Imaging of human parafoveal area with large field of view in adaptive optics line scanning ophthalmoscope

The parafoveal area,with its high concentration of photoreceptors andfine retinal capillaries,is crucial for central vision and often exhibits early signs of pathological changes.The current adaptive optics scanning laser ophthalmoscope(AOSLO)provides an excellent tool to acquire accurate and detailed information about the parafoveal area with cellular resolution.However,limited by the scanning speed of two-dimensional scanning,thefield of view(FOV)in the AOSLO system was usually less than or equal to 2,and the stitching for the parafoveal area required dozens of images,which was time-consuming and laborious.Unfortunately,almost half of patients are unable to obtain stitched images because of their poorfixation.To solve this problem,we integrate AO technology with the line-scan imaging method to build an adaptive optics line scanning ophthalmoscope(AOLSO)system with a larger FOV.In the AOLSO,afocal spherical mirrors in pairs are nonplanar arranged and the distance and angle between optical elements are optimized to minimize the aberrations,two cylinder lenses are orthogonally placed before the imaging sensor to stretch the point spread function(PSF)for sufficiently digitizing light energy.Captured human retinal images show the whole parafoveal area with 55FOV,60 Hz frame rate and cellular resolutions.Take advantage of the 5FOV of the AOLSO,only 9 frames of the retina are captured with several minutes to stitch a montage image with an FOV of 99,in which photoreceptor counting is performed within approximately 5eccentricity.The AOLSO system not only provides cellular resolution but also has the capability to capture the parafoveal region in a single frame,which offers great potential for noninvasive studying of the parafoveal area.

Application of Morphological Filter in Rosette Scanning Sub-Imaging System

To restore the sub image in a rosette scanning system and provide target recognition system with a low distorted image, the sub image is processed with morphological filters. Morphological filter can process rosette scanning sub images more effectively. It can restore the original area and shape of an object effectively, and keep the energy information of the object. To process sub images got by a rosette scanning system, morphological filter is more effective than traditional low pass filter.

Temporal dynamics of neonatal hypoxic-ischemic encephalopathy injuries on magnetic resonance imaging

Moderate to severe perinatal hypoxic-ischemic encephalopathy occurs in~1 to 3/1000 live births in high-income countries and is associated with a significant risk of death or neurodevelopmental disability.Detailed assessment is important to help identify highrisk infants,to help families,and to support appropriate interventions.A wide range of monitoring tools is available to assess changes over time,including urine and blood biomarkers,neurological examination,and electroencephalography.At present,magnetic resonance imaging is unique as although it is expensive and not suited to monitoring the early evolution of hypoxic-ischemic encephalopathy by a week of life it can provide direct insight into the anatomical changes in the brain after hypoxic-ischemic encephalopathy and so offers strong prognostic information on the long-term outcome after hypoxic-ischemic encephalopathy.This review investigated the temporal dynamics of neonatal hypoxic-ischemic encephalopathy injuries,with a particular emphasis on exploring the correlation between the prognostic implications of magnetic resonance imaging scans in the first week of life and their relationship to long-term outcome prediction,particularly for infants treated with therapeutic hypothermia.A comprehensive literature search,from 2016 to 2024,identified 20 pertinent articles.This review highlights that while the optimal timing of magnetic resonance imaging scans is not clear,overall,it suggests that magnetic resonance imaging within the first week of life provides strong prognostic accuracy.Many challenges limit the timing consistency,particularly the need for intensive care and clinical monitoring.Conversely,although most reports examined the prognostic value of scans taken between 4 and 10 days after birth,there is evidence from small numbers of cases that,at times,brain injury may continue to evolve for weeks after birth.This suggests that in the future it will be important to explore a wider range of times after hypoxic-ischemic encephalopathy to fully understand the optimal timing for predicting long-term outcomes.

