve excellent accuracy and robustness. The proposed method first uses RANSAC for rough parameter estimation, then corrects the deviation of the spherical center coordinates through two-dimensional projection, and finally obtains the spherical center point set by sampling and performing K-Means clustering. The largest cluster is weighted to obtain accurate fitting parameters. We conducted a comparative experiment using a three-dimensional ball-plate standard. The sphere center fitting deviation of PK-RANSAC was 1.91 µm, which is significantly better than RANSAC's value of 25.41 µm. The experimental results demonstrate that PK-RANSAC has higher accuracy and stronger robustness for fitting geometric parameters.

International trends in prescribing silicone hydrogel contact lenses for daily wear (2000-2023): An update.

PURPOSE: Introduced around the turn of the 21st century, silicone hydrogel contact lenses alleviated hypoxic anterior eye complications due to their high oxygen transmissibility. The purpose of this work is to update earlier surveys by describing international trends in silicone hydrogel daily wear contact lens fitting between 2000 and 2023. METHOD: An annual contact lens prescribing survey was sent to eye care practitioners in up to 71 countries between 2000 and 2023. Data relating to 260,144 daily wear soft contact lens fits undertaken in 20 countries returning reliable longitudinal data were analysed in respect of silicone hydrogel daily wear contact lens fitting. RESULTS: There has been a dramatic increase in silicone hydrogel daily wear lens fits (p < 0.0001), increasing from 2.8 % of all daily wear soft lens fits in 2000 to 73.7 % in 2023. Of all daily wear soft contact lenses prescribed to males, 44.6 % were silicone hydrogel lenses, compared with 43.5 % for females (p = 0.0146). The mean age of those wearing silicone hydrogel daily wear lenses was 32.0 ± 14.5 years, compared to 30.4 ± 13.6 years for those wearing daily wear hydrogel lenses (p < 0.0001). Between 2019-2023, the average percentage of fits was - (a) material type: silicone hydrogel - 73 %; mid-water content hydrogels - 13 %; high water content hydrogels - 9 %; and low water content hydrogels - 5 %, and (b) lens design: spherical - 44 %, toric - 32 %, multifocal - 17 %, monovision - 4 %, and 'other' - 3 %. CONCLUSION: The dramatic increase in silicone hydrogel contact lens prescribing for daily wear has been commensurate with the introduction of multiple lens brands and an ongoing expansion of lens designs, parameters and replacement frequency options. The balance between silicone hydrogel and hydrogel lens prescribing is perhaps starting to approach an equilibrium.

Prediction Accuracy of Hyperelastic Material Models for Rubber Bumper under Compressive Load.

Different hyperelastic material models (Mooney-Rivlin, Yeoh, Gent, Arruda-Boyce and Ogden) are able to estimate Treloar's test data series containing uniaxial and biaxial tension and pure shear stress-strain characteristics of rubber. If the rubber behaviour is only determined for the specific load of the product, which, in the case of rubber bumpers, is the compression, the time needed for the laboratory test can be significantly decreased. The stress-strain characteristics of the uniaxial compression test of rubber samples were used to fit hyperelastic material models. Laboratory and numerical tests of a rubber bumper with a given compound and complex geometry were used to determine the accuracy of the material models. Designing rubber products requires special consideration of the numerical discretization process due to the nonlinear behaviours (material nonlinearity, large deformation, connections, etc.). Modelling considerations were presented for the finite element analysis of the rubber bumper. The results showed that if only uniaxial compression test data are available for the curve fitting of the material model, the Yeoh model performs the best in predicting the rubber product material response under compressive load and complex strain state.

Fast and Simple Statistical Shape Analysis of Pregnant Women Using Radial Deformation of a Cylindrical Template.

