Pre-operative enhanced magnetic resonance imaging combined with clinical features predict early recurrence of hepatocellular carcinoma after radical resection

BACKGROUND Indentifying predictive factors for postoperative recurrence of hepatocellular carcinoma(HCC)has great significance for patient prognosis.AIM To explore the value of gadolinium ethoxybenzyl diethylenetriamine pentaacetic acid(Gd-EOB-DTPA)enhanced magnetic resonance imaging(MRI)combined with clinical features in predicting early recurrence of HCC after resection.METHODS A total of 161 patients with pathologically confirmed HCC were enrolled.The patients were divided into early recurrence and non-early recurrence group based on the follow-up results.The clinical,laboratory,pathological results and Gd-EOB-DTPA enhanced MRI imaging features were analyzed.RESULTS Of 161 patients,73 had early recurrence and 88 were had non-early recurrence.Univariate analysis showed that patient age,gender,serum alpha-fetoprotein level,the Barcelona Clinic Liver Cancer stage,China liver cancer(CNLC)stage,microvascular invasion(MVI),pathological satellite focus,tumor size,tumor number,tumor boundary,tumor capsule,intratumoral necrosis,portal vein tumor thrombus,large vessel invasion,nonperipheral washout,peritumoral enhancement,hepatobiliary phase(HBP)/tumor signal intensity(SI)/peritumoral SI,HBP peritumoral low signal and peritumoral delay enhancement were significantly associated with early recurrence of HCC after operation.Multivariate logistic regression analysis showed that patient age,MVI,CNLC stage,tumor boundary and large vessel invasion were independent predictive factors.External data validation indicated that the area under the curve of the combined predictors was 0.861,suggesting that multivariate logistic regression was a reasonable predictive model for early recurrence of HCC.CONCLUSION Gd-EOB-DTPA enhanced MRI combined with clinical features would help predicting the early recurrence of HCC after operation.

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.

Topic highlight on texture and color enhancement imaging in gastrointestinal diseases

Olympus Corporation developed texture and color enhancement imaging(TXI)as a novel image-enhancing endoscopic technique.This topic highlights a series of hot-topic articles that investigated the efficacy of TXI for gastrointestinal disease identification in the clinical setting.A randomized controlled trial demonstrated improvements in the colorectal adenoma detection rate(ADR)and the mean number of adenomas per procedure(MAP)of TXI compared with those of white-light imaging(WLI)observation(58.7%vs 42.7%,adjusted relative risk 1.35,95%CI:1.17-1.56;1.36 vs 0.89,adjusted incident risk ratio 1.48,95%CI:1.22-1.80,respectively).A cross-over study also showed that the colorectal MAP and ADR in TXI were higher than those in WLI(1.5 vs 1.0,adjusted odds ratio 1.4,95%CI:1.2-1.6;58.2%vs 46.8%,1.5,1.0-2.3,respectively).A randomized controlled trial demonstrated non-inferiority of TXI to narrow-band imaging in the colorectal mean number of adenomas and sessile serrated lesions per procedure(0.29 vs 0.30,difference for non-inferiority-0.01,95%CI:-0.10 to 0.08).A cohort study found that scoring for ulcerative colitis severity using TXI could predict relapse of ulcerative colitis.A cross-sectional study found that TXI improved the gastric cancer detection rate compared to WLI(0.71%vs 0.29%).A cross-sectional study revealed that the sensitivity and accuracy for active Helicobacter pylori gastritis in TXI were higher than those of WLI(69.2%vs 52.5%and 85.3%vs 78.7%,res-pectively).In conclusion,TXI can improve gastrointestinal lesion detection and qualitative diagnosis.Therefore,further studies on the efficacy of TXI in clinical practice are required.

An ART iterative reconstruction algorithm for computed tomography of diffraction enhanced imaging

X-ray diffraction enhanced imaging （DEI） has extremely high sensitivity for weakly absorbing low- Z samples in medical and biological fields. In this paper, we propose an Algebra Reconstruction Technique （ART） iterative reconstruction algorithm for computed tomography of diffraction enhanced imaging （DEI-CT）. An Ordered Subsets （OS） technique is used to accelerate the ART reconstruction. Few-view reconstruction is also studied, and a partial differential equation （PDE） type filter which has the ability of edge-preserving and denoising is used to improve the image quality and eliminate the artifacts. The proposed algorithm is validated with both the numerical simulations and the experiment at the Beijing synchrotron radiation facility （BSRF）.

