Machine learning and deep learning enabled age estimation on medial clavicle CT images.

The medial clavicle epiphysis is a crucial indicator for bone age estimation (BAE) after hand maturation. This study aimed to develop machine learning (ML) and deep learning (DL) models for BAE based on medial clavicle CT images and evaluate the performance on normal and variant clavicles. This study retrospectively collected 1049 patients (mean± SD: 22.50±4.34 years) and split them into normal training and test sets, and variant training and test sets. An additional 53 variant clavicles were incorporated into the variant test set. The development stages of normal MCE were used to build a linear model and support vector machine (SVM) for BAE. The CT slices of MCE were automatically segmented and used to train DL models for automated BAE. Comparisons were performed by linear versus ML versus DL, and normal versus variant clavicles. Mean absolute error (MAE) and classification accuracy was the primary parameter of comparison. For BAE, the SVM had the best MAE of 1.73 years, followed by the commonly-used CNNs (1.77-1.93 years), the linear model (1.94 years), and the hybrid neural network CoAt Net (2.01 years). In DL models, SE Net 18 was the best-performing DL model with similar results to SVM in the normal test set and achieved an MAE of 2.08 years in the external variant test. For age classification, all the models exhibit superior performance in the classification of 18-, 20-, 21-, and 22-year thresholds with limited value in the 16-year threshold. Both ML and DL models produce desirable performance in BAE based on medial clavicle CT.

Automatic measurement system for large-aperture-angle non-holonomic spherical stitching with laser differential confocal interference.

In response to the urgent need for highly precise and efficient stitching measurements of large-aperture-angle non-holonomic spherical surfaces, a differential confocal interference automatic stitching measurement system for large-aperture-angle non-holonomic spherical surfaces was developed. The system realizes precise positioning of the confocal position through differential confocal precise focusing technology. Through the stitching model, coordinate transformation and error compensation were performed on subaperture data, and the stitching measurement of the spherical surface shape was realized. The positions and postures of the tested samples were adjusted automatically using an automatic adjustment workbench. The stitching measurement accuracy of this measurement system can attain 0.0013λ, relative error can attain 1.36%, and measurement time for eight subaperture stitching is 6 min. This system achieves automatic and rapid adjustment of large-aperture-angle spherical elements and high-precision, nondestructive, fast, and automatic measurement of surface stitching.

Research Progress on Dental Age Estimation Based on MRI Technology.

Dental age estimation is a crucial aspect and one of the ways to accomplish forensic age estimation, and imaging technology is an important technique for dental age estimation. In recent years, some studies have preliminarily confirmed the feasibility of magnetic resonance imaging (MRI) in evaluating dental development, providing a new perspective and possibility for the evaluation of dental development, suggesting that MRI is expected to be a safer and more accurate tool for dental age estimation. However, further research is essential to verify its accuracy and feasibility. This article reviews the current state, challenges and limitations of MRI in dental development and age estimation, offering reference for the research of dental age assessment based on MRI technology.

Zn-MOF hydrogel: regulation of ROS-mediated inflammatory microenvironment for treatment of atopic dermatitis.

Atopic dermatitis (AD) is a chronic and recurrent inflammation disease associated with immune dysfunction. The high level of reactive oxygen species (ROS) causes high oxidative stress and further results in the deterioration of AD. At the same time, the ROS produced by bacterial infection can further aggravate AD. Here, the prepared PVA-based hydrogel (Gel) has a high ROS scavenging ability, and the antibacterial agent Zn-MOF(ZIF-8) loaded into the hydrogel shows a lasting and effective antibacterial activity. Thus, a Zn-MOF hydrogel (Gel@ZIF-8) is prepared to regulate ROS-mediated inflammatory microenvironment. In vitro experiments show that Gel@ZIF-8 has good antibacterial effect and cell biocompatibility. In the AD-induced mouse model, Gel@ZIF-8 can significantly enhance the therapeutic effect, such as reduce the thickness of epidermis, the number of mast cells and IgE antibodies. The results indicate that the ROS-scavenging hydrogel could treat the AD by regulating the inflammatory microenvironment, providing a promising treatment for managing AD.