Non-rigid deformation of a template to fit 3D scans of human subjects is widely used to develop statistical models of 3D human shapes and poses. Complex optimization problems must be solved to use these models to parameterize scans of pregnant women, thus limiting their use in antenatal point-of-care tools in low-resource settings. Moreover, these models were developed using datasets that did not contain any 3D scans of pregnant women. In this study, we developed a statistical shape model of the torso of pregnant women at greater than 36 weeks of gestation using fast and simple vertex-based deformation of a cylindrical template constrained along the radial direction. The 3D scans were pre-processed to remove noisy outlier points and segment the torso based on anatomical landmarks. A cylindrical template mesh T was then fitted onto the segmented scan of the torso by moving each vertex of T in the direction of the radial vector. This process is computationally inexpensive taking only 14.80 seconds to deform a template with 9090 vertices. Principal component analysis (PCA) was performed on the deformed vertex co-ordinates to find the directions of maximum variance. The first 10 principal vectors of our model explained 79.03% of the total variance and reconstructed unseen scans with a mean error of 2.43 cm. We also used the PCA weights of the first 10 principal vectors to accurately predict anthropometric measurements of the pregnant women.

Spatiospectral image processing workflow considerations for advanced MR spectroscopy of the brain.

Magnetic resonance spectroscopy (MRS) is one of the few non-invasive imaging modalities capable of making neurochemical and metabolic measurements in vivo. Traditionally, the clinical utility of MRS has been narrow. The most common use has been the "single-voxel spectroscopy" variant to discern the presence of a lactate peak in the spectra in one location in the brain, typically to evaluate for ischemia in neonates. Thus, the reduction of rich spectral data to a binary variable has not classically necessitated much signal processing. However, scanners have become more powerful and MRS sequences more advanced, increasing data complexity and adding 2 to 3 spatial dimensions in addition to the spectral one. The result is a spatially- and spectrally-variant MRS image ripe for image processing innovation. Despite this potential, the logistics for robustly accessing and manipulating MRS data across different scanners, data formats, and software standards remain unclear. Thus, as research into MRS advances, there is a clear need to better characterize its image processing considerations to facilitate innovation from scientists and engineers. Building on established neuroimaging standards, we describe a framework for manipulating these images that generalizes to the voxel, spectral, and metabolite level across space and multiple imaging sites while integrating with LCModel, a widely used quantitative MRS peak-fitting platform. In doing so, we provide examples to demonstrate the advantages of such a workflow in relation to recent publications and with new data. Overall, we hope our characterizations will lower the barrier of entry to MRS processing for neuroimaging researchers.

Effects of Process Parameters and Process Defects on the Flexural Fatigue Life of Ti-6Al-4V Fabricated by Laser Powder Bed Fusion.

The fatigue performance of laser powder bed fusion-fabricated Ti-6Al-4V alloy was investigated using four-point bending testing. Specifically, the effects of keyhole and lack-of-fusion porosities along with various surface roughness parameters, were evaluated in the context of pore circularity and size using 2D optical metallography. Surface roughness of Sa = 15 to 7 microns was examined by SEM, and the corresponding fatigue performance was found to vary by 102 cycles to failure. The S-N curves for the various defects were also correlated with process window examination in laser beam power-velocity (P-V) space. Basquin's stress-life relation was well fitted to the experimental S-N curves for various process parameters except keyhole porosity, indicating reduced importance for LPBF-fabricated Ti-6Al-4V alloy components.

Preparation and in vitro/in vivo evaluation of uniform-sized Goserelin-loaded sustained release microspheres.

Sustained release microspheres loaded with goserelin are regarded as a promising candidate for treating prostate cancer and other sex hormone diseases. However, their widespread adoption has been hindered by issues such as wide particle size distribution and unstable release characteristics. To address these challenges, we employed a combination of the solid-in-oil-in-water microspheres preparation approach (S/O/W) and innovative premix membrane emulsification technology and deeply investigated the effects of four key parameters on the loaded performance of microspheres and the microscopic mechanisms behind them. With this approach, we successfully produced goserelin-loaded sustained release microspheres of narrow particle size distribution (Span 0.642), remarkable encapsulation efficiency (DL = 4.23 %, EE = 93.98 %), low initial burst release (about 0.50 % within 2 h), and compatibility with small injection needles (23-G, inner diameter 0.33 mm, outer diameter 0.64 mm, maximal force 59 N). In the animal model(administered dose, 2.4 mg·Kg-1), goserelin long-acting sustained release microspheres sustained release for over 32 days, maintaining effective concentrations above 2 ng·mL-1, and effectively reduced serum testosterone concentrations to castration levels (<1.0 ng·mL-1) by day 4, maintaining this inhibition for up to 21 days, exhibiting comparable efficacy to the positive control group. In vivo release kinetics analysis revealed that goserelin-loaded sustained release microspheres exhibited a release pattern dominated by diffusion with corrosion assistance in vivo. In summary, the systematic and comprehensive evaluation of uniform-sized goserelin-loaded sustained release microspheres has highlighted their excellent translational potential, and the study herein may provide new strategies and ideas for the development of microsphere dosage forms.

