Cerebrovascular segmentation from mesoscopic optical images using Swin Transformer

Vascular segmentation is a crucial task in biomedical image processing,which is significant for analyzing and modeling vascular networks under physiological and pathological states.With advances in fluorescent labeling and mesoscopic optical techniques,it has become possible to map the whole-mouse-brain vascular networks at capillary resolution.However,segmenting vessels from mesoscopic optical images is a challenging task.The problems,such as vascular signal discontinuities,vessel lumens,and background fluorescence signals in mesoscopic optical images,belong to global semantic information during vascular segmentation.Traditional vascular segmentation methods based on convolutional neural networks(CNNs)have been limited by their insufficient receptive fields,making it challenging to capture global semantic information of vessels and resulting in inaccurate segmentation results.Here,we propose SegVesseler,a vascular segmentation method based on Swin Transformer.SegVesseler adopts 3D Swin Transformer blocks to extract global contextual information in 3D images.This approach is able to maintain the connectivity and topology of blood vessels during segmentation.We evaluated the performance of our method on mouse cerebrovascular datasets generated from three different labeling and imaging modalities.The experimental results demonstrate that the segmentation effect of our method is significantly better than traditional CNNs and achieves state-of-the-art performance.

Tree species classification using deep learning and RGB optical images obtained by an unmanned aerial vehicle

The diversity of tree species and the complexity of land use in cities create challenging issues for tree species classification.The combination of deep learning methods and RGB optical images obtained by unmanned aerial vehicles(UAVs) provides a new research direction for urban tree species classification.We proposed an RGB optical image dataset with 10 urban tree species,termed TCC10,which is a benchmark for tree canopy classification(TCC).TCC10 dataset contains two types of data:tree canopy images with simple backgrounds and those with complex backgrounds.The objective was to examine the possibility of using deep learning methods(AlexNet,VGG-16,and ResNet-50) for individual tree species classification.The results of convolutional neural networks(CNNs) were compared with those of K-nearest neighbor(KNN) and BP neural network.Our results demonstrated:(1) ResNet-50 achieved an overall accuracy(OA) of 92.6% and a kappa coefficient of 0.91 for tree species classification on TCC10 and outperformed AlexNet and VGG-16.(2) The classification accuracy of KNN and BP neural network was less than70%,while the accuracy of CNNs was relatively higher.(3)The classification accuracy of tree canopy images with complex backgrounds was lower than that for images with simple backgrounds.For the deciduous tree species in TCC10,the classification accuracy of ResNet-50 was higher in summer than that in autumn.Therefore,the deep learning is effective for urban tree species classification using RGB optical images.

Mountain Glacier Flow Velocities Analyzed from Satellite Optical Images

Mountain glaciers are sensitive to environment. It is important to acquire ice flow velocities over time for glacier research and hazard forecast. For this paper, cross-correlating of optical images is used to monitor ice flow velocities, and an improvement, which is called ＂moving grid,＂ is made to this method. For this research, two remote-sensing images in a certain glacier area, dur-ing different times are selected. The first image is divided into grids, and we calculated the correlation coefficient of each window in the grid with the window on the second image. The window with the highest correlation coefficient is considered the counter-part one on the first image. The displacement of the two corresponding windows is the movement of the glacier, and it is used to calculate glacier surface velocity. Compared to the traditional way of dividing an image with ascertain grid, this method uses small steps to move the grid from one location to another adjacent location until the whole glacier area is covered in the image, thus in-creasing corresponding point density. We selected a glacier in the Tianshan Mountains for this experiment and used two re-mote-sensing images with a 10-year interval to determine this method.

An Intelligent Detection Method for Optical Remote Sensing Images Based on Improved YOLOv7