High spatial resolution of topographic imaging and Raman mapping by differential correlation-confocal Raman microscopy.

Confocal Raman microscopy (CRM) has found applications in many fields as a consequence of being able to measure molecular fingerprints and characterize samples without the need to employ labelling methods. However, limited spatial resolution has limited its application when identification of sub-micron features in materials is important. Here, we propose a differential correlation-confocal Raman microscopy (DCCRM) method to address this. This new method is based on the correlation product method of Raman scattering intensities acquired when the confocal Raman pinhole is placed at different (defocused) positions either side of the focal plane of the Raman collection lens. By using this correlation product, a significant enhancement in the spatial resolution of Raman mapping can be obtained. Compared with conventional CRM, these are 23.1% and 33.1% in the lateral and axial directions, respectively. We illustrate these improvements using in situ topographic imaging and Raman mapping of graphene, carbon nanotube, and silicon carbide samples. This work can potentially contribute to a better understanding of complex nanostructures in non-real time spectroscopic imaging fields.

Steep freeform measurement method based on a normal transverse differential confocal.

A normal transverse laser differential confocal freeform measurement (NTDCFM) method was proposed to address the high-precision measurement difficulty of steep freeform surfaces with large variations in inclination, scattering, and reflectance. Using D-shaped diaphragm technology, the freeform surface under test (FSUT) axial variation transformed into a spot transverse movement on the detection focal plane. Meanwhile, a 2D position sensitive detector (PSD) was used to obtain the normal vector of the sampling points so that the measuring sensor's optical axis could track the FSUT normal direction. The focus tracking method extended the sensor measurement range. Theoretical analysis and experimental results showed that the axial resolution of the NTDCFM was better than 0.5 nm, the direction resolution of the normal vector was 0.1°, the maximum surface inclination could be measured up to 90°, the sensor range was 5 mm, and the measurement repeatability of the FSUT was better than 9 nm. It provides an effective new anti-inclination, anti-scattering, and anti-reflectivity method for accurately measuring steep freeform surfaces.

Freeform measurement method based on differential confocal and real-time comparison.

To meet the need for the high-precision contactless measurement of the freeform surface profile during the manufacturing, we propose a high-precision measurement method that combines the laser differential confocal trigger sensor (LDCTS) and the real-time comparison method using reference planes (RCMRP). LDCTS is used to measure the freeform surface under test (FSUT), which enables the high-precision measurement of the surface profile with the large roughness and local inclination. Through the real-time comparisons of the coordinate changes of the reference planes and FSUT, the dominant straightness and rotation errors can be separated based on the error model and thus the spatial motion errors can be significantly reduced along all three axes. Combing these two strategies, we find that the inclination measurement capacity becomes larger than 25° and the repeated measurement accuracy is improved to be better than 10 nm within the horizontal scanning range of 150 mm × 150 mm. Compared with the non-RCMRP method, the repeated measurement accuracy is improved by at least 5 times. We believe the proposed method provides a strategy for the high-precision measurement of freeform surface profile with large local inclination and roughness during different manufacturing periods.

High precision even-power phase modulation method for a self-mixing displacement sensor under the weak feedback regime.

A novel method called even-power phase modulation is proposed in a self-mixing displacement sensor to improve measuring accuracy, to the best of our knowledge, which is realized by combining the even-power fast algorithm with the sinusoidal phase-modulation method. By performing the even-power fast algorithm in the self-mixing interference system, the spectrum of harmonic components is broadened. In this case, the extracted first and second harmonic components in the frequency domain contain rich information, and the displacement of the target can be accurately reconstructed. The principle and signal processing approach are introduced in detail, and the simulation results show that the reconstruction error can be effectively reduced compared with the electro-optic modulator phase modulation method. A series of experiments at different vibration amplitudes is conducted to confirm the feasibility and effectiveness of the method. An amplitude of 120 nm is proved to be measurable, and the absolute error is 10 nm, which shows great potential in the field of non-contact nanometer vibration measurement sensors.

Predicting Blood Glucose Concentration after Short-Acting Insulin Injection Using Discontinuous Injection Records.

