A Preliminary Comparative Study on the Centering Algorithms for CassiniISS NAC Images

Obtaining high precision is an important consideration for astrometric studies using images from the Narrow Angle Camera(NAC)of the Cassini Imaging Science Subsystem(ISS).Selecting the best centering algorithm is key to enhancing astrometric accuracy.In this study,we compared the accuracy of five centering algorithms:Gaussian fitting,the modified moments method,and three point-spread function(PSF)fitting methods(effective PSF(ePSF),PSFEx,and extended PSF(x PSF)from the Cassini Imaging Central Laboratory for Operations(CICLOPS)).We assessed these algorithms using 70 ISS NAC star field images taken with CL1 and CL2 filters across different stellar magnitudes.The ePSF method consistently demonstrated the highest accuracy,achieving precision below 0.03 pixels for stars of magnitude 8-9.Compared to the previously considered best,the modified moments method,the e PSF method improved overall accuracy by about 10%and 21%in the sample and line directions,respectively.Surprisingly,the xPSF model provided by CICLOPS had lower precision than the ePSF.Conversely,the ePSF exhibits an improvement in measurement precision of 23%and 17%in the sample and line directions,respectively,over the xPSF.This discrepancy might be attributed to the xPSF focusing on photometry rather than astrometry.These findings highlight the necessity of constructing PSF models specifically tailored for astrometric purposes in NAC images and provide guidance for enhancing astrometric measurements using these ISS NAC images.

Fabrication of PdSe2/GaAs Heterojunction for Sensitive Near-Infrared Photovoltaic Detector and Image Sensor Application

In this study,we have developed a high-sensitivity,near-infrared photodetector based on PdSe2/GaAs heterojunction,which was made by transferring a multilayered PdSe2 film onto a planar GaAs.The as-fabricated PdSe2/GaAs heterojunction device exhibited obvious photovoltaic behavior to 808 nm illumination,indicating that the near-infrared photodetector can be used as a self-driven device without external power supply.Further device analysis showed that the hybrid heterojunction exhibited a high on/off ratio of 1.16×10^5 measured at 808 nm under zero bias voltage.The responsivity and specific detectivity of photodetector were estimated to be 171.34 mA/W and 2.36×10^11 Jones,respectively.Moreover,the device showed excellent stability and reliable repeatability.After 2 months,the photoelectric characteristics of the near-infrared photodetector hardly degrade in air,attributable to the good stability of the PdSe2.Finally,the PdSe2/GaAs-based heterojunction device can also function as a near-infrared light sensor.

Turbidity analysis using visible and near-infrared light images

The conventional photoelectric detection system requires complex circuitry and spectroscopic systems as well as specialized personnel for its operation.To replace such a system,a method of measuring turbidity using a camera is proposed by combining the imaging characteristics of a digital camera and the high-speed information processing capability of a computer.Two turbidity measurement devices based on visible and near-infrared(NIR)light cameras and a light source driving circuit with constant light intensity were designed.The RGB data in the turbidity images were acquired using a self-developed image processing software and converted to the CIE Lab color space.Based on the relationship between the luminance,chromatic aberration,and turbidity,the turbidity detection models for luminance and chromatic aberration of visible and NIR light devices exhibiting values from 0-1000 NTU,less than 100 NTU,and more than 100 NTU were established.By comparing and analyzing the proposed models,the two measurement models with the best all-around performance were selected and fused to generate new measurement models.The experimental results prove that the correlation between the three models and the commercial turbidity meter measurements exhibite a significance value higher than 0.999.The error of the fusion model is within 1.05%,with a mean square error of 1.14.The visible light device has less error at low turbidity measurements and is less influenced by the color of the image.The NIR light device is more stable and accurate at full range and high turbidity measurements and is therefore more suitable for such measurements.