To address the issue of imbalanced detection performance and detection speed in current mainstream object detection algorithms for optical remote sensing images,this paper proposes a multi-scale object detection model for remote sensing images on complex backgrounds,called DI-YOLO,based on You Only Look Once v7-tiny(YOLOv7-tiny).Firstly,to enhance the model’s ability to capture irregular-shaped objects and deformation features,as well as to extract high-level semantic information,deformable convolutions are used to replace standard convolutions in the original model.Secondly,a Content Coordination Attention Feature Pyramid Network(CCA-FPN)structure is designed to replace the Neck part of the original model,which can further perceive relationships between different pixels,reduce feature loss in remote sensing images,and improve the overall model’s ability to detect multi-scale objects.Thirdly,an Implicitly Efficient Decoupled Head(IEDH)is proposed to increase the model’s flexibility,making it more adaptable to complex detection tasks in various scenarios.Finally,the Smoothed Intersection over Union(SIoU)loss function replaces the Complete Intersection over Union(CIoU)loss function in the original model,resulting in more accurate prediction of bounding boxes and continuous model optimization.Experimental results on the High-Resolution Remote Sensing Detection(HRRSD)dataset demonstrate that the proposed DI-YOLO model outperforms mainstream target detection algorithms in terms of mean Average Precision(mAP)for optical remote sensing image detection.Furthermore,it achieves Frames Per Second(FPS)of 138.9,meeting fast and accurate detection requirements.

SEGMENTATION AND CORRELATION OF OPTICAL COHERENCE TOMOGRAPHY AND X-RAY IMAGES FOR BREAST CANCER DIAGNOSTICS

Pre-operative X ray mammography and int raoperative X-ray specimen radiography are routinely used to identify breast cancer pathology.Recent advances in optical coherence tomography(OCT)have enabled its 1use for the intraoperative assessment of surgical margins during breast cancer surgery.While each modality offers distinct contrast of normal and pathological features,there is an essential need to correlate image based features between the two modalities to take adv antage of the diagnostic capabilities of each technique.We compare OCT to X-ray images of resected human breast tissue and correlate different tissue features between modalities for future use in real-tine intraoperative OCT imaging.X ray imaging(specimen radiography)is currently used during surgical breast cancer procedures to verify tumor margins,but cannot image tissue in situ.OCT has the potential to solve this problem by providing intrao-perative imaging of the resected specimen as well as the in situ tumor cavity.OCT and micro-CT(X-ray)images are automatically segmented using different computational approaches,and quantitatively compared to determine the ability of these algorithms to automat ically differentiate regions of adipose tissue from tumor.Furthermore,two-dimensional(2D)and three-dimensional(3D)results are compared.These correlations,combined with real-time intraoperative OCT,have the potential to identify possible regions of tumor within breast tissue which correlate to tumor regions identified previously on X-ray imaging(mammography or specimen radiography).

Measurement of optical coherence structures of random optical fields using generalized Arago spot experiment

The optical coherence structures of random optical fields can determine beam propagation behavior,light–matter interactions,etc.Their performance makes a light beam robust against turbulence,scattering,and distortion.Recently,we proposed optical coherence encryption and robust far-field optical imaging techniques.All related applications place a high demand on precision in the experimental measurements of complex optical coherence structures,including their real and imaginary parts.Past studies on these measurements have mainly adopted theoretical mathematical approximations,limited to Gaussian statistic involving speckle statistic(time-consuming),or used complicated and delicate optical systems in the laboratory.In this study,we provide:a robust,convenient,and fast protocol to measure the optical coherence structures of random optical fields via generalized Arago(or Poisson)spot experiments with rigorous mathematical solutions.Our proposal only requires to capture the intensity thrice,and is applicable to any optical coherence structures,regardless of their type or optical statistics.The theoretical and experimental results demonstrated that the real and imaginary parts of the structures could be simultaneously recovered with high precision.We believe that such a protocol can be widely employed in phase measurement,optical imaging,and image transfer.

Optical image encryption algorithm based on a new four-dimensional memristive hyperchaotic system and compressed sensing

Some existing image encryption schemes use simple low-dimensional chaotic systems, which makes the algorithms insecure and vulnerable to brute force attacks and cracking. Some algorithms have issues such as weak correlation with plaintext images, poor image reconstruction quality, and low efficiency in transmission and storage. To solve these issues,this paper proposes an optical image encryption algorithm based on a new four-dimensional memristive hyperchaotic system(4D MHS) and compressed sensing(CS). Firstly, this paper proposes a new 4D MHS, which has larger key space, richer dynamic behavior, and more complex hyperchaotic characteristics. The introduction of CS can reduce the image size and the transmission burden of hardware devices. The introduction of double random phase encoding(DRPE) enables this algorithm has the ability of parallel data processing and multi-dimensional coding space, and the hyperchaotic characteristics of 4D MHS make up for the nonlinear deficiency of DRPE. Secondly, a construction method of the deterministic chaotic measurement matrix(DCMM) is proposed. Using DCMM can not only save a lot of transmission bandwidth and storage space, but also ensure good quality of reconstructed images. Thirdly, the confusion method and diffusion method proposed are related to plaintext images, which require both four hyperchaotic sequences of 4D MHS and row and column keys based on plaintext images. The generation process of hyperchaotic sequences is closely related to the hash value of plaintext images. Therefore, this algorithm has high sensitivity to plaintext images. The experimental testing and comparative analysis results show that proposed algorithm has good security and effectiveness.