PSMFNet:Lightweight Partial Separation and Multiscale Fusion Network for Image Super-Resolution

The employment of deep convolutional neural networks has recently contributed to significant progress in single image super-resolution(SISR)research.However,the high computational demands of most SR techniques hinder their applicability to edge devices,despite their satisfactory reconstruction performance.These methods commonly use standard convolutions,which increase the convolutional operation cost of the model.In this paper,a lightweight Partial Separation and Multiscale Fusion Network(PSMFNet)is proposed to alleviate this problem.Specifically,this paper introduces partial convolution(PConv),which reduces the redundant convolution operations throughout the model by separating some of the features of an image while retaining features useful for image reconstruction.Additionally,it is worth noting that the existing methods have not fully utilized the rich feature information,leading to information loss,which reduces the ability to learn feature representations.Inspired by self-attention,this paper develops a multiscale feature fusion block(MFFB),which can better utilize the non-local features of an image.MFFB can learn long-range dependencies from the spatial dimension and extract features from the channel dimension,thereby obtaining more comprehensive and rich feature information.As the role of the MFFB is to capture rich global features,this paper further introduces an efficient inverted residual block(EIRB)to supplement the local feature extraction ability of PSMFNet.A comprehensive analysis of the experimental results shows that PSMFNet maintains a better performance with fewer parameters than the state-of-the-art models.

Pyramid Separable Channel Attention Network for Single Image Super-Resolution

Single Image Super-Resolution(SISR)technology aims to reconstruct a clear,high-resolution image with more information from an input low-resolution image that is blurry and contains less information.This technology has significant research value and is widely used in fields such as medical imaging,satellite image processing,and security surveillance.Despite significant progress in existing research,challenges remain in reconstructing clear and complex texture details,with issues such as edge blurring and artifacts still present.The visual perception effect still needs further enhancement.Therefore,this study proposes a Pyramid Separable Channel Attention Network(PSCAN)for the SISR task.Thismethod designs a convolutional backbone network composed of Pyramid Separable Channel Attention blocks to effectively extract and fuse multi-scale features.This expands the model’s receptive field,reduces resolution loss,and enhances the model’s ability to reconstruct texture details.Additionally,an innovative artifact loss function is designed to better distinguish between artifacts and real edge details,reducing artifacts in the reconstructed images.We conducted comprehensive ablation and comparative experiments on the Arabidopsis root image dataset and several public datasets.The experimental results show that the proposed PSCAN method achieves the best-known performance in both subjective visual effects and objective evaluation metrics,with improvements of 0.84 in Peak Signal-to-Noise Ratio(PSNR)and 0.017 in Structural Similarity Index(SSIM).This demonstrates that the method can effectively preserve high-frequency texture details,reduce artifacts,and have good generalization performance.

Multi-prior physics-enhanced neural network enables pixel super-resolution and twin-imagefree phase retrieval from single-shot hologram

Digital in-line holographic microscopy(DIHM)is a widely used interference technique for real-time reconstruction of living cells’morphological information with large space-bandwidth product and compact setup.However,the need for a larger pixel size of detector to improve imaging photosensitivity,field-of-view,and signal-to-noise ratio often leads to the loss of sub-pixel information and limited pixel resolution.Additionally,the twin-image appearing in the reconstruction severely degrades the quality of the reconstructed image.The deep learning(DL)approach has emerged as a powerful tool for phase retrieval in DIHM,effectively addressing these challenges.However,most DL-based strategies are datadriven or end-to-end net approaches,suffering from excessive data dependency and limited generalization ability.Herein,a novel multi-prior physics-enhanced neural network with pixel super-resolution(MPPN-PSR)for phase retrieval of DIHM is proposed.It encapsulates the physical model prior,sparsity prior and deep image prior in an untrained deep neural network.The effectiveness and feasibility of MPPN-PSR are demonstrated by comparing it with other traditional and learning-based phase retrieval methods.With the capabilities of pixel super-resolution,twin-image elimination and high-throughput jointly from a single-shot intensity measurement,the proposed DIHM approach is expected to be widely adopted in biomedical workflow and industrial measurement.

Role of wide-field autofluorescence imaging and scanning laser ophthalmoscopy in differentiation of choroidal pigmented lesions

·AIM:Toevaluatethe diagnostic properties of wide-field fundus autofluorescence(FAF) scanning laser ophthalmoscope(SLO) imaging for differentiating choroidal pigmented lesions.·METHODS: A consecutive series of 139 patients were included, 101 had established choroidal melanoma with13 untreated lesions and 98 treated with radiotherapy.Thirty-eight had choroidal nevi. All patients underwent a full ophthalmological examination, undilated wide-field imaging, FAF and standardized US examination. FAF images and imaging characteristics from SLO were correlated with the structural findings in the two patient groups.·RESULTS: Mean FAF intensity of melanomas was significantly lower than the FAF of choroidal nevi. Only 1out of 38 included eyes with nevi touched the optic disc compared to 31 out of 101 eyes with melanomas. In 18 out of 101 melanomas subretinal fluid was seen at the pigmented lesion compared to none seen in eyes with confirmed choroidal nevi. In 'green laser separation', a trend towards more mixed FAF appearance of melanomas compared to nevi was observed. The mean maximal and minimal transverse and longitudinal diameters of melanomas were significantly higher than those of nevi.·CONCLUSION: Wide-field SLO and FAF imaging may be an appropriate non-invasive diagnostic screening tool to differentiate benign from malign pigmented choroidal lesions.