Novel imaging system for positioning of the indocyanine green (ICG) target;visible projection of the near-infrared fluorescence image

Background: Even though NIR fluorescence imaging has many advantages in SLN mapping and cancer detection, NIR fluorescence imaging shows a serious drawback that NIR cannot be detected by the naked eye without any detectors. This limitation further disturbs accurate SLN detection and adequate tumor resection resulting in the presence of cancerous cells near the boundaries of surgically removed tissues. Materials and methods: To overcome the drawback of the conventional NIR imaging method, we suggest a novel NIR imaging system which can make the NIR fluorescence image visible to the naked eye as NIR fluorescence image detected by a video camera is processed by a computer and then projected back onto the NIR fluorescence excitation position with a projector using conspicuous color light. Image processing techniques were used for projection onto the exact position of the NIR fluorescence image. Also, we implemented a phantom experiment to evaluate the performance of the developed NIR fluorescence projection system by use of the ICG. Results: The developed NIR fluorescence projection system was applied in normal mouse model to confirm the usefulness of the system in the clinical field. A BALB/c nude mouse was prepared to be applied in normal mouse model and 0.25 mg/ml stock solution of the ICG was injected through a tail vein of the mouse. From the application in normal mouse model, we could confirm that the injected ICG stayed in the liver of the mouse and verify that the projection system projected the ICG fluorescence image at the exact location of the ICG by performing laparotomy of the mouse. Conclusions: From the application in normal mouse model, we could verify that the ICG fluorescence image was precisely projected back on the site where ICG fluorescence generated. It can be demonstrated that the NIR fluorescence projection system can make it possible to visualize the invisible NIR fluorescence image and to realize that SLN mapping and cancer detection in clinical surgery.

MRI T_2 star mapping、T_1 images与3D DESS融合图在隐匿性膝关节软骨损伤中的应用

目的探讨T_2 star mapping、T_1 images与3D DESS融合伪彩图在关节软骨损伤中的诊断价值。方法对26例关节软骨损伤患者行T_2 star mapping、T_1 images和3D DESS扫描,并将T_1 images、T_2 star mapping与3D DESS图像融合,评价患者股骨、胫骨、髌骨关节软骨损伤程度并与关节镜结果对比,计算融合伪彩图诊断软骨损伤的特异性、敏感性及与关节镜诊断结果一致性。结果 T_1 images-3D DESS融合伪彩图诊断关节软骨损伤的敏感度、特异度及Kappa值分别为92.8%、93.0%、0.769,T_2 star mapping-3D DESS融合伪彩图诊断关节软骨损伤的敏感度、特异度及Kappa值分别为91.4%、94.2%、0.787。结论 T_2 star mapping、T_1 images与3D DESS融合伪彩图在关节软骨早期损伤评价上优于关节镜。

Evaluation of COC183B2 antibody targeting ovarian cancer by near-infrared fluorescence imaging

Objective: To evaluate the imaging potential of a novel near-infrared(NIR) probe conjugated to COC183 B2 monoclonal antibodies(MAb) in ovarian cancer(OC).Methods: The expression of OC183 B2 antigen in OC was determined by immunohistochemical(IHC) staining using tissue microarrays with the H-score system and immunofluorescence(IF) staining of tumor cell lines.Imaging probes with the NIR fluorescent dye cyanine 7(Cy7) conjugated to COC183 B2 Mab were chemically engineered. OC183 B2-positive human OC cells(SKOV3-Luc) were injected subcutaneously into BALB/c nude mice. Bioluminescent imaging(BLI) was performed to detect tumor location and growth. COC183 B2-Cy7 at 1.1,3.3, 10, or 30 μg were used for in vivo fluorescence imaging, and phosphate-buffered saline(PBS), free Cy7 dye and mouse isotype immunoglobulin G(IgG)-Cy7(delivered at the same doses as COC183 B2-Cy7) were used as controls.Results: The expression of OC183 B2 with a high H-score was more prevalent in OC tissue than fallopian tube(FT) tissue. Among 417 OC patients, the expression of OC183 B2 was significantly correlated with the histological subtype, histological grade, residual tumor size, relapse state and survival status. IF staining demonstrated that COC183 B2 specifically expressed in SKOV3 cells but not HeLa cells. In vivo NIR fluorescence imaging indicated that COC183 B2-Cy7 was mainly distributed in the xenograft and liver with optimal tumor-to-background(T/B)ratios in the xenograft at 30 μg dose. The highest fluorescent signals in the tumor were observed at 96 h postinjection(hpi). Ex vivo fluorescence imaging revealed the fluorescent signals mainly from the tumor and liver. IHC analysis confirmed that xenografts were OC183 B2 positive.Conclusions: COC183 B2 is a good candidate for NIR fluorescence imaging and imaging-guided surgery in OC.