Structured Stochastic Curve Fitting without Gradient Calculation.

Optimization of parameters and hyperparameters is a general process for any data analysis. Because not all models are mathematically well-behaved, stochastic optimization can be useful in many analyses by randomly choosing parameters in each optimization iteration. Many such algorithms have been reported and applied in chemistry data analysis, but the one reported here is interesting to check out, where a naïve algorithm searches each parameter sequentially and randomly in its bounds. Then it picks the best for the next iteration. Thus, one can ignore irrational solution of the model itself or its gradient in parameter space.

Cycling position optimisation - a systematic review of the impact of positional changes on biomechanical and physiological factors in cycling.

Bike positional configuration changes strongly affect cycling performance. While consensus has emerged on saddle height optimisation, there is none for the relationship between other bike positional variables and cycling performance. Accordingly, this systematic review examines the effect of all major positional variables on performance in cycling, assessing differences between cycling disciplines and sex where possible. The systematic review, conducted per PRISMA guidelines, searched databases including Embase, Web of Science, Medline, and CINAHL, screening 16,578 studies. Of these, 47 were fully analysed. Study quality assessment using the NIH tool revealed none rated "good", 5 "fair" and 33 "poor". The analysis involved 724 participants (90 female, 454 male, 180 sex unstated). Studies focused on trunk angle/upper body position, handlebar height, Q factor, foot position, saddle fore-aft/height, seat tube angle and crank length. Participant cycling disciplines were often unspecified and few papers address women cyclists specifically. Key findings were associated with changing saddle height, trunk angle and saddle fore-aft. For trunk angle, accounting for the biomechanical and physiological effects as well as aerodynamic changes is important. Saddle fore-aft affects the hip angle and trunk angle. There are no clear recommendations for crank length, handlebar height, Q factor or cleat position.

Single-cell analysis via manifold fitting: A framework for RNA clustering and beyond.

Single-cell RNA sequencing (scRNA-seq) data, susceptible to noise arising from biological variability and technical errors, can distort gene expression analysis and impact cell similarity assessments, particularly in heterogeneous populations. Current methods, including deep learning approaches, often struggle to accurately characterize cell relationships due to this inherent noise. To address these challenges, we introduce scAMF (Single-cell Analysis via Manifold Fitting), a framework designed to enhance clustering accuracy and data visualization in scRNA-seq studies. At the heart of scAMF lies the manifold fitting module, which effectively denoises scRNA-seq data by unfolding their distribution in the ambient space. This unfolding aligns the gene expression vector of each cell more closely with its underlying structure, bringing it spatially closer to other cells of the same cell type. To comprehensively assess the impact of scAMF, we compile a collection of 25 publicly available scRNA-seq datasets spanning various sequencing platforms, species, and organ types, forming an extensive RNA data bank. In our comparative studies, benchmarking scAMF against existing scRNA-seq analysis algorithms in this data bank, we consistently observe that scAMF outperforms in terms of clustering efficiency and data visualization clarity. Further experimental analysis reveals that this enhanced performance stems from scAMF's ability to improve the spatial distribution of the data and capture class-consistent neighborhoods. These findings underscore the promising application potential of manifold fitting as a tool in scRNA-seq analysis, signaling a significant enhancement in the precision and reliability of data interpretation in this critical field of study.

NIR-Responsive Deployable and Self-Fitting 4D-Printed Bone Tissue Scaffold.