Diabetes is an increasingly common disease that poses an immense challenge to public health. Hyperglycemia is also a common complication in clinical patients in the intensive care unit, increasing the rate of infection and mortality. The accurate and real-time prediction of blood glucose concentrations after each short-acting insulin injection has great clinical significance and is the basis of all intelligent blood glucose control systems. Most previous prediction methods require long-term continuous blood glucose records from specific patients to train the prediction models, resulting in these methods not being used in clinical practice. In this study, we construct 13 deep neural networks with different architectures to atomically predict blood glucose concentrations after arbitrary independent insulin injections without requiring continuous historical records of any patient. Using our proposed models, the best root mean square error of the prediction results reaches 15.82 mg/dL, and 99.5% of the predictions are clinically acceptable, which is more accurate than previously proposed blood glucose prediction methods. Through the re-validation of the models, we demonstrate the clinical practicability and universal accuracy of our proposed prediction method.

High-precision laser transverse differential confocal radius measurement method.

To meet the current need for high-precision and environment-insensitive measurement of the radius of curvature (ROC), we proposed a transverse differential confocal radius measurement (TDCRM) method based on the optical system of the confocal ROC measurement. Using a D-shaped aperture and the virtual pinhole technology, two signals, analogous to the pre-focus and post-focus signals in the two-detector-based differential confocal radius measurement (DCRM), can be obtained from two segmentations of a single CCD image. The difference of these two signals can be used to precisely determine the cat's-eye and confocal positions, thereby achieving the high-accuracy ROC measurement as DCRM with a relative repeatability of 3.4 ppm. Furthermore, compared to DCRM, no optical alignment is needed after replacing the objective lens, which significantly reduces the time cost of measurements. We believe this novel and high-precision ROC measurement method will widen its application to optical manufacturing and provide an exciting opportunity for mass production of the ROC measurement instrument.

Interferometric microscope with a confocal focusing for inner surface defect detection of ICF capsule.

Inner surface defects of inertial confinement fusion (ICF) capsule are a key factor leading to ignition failure; however, there are still no effective and non-destructive detection methods available. To solve this problem, we propose the first interferometric microscope with confocal focusing (CFIM). CFIM first uses confocal technology to achieve accurate axial positioning of both capsule and the camera, thereby ensuring that the inner surface of the capsule is precisely and clearly imaged at the camera. Then, phase-shifting interferometry based on a short-coherence source and a spherical reference is applied to obtain inner defects result from null inner surface interferograms. In addition, in-situ focusing is realized by the axial adjustment of camera, but not by the capsule, to ensure that the outer defects and the fake inner defects caused by it have the same pixel coordinates, thereby solving the confusion of fake inner defects. The comparative experimental results of the CFIM and the scanning electron microscope (destructive detection) prove the feasibility of the proposed method. With unique precision confocal focusing and in-situ focusing ability, CFIM provides the first approach for non-destructive detection of inner surface defects of ICF capsule to the best of our knowledge.

The neural system of metacognition accompanying decision-making in the prefrontal cortex.

Decision-making is usually accompanied by metacognition, through which a decision maker monitors uncertainty regarding a decision and may then consequently revise the decision. These metacognitive processes can occur prior to or in the absence of feedback. However, the neural mechanisms of metacognition remain controversial. One theory proposes an independent neural system for metacognition in the prefrontal cortex (PFC); the other, that metacognitive processes coincide and overlap with the systems used for the decision-making process per se. In this study, we devised a novel "decision-redecision" paradigm to investigate the neural metacognitive processes involved in redecision as compared to the initial decision-making process. The participants underwent a perceptual decision-making task and a rule-based decision-making task during functional magnetic resonance imaging (fMRI). We found that the anterior PFC, including the dorsal anterior cingulate cortex (dACC) and lateral frontopolar cortex (lFPC), were more extensively activated after the initial decision. The dACC activity in redecision positively scaled with decision uncertainty and correlated with individual metacognitive uncertainty monitoring abilities-commonly occurring in both tasks-indicating that the dACC was specifically involved in decision uncertainty monitoring. In contrast, the lFPC activity seen in redecision processing was scaled with decision uncertainty reduction and correlated with individual accuracy changes-positively in the rule-based decision-making task and negatively in the perceptual decision-making task. Our results show that the lFPC was specifically involved in metacognitive control of decision adjustment and was subject to different control demands of the tasks. Therefore, our findings support that a separate neural system in the PFC is essentially involved in metacognition and further, that functions of the PFC in metacognition are dissociable.

