Source-detector Distance Research Articles

Deep Learning-Based Estimation of Radiographic Position to Automatically Set Up the X-Ray Prime Factors.

Radiation dose and image quality in radiology are influenced by the X-ray prime factors: KVp, mAs, and source-detector distance. These parameters are set by the X-ray technician prior to the acquisition considering the radiographic position. A wrong setting of these parameters may result in exposure errors, forcing the test to be repeated with the increase of the radiation dose delivered to the patient. This work presents a novel approach based on deep learning that automatically estimates the radiographic position from a photograph captured prior to X-ray exposure, which can then be used to select the optimal prime factors. We created a database using 66 radiographic positions commonly used in clinical settings, prospectively obtained during 2022 from 75 volunteers in two different X-ray facilities. The architecture for radiographic position classification was a lightweight version of ConvNeXt trained with fine-tuning, discriminative learning rates, and a one-cycle policy scheduler. Our resulting model achieved an accuracy of 93.17% for radiographic position classification and increased to 95.58% when considering the correct selection of prime factors, since half of the errors involved positions with the same KVp and mAs values. Most errors occurred for radiographic positions with similar patient pose in the photograph. Results suggest the feasibility of the method to facilitate the acquisition workflow reducing the occurrence of exposure errors while preventing unnecessary radiation dose delivered to patients.

Sensitivity of Frequency Domain Near Infrared Spectroscopy for Neurovascular Structure Detection in Biotissue Volume: Numerical Modeling Results.

Through numerical modeling, it has been determined that near infrared spectroscopy with a frequency domain approach can detect neurovascular structures with diameters from 0.5 mm at source-detector distances of 5-8 mm, depending on optical parameters and technical implementation of the method. Among the five classical machine learning methods considered, quadratic discriminant analysis is the most effective for detection. Furthermore, it has been demonstrated that the use of a photomultiplier tube and the registration of both amplitude and phase signal components exhibit the highest sensitivity. Spectroscopy can rival modern ultrasound for detecting arterial vessels. A cross-shaped probe configuration improves sensitivity, and the ratio of reduced scattering coefficient values at different wavelengths is informative for blood-filled vessel detection. These findings are consistent with and significantly extend previous experimental in vivo and in situ studies and could be valuable for intraoperative diagnostic tasks, particularly in neurosurgery.

Depth detection limit of a fluorescent object in tissue-like medium with background emission in continuous-wave measurements: a phantom study.

Although the depth detection limit of fluorescence objects in tissue has been studied, reports with a model including noise statistics for designing the optimum measurement configuration are missing. We demonstrate a variance analysis of the depth detection limit toward clinical applications such as noninvasively assessing the risk of aspiration. It is essential to analyze how the depth detection limit of the fluorescence object in a strong scattering medium depends on the measurement configuration to optimize the configuration. We aim to evaluate the depth detection limit from theoretical analysis and phantom experiments and discuss the source-detector distance that maximizes this limit. Experiments for detecting a fluorescent object in a biological tissue-mimicking phantom of ground beef with background emission were conducted using continuous wave fluorescence measurements with a point source-detector scheme. The results were analyzed using a model based on the photon diffusion equations. Then, variance analysis of the signal fluctuation was introduced. The model explained the measured fluorescence intensities and their fluctuations well. The variance analysis showed that the depth detection limit in the presence of ambient light increased with the decrease in the source-detector distance, and the optimum distance was in the range of 10 to 15mm. The depth detection limit was found to be with this optimum distance for the phantom. The presented analysis provides a guide for the optimum design of the measurement configuration for detecting fluorescence objects in clinical applications.

In vivo optimization of the experimental conditions for the non-invasive optical assessment of breast density