Real-time and high-transmission middle-infrared optical imaging system based on a pixel-wise metasurface micro-polarization array

Real-time polarization medium-wave infrared(MIR)optical imaging systems enable the acquisition of infrared and polarization information for a target.At present,real-time polarization MIR devices face the following problems:poor real-time performance,low transmission and high requirements for fabrication and integration.Herein,we aim to improve the performance of real-time polarization imaging systems in the MIR waveband and solve the above-mentioned defects.Therefore,we propose a MIR polarization imaging system to achieve real-time polarization-modulated imaging with high transmission as well as improved performance based on a pixel-wise metasurface micro-polarization array(PMMPA).The PMMPA element comprises several linear polarization(LP)filters with different polarization angles.The optimization results demonstrate that the transmittance of the center field of view for the LP filters is up to 77%at a wavelength of4.0μm and an extinction ratio of 88 d B.In addition,a near-diffraction-limited real-time MIR imaging optical system is designed with a field of view of 5°and an F-number of 2.The simulation results show that an MIR polarization imaging system with excellent real-time performance and high transmission is achieved by using the optimized PMMPA element.Therefore,the method is compatible with the available optical system design technologies and provides a way to realize real-time polarization imaging in MIR wavebands.

Research on the model of high robustness computational optical imaging system

Computational optical imaging is an interdisciplinary subject integrating optics, mathematics, and information technology. It introduces information processing into optical imaging and combines it with intelligent computing, subverting the imaging mechanism of traditional optical imaging which only relies on orderly information transmission. To meet the high-precision requirements of traditional optical imaging for optical processing and adjustment, as well as to solve its problems of being sensitive to gravity and temperature in use, we establish an optical imaging system model from the perspective of computational optical imaging and studies how to design and solve the imaging consistency problem of optical system under the influence of gravity, thermal effect, stress, and other external environment to build a high robustness optical system. The results show that the high robustness interval of the optical system exists and can effectively reduce the sensitivity of the optical system to the disturbance of each link, thus realizing the high robustness of optical imaging.

Observing single cells in whole organs with optical imaging

Cells are the basic unit of human organs that are not fully understood.The revolutionary advancements of optical imaging alowed us to observe single cells in whole organs,revealing the complicated composition of cells with spatial information.Therefore,in this review,we revisit the principles of optical contrast related to those biomolecules and the optical techniques that transform optical contrast into detectable optical signals.Then,we describe optical imaging to achieve threedimensional spatial discrimination for biological tisutes.Due to the milky appearance of tissues,the spatial information burred deep in the whole organ.Fortunately,strategies developed in the last decade could circumvent this issue and lead us into a new era of investigation of the cells with their original spatial information.

Wide-spectrum optical synthetic aperture imaging via spatial intensity interferometry

High resolution imaging is achieved using increasingly larger apertures and successively shorter wavelengths.Optical aperture synthesis is an important high-resolution imaging technology used in astronomy.Conventional long baseline amplitude interferometry is susceptible to uncontrollable phase fluctuations,and the technical difficulty increases rapidly as the wavelength decreases.The intensity interferometry inspired by HBT experiment is essentially insensitive to phase fluctuations,but suffers from a narrow spectral bandwidth which results in a lack of effective photons.In this study,we propose optical synthetic aperture imaging based on spatial intensity interferometry.This not only realizes diffraction-limited optical aperture synthesis in a single shot,but also enables imaging with a wide spectral bandwidth,which greatly improves the optical energy efficiency of intensity interferometry.And this method is insensitive to the optical path difference between the sub-apertures.Simulations and experiments present optical aperture synthesis diffraction-limited imaging through spatial intensity interferometry in a 100 nm spectral width of visible light,whose maximum optical path difference between the sub-apertures reaches 69λ.This technique is expected to provide a solution for optical aperture synthesis over kilometer-long baselines at optical wavelengths.