Medical application of diffraction enhanced imaging in mouse liver blood vessels

Neovascularization is correlative with many processes of diseases, especially for tumor growth, invasion, and metastasis. What is more, these tumor microvessels are totally different from normal vessels in morphology. Therefore, observation of the morphologic distribution of microvessels is one of the key points for many researchers in the field. Using diffraction enhanced imaging （DEI）, we observed the mirocvessles with diameter of about 40 μm in mouse liver. Moreover, the refraction image obtained from DEI shows higher image contrast and exhibits potential use for medical applications.

X-ray diffraction enhanced imaging study of intraocular tumors in human beings

Diffraction enhanced imaging （DEI） with edge enhancement is suitable for the observation of weakly absorbing objects. The potential ability of the DEI was explored for displaying the microanatomy and pathology of human eyeball in this work. The images of surgical specimens from malignant intraocular tumor of hospitalized patients were taken using the hard X-rays from the topography station of Beamline 4W1A at Beijing Synchrotron Radiation Facility （BSRF）. The obtained radiographic images were analyzed in correlation with those of pathology. The results show that the anatomic and pathologic details of intraocular tumors in human beings can be observed clearly by DEI for the first time, with good visualization of the microscopic details of eyeball ring such as sclera, choroids and other details of intraocular organelles. And the best resolution of DEI images reaches up to the magnitude of several tens of μm. The results suggest that it is capable of exhibiting clearly the details of intraocular tumor using DEI method.

Polynomial curve fitting method for refraction-angle extraction in diffraction enhanced imaging

X-ray diffraction sorbing low-Z sample. How enhanced imaging （DEI） is applied to extract phase information from to inspect internal structures of weakly abraw images measured in different positions of rocking curve is the key problem of DEI. In this paper, we present an effective extraction method called polynomial curve fitting method, in order to extract accurate information angular in a fast speed. It is compared with the existing methods such as multiple-images statistical method and Gaussian curve fitting method. The experiments results on a plastic cylinder and a black ant at the Beijing Synchrotron Radiation Facility prove that the polynomial curve fitting method can obtain most approximate refraction-angle values and its computation speed is 10 times faster than the Gaussian curve fitting method.

Optical coherence tomography with or without enhanced depth imaging for peripapillary retinal nerve fiber layer and choroidal thickness

AIM：To assess peripapillary retinal nerve fiber layer（RNFL）and choroidal thickness obtained with enhanced depth imaging（EDI）mode compared with those obtained without EDI mode using Heidelberg Spectralis optical coherence tomography（OCT）.METHODS：Fifty eyes of 25 normal healthy subjects and32 eyes of 20 patients with different eye diseases were included in the study.All subjects underwent 3.4 mm diameter peripapillary circular OCT scan centered on the optic disc using both the conventional and the EDI OCT protocols.The visualization of RNFL and choroidoscleral junction was assessed using an ordinal scoring scale.The paired t-test,intraclass correlation coefficient（ICC）,95%limits of agreement（LoA）,and Bland and Altman plots were used to test the agreement of measurements.RESULTS：The visibility score of RNFL obtained with and without EDI was of no significant difference（P=0.532）,the visualization of choroidoscleral junction was better using EDI protocol than conventional protocol（P〈0.001）.Peripapillary RNFL thickness obtained with EDI was slightly thicker than that obtained without EDI（103.25±9.42μm vs 101.87±8.78μm,P=0.010）.The ICC of the two protocols was excellent with the value of 0.867 to 0.924,the 95%LoA of global RNFL thickness was between-10.0 to 7.4μm.Peripapillary choroidal thickness obtained with EDI was slightly thinner than that obtained without EDI（147.23±51.04μm vs 150.90±51.84μm,P〈0.001）.The ICC was also excellent with the value of 0.960 to 0.987,the 95%LoA of global choroidal thickness was between-12.5 to 19.8μm.CONCLUSION：Peripapillary circular OCT scan with or without EDI mode shows comparable results in the measurement of peripapillary RNFL and choroidal thickness.

Improved visibility of colorectal tumor by texture and color enhancement imaging with indigo carmine