In this study, time domain diffuse optical spectroscopy is performed in the range 600–1100 nm on 11 healthy volunteers with a portable system for the quantitative characterization of breast tissue in terms of optical properties and optically-derived blood parameters, tissue constituent concentrations, and scattering parameters. A measurement protocol involving different geometries (reflectance and transmittance), subject’s positions (sitting and lying down), probing locations (outer, lower, and inner breast quadrants), and source-detector distances (2 and 3 cm) allowed us to investigate the effect of tissue heterogeneity and different measurement configurations on the results with the aim of identifying the best experimental conditions for the estimate of breast density (i.e., amount of fibro-glandular tissue in the breast) as a strong independent risk factor for breast cancer. Transmittance results, that in previous studies correlated strongly with mammographic density, are used as a reference for the initial test of the simpler and more comfortable reflectance measurement configuration. The higher source-detector distance, which probes deeper tissue, retrieves optical outcomes in agreement with higher average density tissue. Similarly, results on the outer quadrants indicate higher density than internal quadrants. These findings are coherent with breast anatomy since the concentration of dense fibro-glandular stroma is higher in deep tissue and towards the external portion of the breast, where the mammary gland is located. The dataset generated with this laboratory campaign is used to device an optimal measurement protocol for a future clinical trial, where optical results will be correlated with conventional mammographic density, allowing us to identify a subset of wavelengths and measurement configurations for an effective estimate of breast density. The final objective is the design of a simplified, compact and cost-effective optical device for a non-invasive, routine assessment of density-associated breast cancer risk.

Sensitivity analysis of transabdominal fetal pulse oximetry using MRI-based simulations.

Transabdominal fetal pulse oximetry offers a promising approach to improve fetal monitoring and reduce unnecessary interventions. Utilizing realistic 3D geometries derived from MRI scans of pregnant women, we conducted photon simulations to determine optimal source-detector configurations for detecting fetal heart rate and oxygenation. Our findings demonstrate the theoretical feasibility of measuring fetal signals at depths up to 30 mm using source-detector (SD) distances greater than 100 mm and wavelengths between 730 and 850 nm. Furthermore, we highlight the importance of customizing SD configurations based on fetal position and maternal anatomy. These insights pave the way for enhanced non-invasive fetal monitoring in clinical application.

Compression and self-compression of frequency modulated spherical photon density waves in anisotropic scattering media

We report on the results of a simulation of the photon density waves with pulse amplitude modulation by a complex frequency modulated signal. The problem is considered for the optical properties typical for sea water with anisotropy factor values varying from 0.75 to 0.93 at source-detector distances up to 120 m. It is shown that multiple scattering in a medium does not prevent effective compression of a signal registered using matched detection. Two competing phenomena affecting the detected pulse duration and depending on the central frequency of the modulation signal are discussed. The effect of faster attenuation of high harmonics in a complexly modulated signal leads to the detected signal duration increase as a consequence of multiple scattering. On the other hand, anomalous dispersion of photon density waves in media with scattering anisotropy leads to the pulse self-compression. The simulation results presented in the paper demonstrate the prevalence of different phenomena depending on the central frequency of the modulation signal resulting in a pulse duration decrease or increase in different frequency ranges covering the band from 107 to 2⋅109 Hz. The effect of the phase function shape on the observed effect is also discussed.

Detectability of hemodynamic oscillations in cerebral cortex through functional near-infrared spectroscopy: a simulation study.

We explore the feasibility of using time-domain (TD) and continuous-wave (CW) functional near-infrared spectroscopy (fNIRS) to monitor brain hemodynamic oscillations during resting-state activity in humans, a phenomenon that is of increasing interest in the scientific and medical community and appears to be crucial to advancing the understanding of both healthy and pathological brain functioning. Our general object is to maximize fNIRS sensitivity to brain resting-state oscillations. More specifically, we aim to define comprehensive guidelines for optimizing main operational parameters in fNIRS measurements [average photon count rate, measurement length, sampling frequency, and source-detector distance (SSD)]. In addition, we compare TD and CW fNIRS performance for the detection and localization of oscillations. A series of synthetic TD and CW fNIRS signals were generated by exploiting the solution of the diffusion equation for two different geometries of the probed medium: a homogeneous medium and a bilayer medium. Known and periodical perturbations of the concentrations of oxy- and deoxy-hemoglobin were imposed in the medium, determining changes in its optical properties. The homogeneous slab model was used to determine the effect of multiple measurement parameters on fNIRS sensitivity to oscillatory phenomena, and the bilayer model was used to evaluate and compare the abilities of TD and CW fNIRS in detecting and isolating oscillations occurring at different depths. For TD fNIRS, two approaches to enhance depth-selectivity were evaluated: first, a time-windowing of the photon distribution of time-of-flight was performed, and then, the time-dependent mean partial pathlength (TMPP) method was used to retrieve the hemoglobin concentrations in the medium. In the homogeneous medium case, the sensitivity of TD and CW fNIRS to periodical perturbations of the optical properties increases proportionally with the average photon count rate, the measurement length, and the sampling frequency and approximatively with the square of the SSD. In the bilayer medium case, the time-windowing method can detect and correctly localize the presence of oscillatory components in the TD fNIRS signal, even in the presence of very low photon count rates. The TMPP method demonstrates how to correctly retrieve the periodical variation of hemoglobin at different depths from the TD fNIRS signal acquired at a single SSD. For CW fNIRS, measurements taken at typical SSDs used for short-separation channel regression show notable sensitivity to oscillations occurring in the deep layer, challenging the assumptions underlying this correction method when the focus is on analyzing oscillatory phenomena. We demonstrated that the TD fNIRS technique allows for the detection and depth-localization of periodical fluctuations of the hemoglobin concentrations within the probed medium using an acquisition at a single SSD, offering an alternative to multi-distance CW fNIRS setups. Moreover, we offered some valuable guidelines that can assist researchers in defining optimal experimental protocols for fNIRS studies.