Optical coherence tomography enhanced depth imaging of chorioretinal folds in patients with orbital tumors

AIM:To characterize spectral-domain optical coherence tomography(SD-OCT)features of chorioretinal folds in orbital mass imaged using enhanced depth imaging(EDI).METHODS:Prospective observational case-control study was conducted in 20 eyes of 20 patients,the uninvolved eye served as a control.All the patients underwent clinical fundus photography,computed tomography,EDI SDOCT imaging before and after surgery.Two patients with cavernous hemangiomas underwent intratumoral injection of bleomycin A5;the remaining patients underwent tumor excision.Patients were followed 1 to 14mo following surgery(average follow up,5.8mo).RESULTS:Visual acuity prior to surgery ranged from 20/20 to 20/200.Following surgery,5 patients’visual acuity remained unchanged while the remaining 15 patients had a mean letter improvement of 10(range 4 to 26 letters).Photoreceptor inner/outer segment defects were found in 10 of 15 patients prior to surgery.Following surgical excision,photoreceptor inner/outer segment defects fully resolved in 8 of these 10 patients.CONCLUSION:Persistence of photoreceptor inner/outer segment defects caused by compression of the globe by an orbital mass can be associated with reduced visual prognosis.Our findings suggest that photoreceptor inner/outer segment defects on EDI SD-OCT could be an indicator for immediate surgical excision of an orbital mass causing choroidal compression.

Imaging assessment of photosensitizer emission induced by radionuclide-derived Cherenkov radiation using charge-coupled device optical imaging and long-pass filters

BACKGROUND Radionuclides produce Cherenkov radiation(CR),which can potentially activate photosensitizers(PSs)in phototherapy.Several groups have studied Cherenkov energy transfer to PSs using optical imaging;however,cost-effectively identifying whether PSs are excited by radionuclide-derived CR and detecting fluorescence emission from excited PSs remain a challenge.Many laboratories face the need for expensive dedicated equipment.AIM To cost-effectively confirm whether PSs are excited by radionuclide-derived CR and distinguish fluorescence emission from excited PSs.METHODS The absorbance and fluorescence spectra of PSs were measured using a microplate reader and fluorescence spectrometer to examine the photo-physical properties of PSs.To mitigate the need for expensive dedicated equipment and achieve the aim of the study,we developed a method that utilizes a chargecoupled device optical imaging system and appropriate long-pass filters of different wavelengths(manual sequential application of long-pass filters of 515,580,645,700,750,and 800 nm).Tetrakis(4-carboxyphenyl)porphyrin(TCPP)was utilized as a model PS.Different doses of copper-64(^(64)CuCl_(2))(4,2,and 1 mCi)were used as CR-producing radionuclides.Imaging and data acquisition were performed 0.5 h after sample preparation.Differential image analysis was conducted by using ImageJ software(National Institutes of Health)to visually evaluate TCPP fluorescence.RESULTS The maximum absorbance of TCPP was at 390-430 nm,and the emission peak was at 670 nm.The CR and CRinduced TCPP emissions were observed using the optical imaging system and the high-transmittance long-pass filters described above.The emission spectra of TCPP with a peak in the 645-700 nm window were obtained by calculation and subtraction based on the serial signal intensity(total flux)difference between^(64)CuCl_(2)+TCPP and^(64)CuCl_(2).Moreover,the differential fluorescence images of TCPP were obtained by subtracting the^(64)CuCl_(2)image from the^(64)CuCl_(2)+TCPP image.The experimental results considering different^(64)CuCl_(2)doses showed a dosedependent trend.These results demonstrate that a bioluminescence imaging device coupled with different longpass filters and subtraction image processing can confirm the emission spectra and differential fluorescence images of CR-induced TCPP.CONCLUSION This simple method identifies the PS fluorescence emission generated by radionuclide-derived CR and can contribute to accelerating the development of Cherenkov energy transfer imaging and the discovery of new PSs.