Adaptive optics scanning laser ophthalmoscopy in fundus imaging, a review and update

Adaptive optics scanning laser ophthalmoscopy（AOSLO） has been a promising technique in funds imaging with growing popularity. This review firstly gives a brief history of adaptive optics（AO） and AO-SLO. Then it compares AO-SLO with conventional imaging methods（fundus fluorescein angiography, fundus autofluorescence, indocyanine green angiography and optical coherence tomography） and other AO techniques（adaptive optics flood-illumination ophthalmoscopy and adaptive optics optical coherence tomography）. Furthermore, an update of current research situation in AO-SLO is made based on different fundus structures as photoreceptors（cones and rods）, fundus vessels, retinal pigment epithelium layer, retinal nerve fiber layer, ganglion cell layer and lamina cribrosa. Finally, this review indicates possible research directions of AO-SLO in future.

Non-invasive and low-artifact in vivo brain imaging by using a scanning acoustic-photoacoustic dual mode microscopy

Photoacoustic imaging is a potential candidate for in vivo brain imaging,whereas,its imaging performance could be degraded by inhomogeneous multi-layered media,consisted of scalp and skull.In this work,we propose a low-artifact photoacoustic microscopy(LAPAM)scheme,which combines conventional acoustic-resolution photoacoustic microscopy with scanning acoustic microscopy to suppress the reflection artifacts induced by multi-layers.Based on similar propagation characteristics of photoacoustic signals and ultrasonic echoes,the ultrasonic echoes can be employed as the filters to suppress the reflection artifacts to obtain low-artifact photoacoustic images.Phantom experiment is used to validate the effectiveness of this method.Furthermore,LAPAM is applied for in-vivo imaging mouse brain without removing the scalp and the skull.Experimental results show that the proposed method successfully achieves the low-artifact brain image,which demonstrates the practical applicability of LAPAM.This work might improve the photoacoustic imaging quality in many biomedical applications which involve tissues with complex acoustic properties,such as brain imaging through scalp and skull.

Influence of limited-view scanning on depth imaging of photoacoustic tomography

We study the influence of limited-view scanning on the depth imaging of photoacoustic tomography. The situation, in which absorbers are located at different depths with respect to the limited-view scanning trajectory, is called depth imaging and is investigated in this paper. The results show that limited-view scanning causes the reconstructed intensity of deep absorbers to be weaker than that of shallow ones and that deep absorbers will be invisible if the scanning range is too small. The concept of effective scanning angle is proposed to analyse that phenomenon. We find that an effective scanning angle can well predict the relationship between scanning angle and the intensity ratio of absorbers. In addition, limited-view scanning is employed to improve image quality.

Super-Resolution Imaging of Mammograms Based on the Super-Resolution Convolutional Neural Network

Purpose: To apply and evaluate a super-resolution scheme based on the super-resolution convolutional neural network (SRCNN) for enhancing image resolution in digital mammograms. Materials and Methods: A total of 711 mediolateral oblique (MLO) images including breast lesions were sampled from the Curated Breast Imaging Subset of the Digital Database for Screening Mammography (CBIS-DDSM). We first trained the super-resolution convolutional neural network (SRCNN), which is a deep-learning based super-resolution method. Using this trained SRCNN, high-resolution images were reconstructed from low-resolution images. We compared the image quality of the super-resolution method and that obtained using the linear interpolation methods (nearest neighbor and bilinear interpolations). To investigate the relationship between the image quality of the SRCNN-processed images and the clinical features of the mammographic lesions, we compared the image quality yielded by implementing the SRCNN, in terms of the breast density, the Breast Imaging-Reporting and Data System (BI-RADS) assessment, and the verified pathology information. For quantitative evaluation, peak signal-to-noise ratio (PSNR) and structural similarity (SSIM) were measured to assess the image restoration quality and the perceived image quality. Results: The super-resolution image quality yielded by the SRCNN was significantly higher than that obtained using linear interpolation methods (p p Conclusion: SRCNN can significantly outperform conventional interpolation methods for enhancing image resolution in digital mammography. SRCNN can significantly improve the image quality of magnified mammograms, especially in dense breasts, high-risk BI-RADS assessment groups, and pathology-verified malignant cases.