Modeling sub‐resolution porosity of a heterogeneous carbonate rock sample

AbstractAccurately estimating the petrophysical properties of heterogeneous carbonate rocks across various scales poses significant challenges, particularly within the context of water and hydrocarbon reservoir studies. Digital rock analysis techniques, such as X‐ray computed microtomography and synchrotron‐light‐based imaging, are increasingly employed to study the complex pore structure of carbonate rocks. However, several technical limitations remain, notably the need to balance the volume of interest with the maximum achievable resolution, which is influenced by geometric properties of the source–detector distance in each apparatus. Typically, higher resolutions necessitate smaller sample volumes, leading to a portion of the pore structure (the sub‐resolution or unresolved porosity), that remain undetected. In this study, X‐ray microtomography is used to infer the fluid flow properties of a carbonate rock sample having a substantial fraction of porosity below the imaging resolution. The existence of unresolved porosity is verified by comparisons with nuclear magnetic resonance (NMR) data. We introduce a methodology for modeling the sub‐resolution pore structure within images by accounting for unresolved pore bodies and pore throats derived from a predetermined distribution of pore throat radii. The process identifies preferential pathways between visible pores using the shortest distance and establishes connections between these pores by allocating pore bodies and throats along these paths, while ensuring compatibility with the NMR measurements. Single‐phase flow simulations are conducted on the full volume of a selected heterogeneous rock sample by using the developed pore network model. Results are then compared with petrophysical data obtained from laboratory measurements.

Minimum phantom size for megavoltage photon beam reference dosimetry.

Water phantoms are required to perform reference dosimetry and beam quality measurements but there are no published studies about the size requirements for suchphantoms. To investigate, using Monte Carlo techniques, the size requirements for water phantoms used in reference dosimetry and/or to measure the beam quality specifiers and . The EGSnrc application DOSXYZnrc is used to calculate , the dose per incident fluence at 10cm depth in a water phantom irradiated by incident beams of or 6MV photons. The water phantom dimensions are varied from to and occasionally smaller. The and values are also calculated with care being taken to distinguish results when using Method A (changing depth of water in phantom) and Method B (moving entire phantom). Typical statistical uncertainties are 0.03%. Phantom dimensions have only minor effects for phantoms larger than . A table of corrections to the dose at 10cm depth in beams of or 6MV photons are provided and range from no correction to 0.75% for a beam incident on a phantom. There can be distinct differences in the values measured using Method A or Method B, especially for smaller phantoms. It is explicitly demonstrated that, within 0.15%, values for a phantom measured using Method A or B are independent of source detector distance between 40 and200cm. The phantom sizes recommended in the TG-51 and IAEA TRS-398 reference dosimetry protocols are adequate for accurate reference dosimetry and in some cases are even conservative. Correction factors are necessary for accurate measurement of the dose at 10cm depth in smaller phantoms and these factors are provided. Very accurate beam quality specifiers are not required for reference dosimetry itself, but for specifying beam stability and characteristics it is important to specify phantom sizes and also the method used for measurements.