Forensic age estimation based on magnetic resonance imaging of the proximal humeral epiphysis in Chinese living individuals.

Forensic age estimation in living individuals is mainly based on radiological features, but direct radiography and computed tomography lead to a rise in ethical concerns due to radiation exposure. Thus, the contribution of magnetic resonance imaging (MRI) to age estimation of living individuals is a subject of ongoing research. In the current study, MRIs of shoulder were retrospectively collected from a modern Chinese Han population and data from 835 individuals (599 males and 236 females) in the age group 12 to 30 years were obtained. A staging technique based on (Schmidt et al. Int J Legal Med 121(4):321-324, 2007) and (Kellinghaus et al. Int J Legal Med 124(4):321-325, 2010) was used and all images were evaluated with T1-wieghted turbo spin echo (T1-TSE) sequence and T2-weighed fat suppression (T2-FS) sequence. One-sided images were assessed because data from both sides were considered coincidental, as no significant differences were found (P > 0.05). Two MRI sequences were evaluated separately and subsequently compared. Regression models and supportive vector classification (SVC) models were established accordingly. The intraobserver and interobserver agreement levels were good. Compared with T1-TSE sequence, the R2 values of T2-FS sequence were generally higher, while the mean absolute deviation (MAD) values were slightly lower. For T2-FS sequence, the MAD value was 1.49 years in males and 2.19 years in females. With two MRI sequences incorporated, the SVC model obtained with 85.7% correctly classified minors and 96.2% correctly classified adults in males, while 83.3% and 98.0% respectively in females. In conclusion, T2-FS sequence may slightly outperform the T1-TSE sequence in shoulder MRI analysis for age estimation, while shoulder MRIs could be a reliable prediction indicator for the 18-year threshold and two MRI sequences incorporated are encouraged.

A general purpose MALDI matrix for the analyses of small organic, peptide and protein molecules.

Matrix-assisted laser desorption/ionization mass spectrometry (MALDI MS) has been widely applied for the analysis of large biomolecules. The emergence of inorganic material substrates and new organic matrices extends the use of MALDI MS for small molecule analyses. However, there are usually preferred matrices for different types of analytes. Here, an organic compound, 4-hydroxy-3-nitrobenzonitrile, was found to be a general purpose matrix for the analyses of small organic, peptide and protein molecules. In particular, 4-hydroxy-3-nitrobenzonitrile has a strong UV absorption property, and it provides a clean background in the low mass range. Its analytical performances as a UV-laser matrix were demonstrated for different types of analytes, including organic drugs, peptides, proteins, mouse brain tissue and bacteria. Compared with commercial matrices, this new matrix has better performances when analyzing small molecules, such as drugs, peptides and lipids, while it has similar performances when analyzing proteins.

Wavelength calibration methods in laser wavelength measurement.

At present, accurate wavelength calibration plays an important role in laser spectrum measurements. Although the wavelength calibration methods have been investigated for a long time, there are no techniques that are particularly designed for laser spectral calibration to the best of our knowledge. A mathematical model for calibrating a pulse laser wavelength is first established, to the best of our knowledge. According to the analysis formula of dispersion aberration, a flat-field concave grating in the near-infrared band is designed. Then, a wavelength calibration model based on concave grating spectroscopy is proposed. Through adjusting the spectra of each pixel, we design a calibration algorithm based on the cubic spline interpolation and kernel regression methods. By compensating and interpolating spectral data, accurate wavelengths are obtained. Finally, some experiments verify the calibration performance of the proposed method. Meanwhile, the uncertainty of measurement is also analyzed.

Divided-aperture confocal Brillouin microscopy for simultaneous high-precision topographic and mechanical mapping.