Real time detection of antibody-antigen interaction using a laser scanning confocal imaging-surface plasmon resonance system

A laser scanning confocal imaging-surface plasmon resonance （LSCI-SPR） instrument integrated with a wavelength-dependent surface plasmon resonance （SPR） sensor and a laser scanning confocal microscopy （LSCM） is built to detect the bonding process of human IgG and fluorescent-labeled affinity purified antibodies in real time. The shifts of resonant wavelength at different reaction time stages are obtained by SPR, corresponding well with the changes of the fluorescence intensity collected by using LSCM. The instrument shows the merits of the combination and complementation of the SPR and LSCM, with such advantages as quantificational analysis, high spatial resolution and real time monitor, which are of great importance for practical applications in biosensor and life science.

Spectroscopic measurements and terahertz imaging of the cornea using a rapid scanning terahertz time domain spectrometer

Spectroscopic measurements and terahertz imaging of the cornea are carried out by using a rapid scanning terahertz time domain spectroscopy（THz-TDS） system.A voice coil motor stage based optical delay line（VCM-ODL） is developed to provide a rather simple and robust structure with both the high scanning speed and the large delay length.The developed system is used for THz spectroscopic measurements and imaging of the corneal tissue with different amounts of water content,and the measurement results show the consistence with the reported results,in which the measurement time using VCM-ODL is a factor of 360 shorter than the traditional motorized optical delay line（MDL）.With reducing the water content a monotonic decrease of the complex permittivity of the cornea is observed.The two-term Debye relaxation model is employed to explain our experimental results,revealing that the fast relaxation time of a dehydrated cornea is much larger than that of a hydrated cornea and its dielectric behavior can be affected by the presence of the biological macromolecules.These results demonstrate that our THz spectrometer may be a promising candidate for tissue hydration sensing and practical application of THz technology.

Polarimetric super-resolution algorithm for radar range imaging via spatial smoothing processing

A full-polarimetric super-resolution algorithm with spatial smoothing processing is presented for one-dimensional（1-D）radar imaging.The coherence between scattering centers is minimized by using spatial smoothing processing（SSP）.Then the range and polarimetric scattering matrix of the scattering centers are estimated.The impact of different lengths of the smoothing window on the imaging quality is mainly analyzed with different signal-to-noise ratios（SNR）.Simulation and experimental results show that an improved radar super-resolution range profile and more precise estimation can be obtained by adjusting the length of the smoothing window under different SNR conditions.

Near-field multiple super-resolution imaging from Mikaelian lens to generalized Maxwell's fish-eye lens

Super-resolution imaging is vital for optical applications, such as high capacity information transmission, real-time bio-molecular imaging, and nanolithography. In recent years, technologies and methods of super-resolution imaging have attracted much attention. Different kinds of novel lenses, from the superlens to the super-oscillatory lens, have been designed and fabricated to break through the diffraction limit. However, the effect of the super-resolution imaging in these lenses is not satisfactory due to intrinsic loss, aberration, large sidebands, and so on. Moreover, these lenses also cannot realize multiple super-resolution imaging. In this research, we introduce the solid immersion mechanism to Mikaelian lens(ML) for multiple super-resolution imaging. The effect is robust and valid for broadband frequencies. Based on conformal transformation optics as a bridge linking the solid immersion ML and generalized Maxwell's fish-eye lens(GMFEL), we also discovered the effect of multiple super-resolution imaging in the solid immersion GMFEL.

Super-resolution imaging in glycoscience: New developments and challenges

Carbohydrates on cell surfaces play a crucial role in a wide variety of biological processes,including cell adhesion,recognition and signaling,viral and bacterial infection,in°ammation and metastasis.However,owing to the large diversity and complexity of carbohydrate structure and nongenetically synthesis,glycoscience is the least understood¯eld compared with genomics and proteomics.Although the structures and functions of carbohydrates have been investigated by various conventional analysis methods,the distribution and role of carbohydrates in cell membranes remain elusive.This review focuses on the developments and challenges of super-resolution imaging in glycoscience through introduction of imaging principle and the available°uorescent probes for super-resolution imaging,the labeling strategies of carbohydrates,and the recent applications of super-resolution imaging in glycoscience,which will promote the super-resolution imaging technology as a promising tool to provide new insights into the study of glycoscience.