Advances in surgical techniques for gastric cancer:Indocyanine green and near-infrared fluorescence imaging.Is it ready for prime time?

Surgery is still the primary curative treatment for gastric cancer,which includes resection of the tumor with adequate margins and extended lymphadenectomy.In order to improve the operative results and the quality of life of patients,several endeavors have been made toward precision medicine through image-guided surgery,allowing access to real-time intraoperative anatomy and accurate tumor staging.The goal of the surgeon is to achieve a more precise,individualized,and less invasive surgery without compromising oncological efficiency and safety.In this perspective,we have demonstrated the role of indocyanine green(ICG)and near-infrared(NIR)fluorescence imaging method in gastric cancer surgery.This technique may be used to improve localization of the tumor,detection of sentinel lymph nodes(SLN),real-time lymphatic mapping,and blood flow assessment(anastomosis perfusion).

Hyperspectral Images-Based Crop Classification Scheme for Agricultural Remote Sensing

Hyperspectral imaging is gaining a significant role in agricultural remote sensing applications.Its data unit is the hyperspectral cube which holds spatial information in two dimensions while spectral band information of each pixel in the third dimension.The classification accuracy of hyperspectral images(HSI)increases significantly by employing both spatial and spectral features.For this work,the data was acquired using an airborne hyperspectral imager system which collected HSI in the visible and near-infrared(VNIR)range of 400 to 1000 nm wavelength within 180 spectral bands.The dataset is collected for nine different crops on agricultural land with a spectral resolution of 3.3 nm wavelength for each pixel.The data was cleaned from geometric distortions and stored with the class labels and annotations of global localization using the inertial navigation system.In this study,a unique pixel-based approach was designed to improve the crops'classification accuracy by using the edge-preserving features(EPF)and principal component analysis(PCA)in conjunction.The preliminary processing generated the high-dimensional EPF stack by applying the edge-preserving filters on acquired HSI.In the second step,this high dimensional stack was treated with the PCA for dimensionality reduction without losing significant spectral information.The resultant feature space(PCA-EPF)demonstrated enhanced class separability for improved crop classification with reduced dimensionality and computational cost.The support vector machines classifier was employed for multiclass classification of target crops using PCA-EPF.The classification performance evaluation was measured in terms of individual class accuracy,overall accuracy,average accuracy,and Cohen kappa factor.The proposed scheme achieved greater than 90%results for all the performance evaluation metrics.The PCA-EPF proved to be an effective attribute for crop classification using hyperspectral imaging in the VNIR range.The proposed scheme is well-suited for practical applications of crops and landfill estimations using agricultural remote sensing methods.

Near-infrared fluorescent labeled CGRRAGGSC peptides for optical imaging of IL-11Rα in athymic mice bearing tumor xenografts

The interleukin-11(IL-11)and the IL-11 receptorα-subunit(IL-11Rα)have been demonstrated to regulate the invasion and proliferation of tumor cells.Our study intends to evaluate a noninvasive imaging of IL-11Rαexpression in breast tumors using near-infrared(NIR)fluorescent dye Cy7-labeled IL-11 mimic peptide CGRRAGGSC.This work evaluated the IL-11Rαexpression of breast tumor cells and the binding status of this peptide to IL-11Rαin vitro and in vivo by using Western blotting,immunofluorescence staining and near-infrared fluorescence imaging.Our biochemical study showed that IL-11Rαwas overexpressed in breast tumor cells(MCF-7).The cell-binding assay demonstrated specific binding of peptide CGRRAGGSC to MCF-7 cells in vitro.In vivo imaging results showed that NIR fluorescent signals of Cy7-CGRRAGGSC were selectively accumulated in tumor and metabolic organs.While in the blocking experiment,free CGRRAGGSC obviously blocked the concentration of the Cy7-CGRRAGGSC in the tumors.These results suggested that IL-11Rαmay be used as a potential target for noninvasive imaging in IL-11Rαoverexpressed tumors.Furthermore,the imaging agent of near-infrared fluorescent dye Cy7-labeled CGRRAGGSC is suitable for IL-11Rαexpression imaging study in vivo.