The treatment of irregular-shaped and critical-sized bone defects poses a clinical challenge. Deployable, self-fitting tissue scaffolds that can be implanted by minimally invasive procedures are a promising solution. Toward this, we fabricated NIR-responsive and programmable polylactide-co-trimethylene carbonate (PLMC) scaffolds nanoengineered with polydopamine nanoparticles (PDA) by extrusion-based three-dimensional (3D) printing. The 3D-printed scaffolds demonstrated excellent (>99%), fast (under 30 s), and tunable shape recovery under NIR irradiation. PLMC-PDA composites demonstrated significantly higher osteogenic potential in vitro as revealed by the significantly enhanced alkaline phosphatase (ALP) secretion and mineral deposition in contrast to neat PLMC. Intraoperative deployability and in vivo bone regeneration ability of PLMC-PDA composites were demonstrated, using self-fitting scaffolds in critical-sized cranial bone defects in rabbits. The 3D-printed scaffolds were deformed into compact shapes that could self-fit into the defect shape intraoperatively under low power intensity (0.76 W cm-2) NIR. At 6 and 12 weeks postsurgical implantation, near-complete bone regeneration was observed in PLMC-PDA composites, unlike neat PLMC through microcomputed tomography (micro-CT) analysis. The potential clinical utility of the 3D-printed composites to secure complex defects was confirmed through self-fitting of the scaffolds into irregular defects in ex vivo models of rabbit tibia, mandible, and tooth models. Taken together, the composite scaffolds fabricated here offer an innovative strategy for minimally invasive deployment to fit irregular and complex tissue defects for bone tissue regeneration.

Anatomy-based fitting improves speech perception in noise for cochlear implant recipients with single-sided deafness.

OBJECTIVE: To evaluate objective and subjective hearing outcomes in experienced cochlear implant users with single sided deafness (SSD CI) who used fitting maps created via anatomy-based fitting (ABF) and clinically-based fitting (CBF). PARTICIPANTS: Twelve SSD CI users with postlingual hearing loss. INTERVENTION: OTOPLAN (Version 3. (MED-EL) was used to determine intracochlear electrode contact positions using post-operative high-resolution flat panel volume computed tomography. From these positions, the corresponding center frequencies and bandwidths were derived for each channel. These were implemented in the clinical fitting software MAESTRO to yield an ABF map individualized to each user. MAIN OUTCOME MEASURES: ABF and CBF maps were compared. Objective speech perception in quiet and in noise, binaural effects, and self-perceived sound quality were evaluated. RESULTS: Significantly higher speech perception in noise scores were observed with the ABF map compared to the CBF map (mean SRT50: -6.49 vs. -4.8 dB SNR for the S0NCI configuration and - 3.85 vs. -2.75 dB SNR for the S0N0 configuration). Summation and squelch effects were significantly increased with the ABF map (0.86 vs. 0.21 dB SNR for summation and 0.85 vs. -0.09 dB SNR for squelch). No improvement in speech perception in quiet or spatial release from masking were observed with the ABF map. A similar level of self-perceived sound quality was reported for each map. Upon the end of the study, all users opted to keep the ABF map. This preference was independent of the angular insertion depth of the electrode array. CONCLUSIONS: Experienced SSD CI users preferred using the ABF map, which gave them significant improvements in binaural hearing and some aspects of speech perception.

A shifted ratio spectrum strategy for effective subtraction of fluorescence interference in Raman spectra.

Raman spectroscopy is an important technique for analyzing the chemical composition of samples in many fields. A severe challenge often encountered in Raman measurements is the presence of a concurrent fluorescence background, especially in biological samples. In order to obtain accurate Raman spectra, the fluorescence background must be subtracted from the original Raman spectra. We proposed a shifted ratio spectrum method to subtract the strong fluorescence background from the original Raman spectrum. First, the original Raman spectrum is divided into multiple regions according to the spectral shape of the shifted ratio spectra, and then, Gaussian fitting is performed in each region. The fitting results are stitched together in order to obtain the complete fluorescence background. Finally, this fluorescence background is subtracted from the original spectrum to obtain a pure Raman spectrum. This method can accurately subtract the fluorescence background of Rhodamine 6G (R6G)/ethanol solution and serum. This highlights the great potential of this method for applications in both biological and non-biological samples.