Thermoacoustic imaging:From single-element scanning to portable and array-based imaging

The microwave-induced thermoacoustic imaging(TAI)technology has both the advantages of high contrast of microwave imaging and high resolution of ultrasound imaging(UI),so it has carried out exploratory application research in various areas,such as the early detection of breast tumors and cerebrovascular diseases.However,the microwave generator used in the traditional TAI technology is huge and expensive,and the temporal resolution is also too low due to the single-element scanning mechanism.Thus,it is difficult to meet the needs of clinical applications.In this paper,the iterative process and the analysis of related application scenarios from single-element scanning to portable and array-based TAI,such as the miniaturized microwave generator,handheld antenna,multi-channel data acquisition,and UI/TAIdual-modality imaging,are reviewed,and the future trends of this technology are discussed.This review helps researchers in the field of TAI learn the technological development process and future trends.It also deepens clinicians’understanding of TAI so as to put forward more application requirements.

Sub-Rayleigh imaging via undersampling scanning based on sparsity constraints

We demonstrate that, by undersampling scanning object with a reconstruction algorithm related to compressed sensing, an image with the resolution exceeding the finest resolution defined by the numerical aperture of the system can be obtained. Experimental results show that the measurements needed to achieve sub-Rayleigh resolution enhancement can be less than 10% of the pixels of the object. This method offers a general approach applicable to point-by-point illumination super-resolution techniques.

Application of Dual-Source CT TurboFlash Coarse Pitch Scanning in Coronary Artery Imaging

Objective: To compare and analyze the image quality and radiation dose of three scanning modes of dual-source CT coronary artery retrospectively, and to discuss the application value of TurboFlash coarse pitch scanning mode. Methods: The imaging data of 100 patients who underwent CT coronary angiography (CCTA) using Siemens force CT retrospective gated triggering spiral scan (RES-SPIRAL), adaptive prospective gated triggering sequence scan (SEQ) and prospective coarse pitch scan (TurboFlash) retrospectively was collected. The image quality was evaluated by objective and subjective methods. The effective radiation dose of patients was compared and analyzed, and the indications of the three scanning modes were analyzed. The application value of dual-source CT TurboFlash coarse pitch scanning in coronary artery imaging was evaluated. Results: The results showed that the left main coronary artery, the right coronary artery and their tertiary branches could be clearly displayed in the three groups of images: the left anterior descending branch, the left circumflex branch, and their three-level branches. There was no statistical difference in subjective image quality among the three groups of pictures (P > 0.05). There was no statistical difference in objective evaluation indexes, such as CT value, SNR, CNR and Noise among the three groups (P > 0.05). The patient radiation dose results showed that the effective radiation dose ED of RES-SPIRA scan was (9.22 ± 1.33) mSv. The dose of SEQ was (2.88 ± 2.47) mSv, and the dose of TurboFlash was (0.51 ± 0.16) mSv. There was significant difference in comparison of the three groups (P 0.05). RES-spiral scanning had the highest radiation dose and TurboFlash coarse pitch scanning (TurboFlash) had the lowest radiation dose. Conclusion: TurboFlash coarse pitch scanning is low in dosage, fast in speed and wide in adaptability. It is especially suitable for the elderly, children, coma and other patients who cannot cooperate with breath-holding examination, as well as for the screening and examination of coronary artery diseases in asymptomatic population. Undoubtedly, it is a worthy method of heart coronary artery examination.

Optical micro-scanning location calibration of thermal microscope imaging system

A method of micro-scanning location adaptive calibration was proposed, which was real- ized by the digital image micro-displacement estimation. With geometric calculation, this calibration method used the displacement estimation of two thermal microscope images to get the size and direc- tion of each scanning location calibration angle. And each location calibration process was repeated according to the offset given by the system beforehand. The comparison experiments of sequence oversampling reconstruction before and after the micro-scanning location calibration were done. The results showed that the calibration method effectively improved the thermal microscope imaging qual- ity.