Simulation study on penetration depth of light in the source–detector distance using a nine-layered skin tissue model in the visible wavelength range

Simulation study on penetration depth of light in the source–detector distance using a nine-layered skin tissue model in the visible wavelength range

A proposed numerical method for absolute efficiency calibration of α-spectrometers and its application for activity calculation

In this work, an absolute method to calibrate an α-spectrometer is proposed taking into account the Source-to-Detector, and lateral distances due to eccentric source distribution. An analytical formula to calibrate an α-spectrometer is derived and the Simpson's integration method was utilized to solve these equations in its integral form numerically using a written C computer code. The general Monte Carlo N-particle code, MCNP as well as experimental measurements for some standard α-emitters are used to benchmark the proposed method. An agreement was found between the efficiency results calculated by MC and the proposed method with a maximum relative difference of about 0.5%. While, experimental measurement of α-emitters activity employing the proposed method differs by about 1.65% from the certified values. Accounting for the man made error allows to accurately quantify the assayed sample. Therefore, the inaccuracy in the efficiency results due to non-accurate inputs pertained to the source, and detector radii, Source–Detector distances, and eccentric source distribution are investigated in the Source-to-Detector distance range of (4 to 44 mm). The results show that a difference of ±1% in the detector radius, and Source-to-Detector distance than the normal values yields a relative difference of about ±2%, while a difference of ±50% in the source radius or source lateral distance from detector symmetry axis could only yields inaccuracy of less than ±3% in the efficiency results.

Initial non-invasive in vivo sensing of the lung using time domain diffuse optics

The in vivo diagnosis and monitoring of pulmonary disorders (caused for example by emphysema, Covid-19, immature lung tissue in infants) could be effectively supported by the non-invasive sensing of the lung through light. With this purpose, we investigated the feasibility of probing the lung by means of time-resolved diffuse optics, leveraging the increased depth (a few centimeters) attained by photons collected after prolonged propagation time (a few nanoseconds). We present an initial study that includes measurements performed on 5 healthy volunteers during a breathing protocol, using a time-resolved broadband diffuse optical spectroscopy system. Those measurements were carried out across the spectral range of 600–1100 nm at a source-detector distance of 3 cm, and at 820 nm over a longer distance (7–9 cm). The preliminary analysis of the in vivo data with a simplified homogeneous model revealed a maximum probing depth of 2.6–3.9 cm, suitable for reaching the lung. Furthermore, we observed variations in signal associated with respiration, particularly evident at long photon propagation times. However, challenges stemming from both intra- and inter-subject variability, along with inconsistencies potentially arising from conflicting scattering and absorption effects on the collected signal, hindered a clear interpretation. Aspects that require further investigation for a more comprehensive understanding are outlined.

Non-destructive detection of single corn seed vigor based on visible/near-infrared spatially resolved spectroscopy combined with chemometrics

Seed vigor is an essential quality evaluation index for seed selection. However, accurately detecting the vigor of a single corn seed is challenging. In this study, we constructed a single-fiber spatially resolved detection device using visible/near-infrared spectroscopy to investigate the patterns and correlations between spatially resolved spectroscopy (SRS) at 500–1000 nm and seed vigor. The device collected spectral data at a light source–detector distance of 5–6.6 mm on the embryo side (S1) and endosperm side (S2) of the corn seeds. The proposed spectral ratio method based on SRS and spectral combination analysis achieved an improvement in the detection accuracy of different corn seed vigor. Modeling by SG-CARS-PLSDA using the ratio method showed further improvement in the prediction ability. The highest accuracy for both S1 and S2 in the Zhengdan 958 variety was 91.67 %, while those of S1 and S2 for the Shaandan 650 variety were 86.67 % and 88.33 %, respectively. In addition, SRS was found to be more advantageous in S2 acquisition, verifying the potential of SRS in the non-destructive testing of seed vigor. This provides a favorable reference for the comprehensive evaluation of other internal quality indices of seeds.

A new Excel-based Monte Carlo transport code for simulating energy response spectra and efficiencies in gamma-ray detection materials

This study presents and assesses a new, user-friendly, and Excel-based Monte Carlo photon transport code, specifically designed to simulate Gaussian energy broadened response spectra of gamma-ray detector materials. This vectorized code utilizes the EPICS2017 photoatomic data library, with unionized energy grid construction, to facilitate precise and efficient photon transport simulations in any user-defined materials composition. Performance benchmarks were conducted using PHITS 3.31, with both basic and detailed models of a gamma-ray scintillator system, and detection crystals of NaI(Tl) and LaBr3(Ce). These benchmarks spanned a wide array of photon source monoenergetic emissions. Detector model efficiency was determined through automated peak area analysis, employing algorithms from the Ortec GammaVision software. The results indicated only minor spectral differences between the Excel-based code and the PHITS models, particularly within the range of practical gamma-ray energies and near-zero source-detector distances. Efficiency curves demonstrated good agreement between the Excel-based code and PHITS models, especially within the energy range of approximately 200 keV to a few MeV, with increasing agreement as detector crystal size increased. Comparisons were conducted with the existing data in literature at source-detector distances of 2 cm and 5 cm, using a detector crystal size of 2”. These comparisons support the code’s validity and its implementation of a basic geometry. This new Excel-based code appears as a promising tool with potential applications in radiation detector characterization and materials research.