Confocal Brillouin microscopy (CBM) is a novel and powerful technique for providing non-contact and direct readout of the micro-mechanical properties of a material, and thus used in a broad range of applications, including biological tissue detection, cell imaging, and material characterization in manufacturing. However, conventional CBMs have not enabled high precision mechanical mapping owing to the limited depth of focus and are subject to system drift during long-term measurements. In this paper, a divided-aperture confocal Brillouin microscopy (DCBM) is proposed to improve the axial focusing capability, stability, and extinction ratio of CBM. We exploit high-sensitivity divided-aperture confocal technology to achieve an unprecedented 100-fold enhancement in the axial focusing sensitivity of the existing CBMs, reaching 5 nm, and to enhance system stability. In addition, the dark-field setup improves the extinction ratio by 20 dB. To the best of our knowledge, our method achieves the first in situ topographic imaging and mechanical mapping of the sample and provides a new approach for Brillouin scattering applications in material characterization.

High-precision laser differential confocal measurement method for multi-geometric parameters of inner and outer spherical surfaces of laser fusion capsules.

We propose a well-integrated, high-efficiency, high-precision, and non-destructive differential confocal measurement method for the multi-geometric parameters of the inner and outer spherical surfaces of laser fusion capsules. Based on the laser differential confocal measurement system with high tomography fixed-focus ability and high spatial resolution, the proposed method is used to perform the fixed-focus trigger measurement of the outer vertex, the inner vertex, and the spherical center of the capsule. From the rotation measurement around the Y-axis and the transposition measurement around the Z-axis, the inner and outer diameters, the three-dimensional inner and outer profiles, the shell thickness uniformity, and the shell non-concentricity of the capsule are measured with high precision and no damage. To the best of our knowledge, this is the first method to achieve the high-precision measurement for the multi-geometric parameters of the capsule inner and outer spherical surfaces with the same instrument.

Laser confocal vibration measurement method with high dynamic range.

A new laser confocal vibration measurement method (LCVM) is proposed to meet the requirements of high precision and high dynamic range measurements in micro and nano electromechanical systems. The proposed method uses different measurement modes to ensure that the amplitude solution interval of the out-of-plane is always in the optimal test interval of a confocal curve with the highest sensitivity to axial displacement, and thereby achieving the high-precision extraction of large-scale frequency and the high-precision measurement of large-scale amplitude. Using a 100×, NA=0.9 objective lens with a working distance of 1 mm, the theoretical analysis and preliminary experimental results indicate that the maximum measurable amplitude is 500 µm, the displacement resolution of the amplitude is 4 nm, and the measurable frequency range limited by electrical design is 0-120 MHz. The LCVM provides a novel approach for out-of-plane vibration measurements.

Differential confocal self-collimation method for high-accuracy measurements of lens decentration.

A differential confocal self-collimation decentration measurement method (DCSDM) is proposed. It uses the differential confocal method to precisely identify the center and vertex positions of the tested lens surface, thereby obtaining the radius of curvature. Then, it uses the self-collimation light-path to detect the position of the reflected light during the rotation of the tested surface, thereby obtaining the center bias. Finally, it calculates the decentration. Theoretical analysis and experiments indicate that DCSDM achieves an accuracy of 0.069". Compared with existing methods, DCSDM significantly reduces the focusing error by using differential techniques, prevents multiple clamping errors by integrating the radius and center bias measurements in one system, and is a feasible method for decentration measurement.

Dual differential confocal method for surface profile measurement with a large sensing measurement range.

To meet the requirements of the large sensing measurement range and high axial depth resolution for profile measurement, a dual differential confocal method (DDCM) is proposed in this paper. The DDCM uses the confocal signal to process separately the signal of two pinholes with axial offset, and it adds the two processed signals to obtain an axial response curve with a large slope and linear response range, thereby achieving a high-precision surface profile measurement with no axial scanning. Preliminary experiments show that the DDCM has a sensing measurement range of 0.54 µm and an axial resolution of 1 nm at the numerical aperture of 0.9. Furthermore, the sensing measurement range of the DDCM is approximately 2.9 times that of the differential confocal microscopy.