Automatic removal of false image stars in disk-resolved images of the Cassini Imaging Science Subsystem

Taking a large number of images,the Cassini Imaging Science Subsystem(ISS)has been routinely used in astrometry.In ISS images,disk-resolved objects often lead to false detection of stars that disturb the camera pointing correction.The aim of this study was to develop an automated processing method to remove the false image stars in disk-resolved objects in ISS images.The method included the following steps:extracting edges,segmenting boundary arcs,fitting circles and excluding false image stars.The proposed method was tested using 200 ISS images.Preliminary experimental results show that it can remove the false image stars in more than 95%of ISS images with disk-resolved objects in a fully automatic manner,i.e.,outperforming the traditional circle detection based on Circular Hough Transform(CHT)by 17%.In addition,its speed is more than twice as fast as that of the CHT method.It is also more robust(no manual parameter tuning is needed)when compared with CHT.The proposed method was also applied to a set of ISS images of Rhea to eliminate the mismatch in pointing correction in automatic procedure.Experiment results showed that the precision of final astrometry results can be improve by roughly 2 times that of automatic procedure without the method.It proved that the proposed method is helpful in the astrometry of ISS images in a fully automatic manner.

An Approach to Star Map Simulation for Star Sensor Considering the Effect of Image Motion

To test high resolution and dynamic performance of star sensor, a method of consideration image motion on Modeling the motion blur of star sensor is proposed. Firstly, image motion geometric model based on the rotation of Starlight vector is studied. Secondly, with the help of the normal distribution of static star image energy model, introducing the star image motion speed, obtaining the energy distribution function of moving stars, implementing high dynamic simulation of star map. Finally, establishing the simulation environment, through adjusting input parameters such as integral time, rate of change of three attitude angle, the launch time, location, then, important simulation data of stars observed by star sensor in orbit can quickly be obtained, such as navigation stars information, value and direction of image motion, intensity distribution, signal to noise ratio. This work is very important to research and evaluate the star image motion compensation algorithm.

Super-resolution Imaging of Telescopic Systems based on Optical-neural Network Joint Optimization

Optical telescopes are an important tool for acquiring optical information about distant objects,and resolution is an important indicator that measures the ability to observe object details.However,due to the effects of system aberration,atmospheric seeing,and other factors,the observed image of ground-based telescopes is often degraded,resulting in reduced resolution.This paper proposes an optical-neural network joint optimization method to improve the resolution of the observed image by co-optimizing the point-spread function(PSF)of the telescopic system and the image super-resolution(SR)network.To improve the speed of image reconstruction,we designed a generative adversarial net(LCR-GAN)with light parameters,which is much faster than the latest unsupervised networks.To reconstruct the PSF trained by the network in the optical path,a phase mask is introduced.It improves the image reconstruction effect of LCR-GAN by reconstructing the PSF that best matches the network.The results of simulation and verification experiments show that compared with the pure deep learning method,the SR image reconstructed by this method is rich in detail and it is easier to distinguish stars or stripes.