Efficiency and energy resolution of gamma spectrometry system with HPGe detector depending on variable source-to-detector distances

The high-purity germanium (HPGe) detectors, which are one of the basic instruments in the experimental nuclear physics, are widely used in many areas such as the environmental radioactivity, neutron activation analysis and geology. This study reports the results of energy calibration, energy resolution and efficiency calculations for an HPGe detector (ORTEC), which are necessary to determine the quality of the measurement results obtained from a gamma spectrometry system. For the purpose of examining the effects of gamma-ray energy and the distance between the source and the detector on the detector efficiency, measurements were made at six different source–detector distances for a total of about fourteen energies of the point sources (133Ba, 109Cd, 137Cs, 57Co, 60Co, 152Eu, 22Na, and 65Zn). Basic data were obtained with this detector system for later studies.

Quantification of blood flow index in diffuse correlation spectroscopy using a robust deep learning method.

Diffuse correlation spectroscopy (DCS) is a powerful, noninvasive optical technique for measuring blood flow. Traditionally the blood flow index (BFi) is derived through nonlinear least-square fitting the measured intensity autocorrelation function (ACF). However, the fitting process is computationally intensive, susceptible to measurement noise, and easily influenced by optical properties (absorption coefficient and reduced scattering coefficient ) and scalp and skull thicknesses. We aim to develop a data-driven method that enables rapid and robust analysis of multiple-scattered light's temporal ACFs. Moreover, the proposed method can be applied to a range of source-detector distances instead of being limited to a specific source-detector distance. We present a deep learning architecture with one-dimensional convolution neural networks, called DCS neural network (DCS-NET), for BFi and coherent factor () estimation. This DCS-NET was performed using simulated DCS data based on a three-layer brain model. We quantified the impact from physiologically relevant optical property variations, layer thicknesses, realistic noise levels, and multiple source-detector distances (5, 10, 15, 20, 25, and 30mm) on BFi and estimations among DCS-NET, semi-infinite, and three-layer fitting models. DCS-NET shows a much faster analysis speed, around 17,000-fold and 32-fold faster than the traditional three-layer and semi-infinite models, respectively. It offers higher intrinsic sensitivity to deep tissues compared with fitting methods. DCS-NET shows excellent anti-noise features and is less sensitive to variations of and at a source-detector separation of 30mm. Also, we have demonstrated that relative BFi (rBFi) can be extracted by DCS-NET with a much lower error of 8.35%. By contrast, the semi-infinite and three-layer fitting models result in significant errors in rBFi of 43.76% and 19.66%, respectively. DCS-NET can robustly quantify blood flow measurements at considerable source-detector distances, corresponding to much deeper biological tissues. It has excellent potential for hardware implementation, promising continuous real-time blood flow measurements.

Improving heart rate monitoring in the obese with time-of-flight photoplethysmography (TOF-PPG): a quantitative analysis of source-detector-distance effect.

Commercial photoplethysmography (PPG) sensors rely on the measurement of continuous-wave diffuse reflection signals (CW-DRS) to monitor heart rate. Using Monte Carlo modeling of light propagation in skin, we quantitatively evaluate the dependence of continuous-wave photoplethysmography (CW-PPG) in commercial wearables on source-detector distance (SDD). Specifically, when SDD increases from 0.5 mm to 3.3 mm, CW-PPG signal increases by roughly 846% for non-obese (NOB) skin and roughly 683% for morbidly obese (MOB) skin. Ultimately, we introduce the concept of time-of-flight PPG (TOF-PPG) which can significantly improve heart rate signals. Our model shows that the optimized TOF-PPG improves heart rate monitoring experiences by roughly 47.9% in NOB and 93.2% in MOB when SDD = 3.3 mm is at green light. Moving forward, these results will provide a valuable source for hypothesis generation in the scientific community to improve heart rate monitoring.