NIR-II fluorescence imaging in liver tumor surgery: A narrative review

In liver tumor surgery,the recognition of tumor margin and radical resection of microcancer focis have always been the crucial points to reduce postoperative recurrence of tumor.However,naked-eye inspection and palpation have limited effectiveness in identifying tumor boundaries,and traditional imaging techniques cannot consistently locate tumors in real time.As an intraoperative real-time navigation imaging method,NIRfluorescence imaging has been extensively studied for its simplicity,reliable safety,and superior sensitivity,and is expected to improve the accuracy of liver tumor surgery.In recent years,the research focus of NIRfluorescence has gradually shifted from the-rst near-infrared window(NIR-I,700–900 nm)to the second near-infrared window(NIR-II,1000–1700 nm).Fluorescence imaging in NIR-II reduces the scattering effect of deep tissue,providing a preferable detection depth and spatial resolution while signi-cantly eliminating liver autofluorescence background to clarify tumor margin.Developingfluorophores combined with tumor antibodies will further improve the precision offluorescence-guided surgical navigation.With the development of a bunch offluorophores with phototherapy ability,NIR-II can integrate tumor detection and treatment to explore a new therapeutic strategy for liver cancer.Here,we review the recent progress of NIR-IIfluorescence technology in liver tumor surgery and discuss its challenges and potential development direction.

Association of colorectal cancer with pathogenic Escherichia coli: Focus on mechanisms using optical imaging

AIM: To investigate the molecular or cellular mechanisms related to the infection of epithelial colonic mucosa by pks-positive Escherichia coli(E. coli) using optical imaging.METHODS: We choose to evaluate the tumor metabolic activity using a fluorodeoxyglucose analogue as 2-deoxyglucosone fluorescent probes and to correlate it with tumoral volume(mm^3). Inflammation measuring myeloperoxidase(MPO) activity and reactive oxygen species production was monitored by a bioluminescent(BLI) inflammation probe and related to histological examination and MPO levels by enzyme-linked immunosorbent assay(ELISA) on tumor specimens. The detection and quantitation of these two signals were validated on a xenograft model of human colon adenocarcinoma epithelial cells(HCT116) in nude mice infected with a pks-positive E. coli. The inflammatory BLI signal was validated intra-digestively in the colitisCEABAC10 DSS models, which mimicked Crohn's disease. RESULTS: Using a 2-deoxyglucosone fluorescent probe, we observed a high and specific HCT116 tumor uptake in correlation with tumoral volume(P = 0.0036). Using the inflammation probe targeting MPO, we detected a rapid systemic elimination and a significant increase of the BLI signal in the pks-positive E. coli-infected HCT116 xenograft group(P < 0.005). ELISA confirmed that MPO levels were significantly higher(1556 ± 313.6 vs 234.6 ± 121.6 ng/m L P = 0.001) in xenografts infected with the pathogenic E. coli strain. Moreover, histological examination of tumor samples confirmed massive infiltration of pks-positive E. coli-infected HCT116 tumors by inflammatory cells compared to the uninfected group. These data showed that infection with the pathogenic E. coli strain enhanced inflammation and ROS production in tumors before tumor growth. Moreover, we demonstrated that the intra-digestive monitoring of inflammation is feasible in a reference colitis murine model(CEABAC10/DSS).CONCLUSION: Using BLI and fluorescence optical imaging, we provided tools to better understand hostpathogen interactions at the early stage of disease, such as inflammatory bowel disease and colorectal cancer.

PCA-based sea-ice image fusion of optical data by HIS transform and SAR data by wavelet transform

Sea ice as a disaster has recently attracted a great deal of attention in China. Its monitoring has become a routine task for the maritime sector. Remote sensing, which depends mainly on SAR and optical sensors, has become the primary means for sea-ice research. Optical images contain abundant sea-ice multi-spectral in-formation, whereas SAR images contain rich sea-ice texture information. If the characteristic advantages of SAR and optical images could be combined for sea-ice study, the ability of sea-ice monitoring would be im-proved. In this study, in accordance with the characteristics of sea-ice SAR and optical images, the transfor-mation and fusion methods for these images were chosen. Also, a fusion method of optical and SAR images was proposed in order to improve sea-ice identification. Texture information can play an important role in sea-ice classification. Haar wavelet transformation was found to be suitable for the sea-ice SAR images, and the texture information of the sea-ice SAR image from Advanced Synthetic Aperture Radar （ASAR） loaded on ENVISAT was documented. The results of our studies showed that, the optical images in the hue-intensi-ty-saturation （HIS） space could reflect the spectral characteristics of the sea-ice types more efficiently than in the red-green-blue （RGB） space, and the optical image from the China-Brazil Earth Resources Satellite （CBERS-02B） was transferred from the RGB space to the HIS space. The principal component analysis （PCA） method could potentially contain the maximum information of the sea-ice images by fusing the HIS and texture images. The fusion image was obtained by a PCA method, which included the advantages of both the sea-ice SAR image and the optical image. To validate the fusion method, three methods were used to evaluate the fused image, i.e., objective, subjective, and comprehensive evaluations. It was concluded that the fusion method proposed could improve the ability of image interpretation and sea-ice identification.