Initial Experience of NIR-II Fluorescence Imaging-Guided Surgery in Foot and Ankle Surgery

Optical imaging in the second near-infrared(NIR-II;900-1880 nm)window is currently a popular research topic in the field of biomedical imaging.This study aimed to explore the application value of NIR-II fluorescence imaging in foot and ankle surgeries.A lab-established NIR-II fluorescence surgical navigation system was developed and used to navigate foot and ankle surgeries which enabled obtaining more high-spatial-frequency information and a higher signal-to-background ratio(SBR)in NIR-II fluorescence images compared to NIR-I fluorescence images;our result demonstrates that NIR-II imaging could provide higher-contrast and larger-depth images to surgeons.Three types of clinical application scenarios(diabetic foot,calcaneal fracture,and lower extremity trauma)were included in this study.Using the NIR-II fluorescence imaging technique,we observed the ischemic region in the diabetic foot before morphological alterations,accurately determined the boundary of the ischemic region in the surgical incision,and fully assessed the blood supply condition of the flap.NIR-II fluorescence imaging can help surgeons precisely judge surgical margins,detect ischemic lesions early,and dynamically trace the perfusion process.We believe that portable and reliable NIR-II fluorescence imaging equipment and additional functional fluorescent probes can play crucial roles in precision surgery.

Preparation for CSST:Star-galaxy Classification using a Rotationally Invariant Supervised Machine Learning Method

Most existing star-galaxy classifiers depend on the reduced information from catalogs,necessitating careful data processing and feature extraction.In this study,we employ a supervised machine learning method(GoogLeNet)to automatically classify stars and galaxies in the COSMOS field.Unlike traditional machine learning methods,we introduce several preprocessing techniques,including noise reduction and the unwrapping of denoised images in polar coordinates,applied to our carefully selected samples of stars and galaxies.By dividing the selected samples into training and validation sets in an 8:2 ratio,we evaluate the performance of the GoogLeNet model in distinguishing between stars and galaxies.The results indicate that the GoogLeNet model is highly effective,achieving accuracies of 99.6% and 99.9% for stars and galaxies,respectively.Furthermore,by comparing the results with and without preprocessing,we find that preprocessing can significantly improve classification accuracy(by approximately 2.0% to 6.0%)when the images are rotated.In preparation for the future launch of the China Space Station Telescope(CSST),we also evaluate the performance of the GoogLeNet model on the CSST simulation data.These results demonstrate a high level of accuracy(approximately 99.8%),indicating that this model can be effectively utilized for future observations with the CSST.

Epileptic brain network mechanisms and neuroimaging techniques for the brain network

Epilepsy can be defined as a dysfunction of the brain network,and each type of epilepsy involves different brain-network changes that are implicated diffe rently in the control and propagation of interictal or ictal discharges.Gaining more detailed information on brain network alterations can help us to further understand the mechanisms of epilepsy and pave the way for brain network-based precise therapeutic approaches in clinical practice.An increasing number of advanced neuroimaging techniques and electrophysiological techniques such as diffusion tensor imaging-based fiber tra ctography,diffusion kurtosis imaging-based fiber tractography,fiber ball imagingbased tra ctography,electroencephalography,functional magnetic resonance imaging,magnetoencephalography,positron emission tomography,molecular imaging,and functional ultrasound imaging have been extensively used to delineate epileptic networks.In this review,we summarize the relevant neuroimaging and neuroelectrophysiological techniques for assessing structural and functional brain networks in patients with epilepsy,and extensively analyze the imaging mechanisms,advantages,limitations,and clinical application ranges of each technique.A greater focus on emerging advanced technologies,new data analysis software,a combination of multiple techniques,and the construction of personalized virtual epilepsy models can provide a theoretical basis to better understand the brain network mechanisms of epilepsy and make surgical decisions.

Some Inequalities for the L_p-polar Curvature Images of Star Bodies

Zhu,Lü and Leng extended the concept of L_p-polar curvature image. We continuously study the L_p-polar curvature image and mainly expound the relations between the volumes of star bodies and their L_p-polar curvature images in this article. We first establish the L_p-affine isoperimetric inequality associated with L_p-polar curvature image. Secondly,we give a monotonic property for L_p-polar curvature image. Finally, we obtain an interesting equation related to L_p-projection body of L_p-polar curvature image and L_p-centroid body.