Body composition analysis via spatially resolved NIR spectroscopy with multifrequency bioimpedance precision.

Near-infrared spectroscopy (NIRS) is often criticized due to its insufficient accuracy in determining body composition compared to the gold standard methods. In this work, we show that the use of multiple source-detector distances, as well as the simultaneous use of physiological and optical features, can significantly improve the accuracy of determination of fat and lean mass percentage in the human body using NIR spectroscopy. The study performed on the n = 292 cohort revealed the mean absolute errors of 3.5% for fat content and 3.3% for soft lean mass percentage prediction (r = 0.93) using the multifrequency bioimpedance analysis (BIA) as a reference. Hence, NIRS can serve as an independent reliable method for body composition analysis with precision close to that of advanced multifrequency BIA.

An easy and direct protocol based on planar molecular images to quantify 131I using thyroid phantom

A planar nuclear medicine image can be used to estimate dosimetry during iodine therapy. To this end, radionuclide activity distribution should be quantified in the patient’s body in terms of a calibration coefficient. This coefficient allows the net counts to correlate with the image’s activity. This study aims propose a simple and easy calibration protocol to quantify 131I activity in thyroid phantom by molecular planar images. Were acquired 13 planar images of different phantoms: thyroid phantom of symmetrical lobes; thyroid phantom of asymmetrical lobes; the Jacszack cylinder phantom with a syringe surrounded by air and water, and finally a plastic bottle containing a syringe with radionuclide. We applied the 131I radionuclide in a General Electric gamma camera, model Discovery NM/CT 670 with a high energy general purpose parallel hole collimator above the phantoms positioned at camera bed. The calibration coefficient of the gamma camera and the standard deviation were determined for each phantom; the average calibration coefficient obtained was 0.062±0.006 MBq/cps. The results suggested that the phantoms applied as too the calibration coefficient obtained by them can provides reasonable value for the gamma camera calibration factor for iodine 131, therefore an accurate evaluation of the scattering media as the source detector distance could impose higher variability and uncertainties on results.

Optical properties of melon tissues and Monte Carlo simulation of light propagation through melon fruit

Visible/near-infrared (Vis/NIR) spectroscopy has been authenticated for quality evaluation of melon fruit. However, since melon is a multi-layered fruit with large size, the optical properties (OPs) of different tissue layers can influence the performance of the quality evaluation. Therefore, the OPs of different tissue layers (exocarp, green mesocarp and pulp) among different fruit positions (stem, equator and calyx) of 36 ‘Huanghemi’ melons were measured using single integrating sphere measurements and the light propagation through melon fruit was investigated by the Monte Carlo (MC) simulation based on the OPs. Moreover, the relationship of the OPs with microstructure and internal quality properties (soluble solids content (SSC) and moisture content) was explored. In the absorption coefficient (μa) spectra, five obvious absorption peaks for carotenoids (481 nm), chlorophyll (675 nm) and water (984, 1195 and 1423 nm) were observed. The exocarp had the highest μa values at 481 nm owing to its orange-yellow peel and the lowest μa values at 1423 nm, while the μa values of green mesocarp and pulp had no significant differences at all absorption peaks. The differences in reduced scattering coefficient (μs') spectra were obvious with a decreasing trend from the outermost (exocarp) to the innermost (pulp) layer and the stem to the calyx position in pulp layer, which mainly related to the different tissue structure. The MC simulation results indicated that the energy along the wavelength was mainly absorbed by the exocarp and green mesocarp, with a ‘diagnostic window’ appearing in 700–850 nm. As the source-detector distance increased, the mean optical pathlength and attenuation of detected photons in each tissue layer increased, while the contribution fraction to the detected diffuse reflectance signals by the exocarp, green mesocarp and pulp respectively decreased, increased and increased. To acquire more information about the pulp and ensure a good signal-to-noise ratio of the spectral signal, a source-detector distance of 7 mm with a suitable light source power would be a good choice. Furthermore, the best prediction models with good performance for SSC and moisture content were built based on the μa spectra, with the correlation coefficient of prediction (Rp) of 0.78–0.80, 0.76–0.88 and the root mean square error of prediction (RMSEP) of 0.83–0.92%, 0.70–0.93%. This study was the first attempt to measure the OPs of melon tissues and investigate the light propagation through melon fruit, which would provide a reference to develop nondestructive testing techniques or instruments for melon fruit based on Vis/NIR spectroscopy.