Mapping the bathymetry of shallow coastal water using singleframe fine-resolution optical remote sensing imagery

This paper presents a bathymetry inversion method using single-frame fine-resolution optical remote sensing imagery based on ocean-wave refraction and shallow-water wave theory. First, the relationship among water depth, wavelength and wave radian frequency in shallow water was deduced based on shallow-water wave theory. Considering the complex wave distribution in the optical remote sensing imagery, Fast Fourier Transform （FFT） and spatial profile measurements were applied for measuring the wavelengths. Then, the wave radian frequency was calculated by analyzing the long-distance fluctuation in the wavelength, which solved a key problem in obtaining the wave radian frequency in a single-frame image. A case study was conducted for Sanya Bay of Hainan Island, China. Single-flame fine-resolution optical remote sensing imagery from QuickBird satellite was used to invert the bathymetry without external input parameters. The result of the digital elevation model （DEM） was evaluated against a sea chart with a scale of 1：25 000. The root-mean-square error of the inverted bathymetry was 1.07 m, and the relative error was 16.2%. Therefore, the proposed method has the advantages including no requirement for true depths and environmental parameters, and is feasible for mapping the bathymetry of shallow coastal water.

Pencil-beam scanning catheter for intracoronary optical coherence tomography

Current gradient-index(GRIN)lens based proximal-driven intracoronary optical coherence tomography(ICOCT)probes consist of a spacer and a GRIN lens with large gradient constant.This design provides great flexibility to control beam profiles,but the spacer length should be well controlled to obtain desired beam profiles and thus it sets an obstacle in mass catheter fabrication.Besides,although GRIN lens with large gradient constant can provide tight focus spot,it has short depth of focus and fast-expanded beam which leads to poor lateral resolution for deep tissue.In this paper,a type of spacer-removed probe is demonstrated with a small gradient constant GRIN lens.This design simplifies the fabrica-tion process and is suitable for mass production.The output beam of the catheter is a narrow nearly collimated light beam,referred to as pencil beam here.The full width at half maximum beam size varies from 35.1μm to 75.3μm in air over 3-mm range.Probe design principles are elaborated with probe/catheter fabrication and performance test.The in vivo imaging of the catheter was verified by a clinical ICOCT system.Those results prove that this novel pencil-beam scanning catheter is potentially a good choice for ICOCT systems.

In Vivo Tumor-Targeted Dual-Modality PET/Optical Imaging with a Yolk/Shell-Structured Silica Nanosystem

Silica nanoparticles have been one of the most promising nanosystems for biomedical applications due to their facile surface chemistry and non-toxic nature. However, it is still challenging to effectively deliver them into tumor sites and noninvasively visualize their in vivo biodistribution with excellent sensitivity and accuracy for effective cancer diagnosis. In this study, we design a yolk/shell-structured silica nanosystem ^(64) Cu-NOTAQD@HMSN-PEG-TRC105, which can be employed for tumor vasculature targeting and dual-modality PET/optical imaging, leading to superior targeting specificity, excellentimaging capability and more reliable diagnostic outcomes.By combining vasculature targeting, pH-sensitive drug delivery, and dual-modality imaging into a single platform,as-designed yolk/shell-structured silica nanosystems may be employed for the future image-guided tumor-targeted drug delivery, to further enable cancer theranostics.

Optical angiography for diabetes-induced pathological changes in microvascular structure and function:An overview

Diabetes mellitus(DM)is a kind of metabolic disorder characterized by chronic hyperglycemia and glucose intolerance due to absolute or relative lack of insulin,leading to chronic damage of vasculature within various organ systems.These detrimental e®ects on the vascular networks will result in the development of various diseases associated with microvascular injury.Modern optical imaging techniques provide essential tools for accurate evaluation of the structural and functional changes of blood vessels down to capillaries level,which can o®er valuable insight on understanding the development of DM-associated complications and design of targeted therapy.This review will brie°y introduce the DM-induced structural and functional alterations of vasculature within di®erent organs such as skin,cerebrum and kidneys,as well as how novel optical imaging techniques facilitate the studies focusing on exploration of these pathological changes of vasculature caused by DM both in-vivo and ex-vivo.