NEAR-INFRARED,BROAD-BAND SPECTRAL IMAGING OF THE HUMAN BREAST FOR QUANTITATIVE OXIMETRY:APPLICATIONS TO HEALTHY AND CANCEROUS BREASTS

We have examined ten human subjects with a previously developed instrument for near-infrared diffuse spectral imaging of the female breast.The instrument is based on a tandem,planar scan of two collinear optical fibers(one for illumination and one for collection)to image a gently compressed breast in a transmission geometry.The optical data collection features a spatial sampling of 25 points/cm2 over the whole breast,and a spectral sampling of 2 points/nm in the 650-900nm wavelength range.Of the ten human subjects examined,eight are healthy subjects and two are cancer patients with unilateral invasive ductal carcinoma and ductal carcinoma in situ,respectively.For each subject,we generate second-derivative images that identify a network of highly absorbing structures in the breast that we assign to blood vessels.A previously developed paired-wavelength spectral method assigns oxygenation values to the absorbing structures displayed in the second-derivative images.The resulting oxygenation images feature average values over the whole breast that are significantly lower in cancerous breasts(69±14%,n=2)than in healthy breasts(85±7%,n=18)(p<0.01).Furthermore,in the two patients with breast cancer,the average oxygenation values in the cancerous regions are also significantly lower than in the remainder of the breast(invasive ductal carcinoma:49±11%vs 61±16%,p<0.01;ductal carcinoma in situ:58±8%vs 77±11%,p<0.001).

Observation of Atherosclerotic Plaque Phantoms through Saline or Blood Layers by Near-Infrared Hyperspectral Imaging

We observed atherosclerotic plaque phantoms using a novel near-infrared (NIR) hyperspectral imaging (HSI) technique. Data were obtained through saline or blood layers to simulate an angioscopic environment for the phantom. For the study, we developed a NIR-HSI system with an NIR supercontinuum light source and mercury-cadmium-telluride camera. Apparent spectral absorbance was obtained at wavelengths of 1150 - 2400 nm. Hyperspectral images of lipid were constructed using a spectral angle mapper algorithm. Bovine fat covered with saline or blood was observed using hyperspectral images at a wavelength around 1200 nm. Our results show that NIR-HSI is a promising angioscopic technique with the potential to identify lipid-rich plaques without clamping and saline injection.

Recent developments of fluorescence imaging technology in the second near-infrared window

Background:Fluorescence bio-imaging in the second near-infrared window(NIR-II FL,1000-1700nm)has great potential in clinical theranostics,which is of great importance providing precise locations of lesions and molecular dynamic actions simultaneously in a single nanoprobe.Methods:T here has been an upsurge of multidisciplinary research focusing on developing functional types of inorganic and organic nanoprobes that can be used for NIR-II FL with the high spatiotemporal resolution,deep tissue penetration,and negligible auto-fluorescence.Results:In this mini-review,we summarize recent progress in inorganic/organic NIR-II FL nanoprobes.We introduce the design and properties of inorganic and organic nanoprobes,in the order of single-walled carbon nanotubes,quantum dots,rare-earth-doped nanoparticles,metal nanoclusters and organic fluorophores,expect to realize precise diagnosis and efficient image-guided therapy.Conclusion:Meanwhile,to elucidate the problems and perspectives,we aim to offer diverse biological applications of inorganic/organic NIR-II FL nanoprobes and accelerate the clinical transformation progress.

PREPARATION AND CHARACTERIZATION OF WATER-SOLUBLE NEAR-INFRARED EMITTING PbS QUANTUM DOTS

A new facile method for preparing water-soluble near-infrared （NIR）-emitting PbS quantum dots （QDs） is proposed by using N-acetyl-L-cysteine （NAC, a derivate of L-cysteine） as its stabilizer. The influence of the precursor Pb/S molar ratio, the Pb/NAC molar ratio, and the pH of original solution on optical properties is explored. Results show that aqueous PbS QDs with strong NIR fluorescence can be prepared and their photoluminescence emission peaks can be tuned from 895 nm to 970 nm. Studies indicate that such aqueous QDs have a potential application in biomedical imaging, especially in noninvasive in vivo fluorescence imaging. In addition, the resulting PbS QDs are further characterized by a transmission electron microscopy and X-ray diffraction analysis.