BACKGROUND Accurate diagnosis and early resection of colorectal polyps are important to prevent the occurrence of colorectal cancer.However,technical factors and morphological factors of polyps itself can lead to missed diagnoses.Imageenhanced endoscopy and chromoendoscopy(CE)have been developed to facilitate an accurate diagnosis.There have been no reports on visibility using a combination of texture and color enhancement imaging(TXI)and CE for colorectal tumors.AIM To investigate the visibility of margins and surfaces with the combination of TXI and CE for colorectal lesions.METHODS This retrospective study included patients who underwent lower gastrointestinal endoscopy at the Toyoshima Endoscopy Clinic.We extracted polyps that were resected and diagnosed as adenomas or serrated polyps(hyperplastic polyps and sessile serrated lesions)from our endoscopic database.An expert endoscopist performed the lower gastrointestinal endoscopies and observed the lesion using white light imaging(WLI),TXI,CE,and TXI+CE modalities.Indigo carmine dye was used for CE.Three expert endoscopists rated the visibility of the margin and surface patterns in four ranks,from 1 to 4.The primary outcomes were the average visibility scores for the margin and surface patterns based on the WLI,TXI,CE,and TXI+CE observations.Visibility scores between the four modalities were compared by the Kruskal-Wallis and Dunn tests.RESULTS A total of 48 patients with 81 polyps were assessed.The histological subtypes included 50 tubular adenomas,16 hyperplastic polyps,and 15 sessile serrated lesions.The visibility scores for the margins based on WLI,TXI,CE,and TXI+CE were 2.44±0.93,2.90±0.93,3.37±0.74,and 3.75±0.49,respectively.The visibility scores for the surface based on WLI,TXI,CE,and TXI+CE were 2.25±0.80,2.84±0.84,3.12±0.72,and 3.51±0.60,respectively.The visibility scores for the detection and surface on TXI were significantly lower than that on CE but higher than that on WLI(P<0.001).The visibility scores for the margin and surface on TXI+CE were significantly higher than those on CE(P<0.001).In the sub-analysis of adenomas,the visibility for the margin and surface on TXI+CE was significantly better than that on WLI,TXI,and CE(P<0.001).In the sub-analysis of serrated polyps,the visibility for the margin and surface on TXI+CE was also significantly better than that on WLI,TXI,and CE(P<0.001).CONCLUSION TXI+CE enhanced the visibility of the margin and surface compared to WLI,TXI,and CE for colorectal lesions.

Mucosal patterns change after Helicobacter pylori eradication:Evaluation using blue laser imaging in patients with atrophic gastritis

BACKGROUND Mucosal patterns(MPs)observed on blue laser imaging in patients with atrophic gastritis can be classified as spotty,cracked,and mottled.Furthermore,we hypothesized that the spotty pattern may change to the cracked pattern after Helicobacter pylori(H.pylori)eradication.AIM To further substantiate and comprehensively investigate MP changes after H.pylori eradication in a larger number of patients.METHODS We included 768 patients who were diagnosed with atrophic gastritis with evaluable MP using upper gastrointestinal endoscopy at the Nishikawa Gastrointestinal Clinic,Japan.Among them,325 patients were H.pylori-positive,and of them,101 patients who underwent upper gastrointestinal endoscopy before and after H.pylori eradication were evaluated for post-eradication MP changes.The patients’MPs were interpreted by three experienced endoscopists who were blinded to their clinical features.RESULTS Among 76 patients with the spotty pattern before or after H.pylori eradication,the pattern disappeared or decreased in 67 patients[88.2%,95%confidence interval(CI):79.0%-93.6%),appeared or increased in 8 patients(10.5%,95%CI:5.4%-19.4%),and showed no change in 1 patient(1.3%,95%CI:0.2%-7.1%).In 90 patients with the cracked pattern before or after H.pylori eradication,the pattern disappeared or decreased in 7 patients(7.8%,95%CI:3.8%-15.2%),appeared or increased in 79 patients(87.8%,95%CI:79.4%-93.0%),and showed no change in 4 patients(4.4%,95%CI:1.7%-10.9%).In 70 patients with the mottled pattern before or after H.pylori eradication,the pattern disappeared or decreased in 28 patients(40.0%,95%CI:29.3%-51.7%),appeared or increased in 35 patients(50.0%,95%CI:38.6%-61.4%),and showed no change in 7 patients(10.0%,95%CI:4.9%-19.2%).CONCLUSION After H.pylori eradication,MPs changed from spotty to cracked in most patients,which may help endoscopists easily and precisely evaluate H.pylori-related gastritis status.

Standardization of choroidal thickness measurements using enhanced depth imaging optical coherence tomography

AIM: To describe and evaluate a standardized protocol for measuring the choroidal thickness(Ch T) using enhanced depth imaging optical coherence tomography(EDI OCT).METHODS: Single 9 mm EDI OCT line scans across the fovea were used for this study. The protocol used in this study classified the EDI OCT images into four groups based on the appearance of the choroidal-scleral interface and suprachoroidal space. Two evaluation iterations of experiments were performed: first, the protocol was validated in a pilot study of 12 healthy eyes. Afterwards, the applicability of the protocol was tested in 82 eyes of patients with diabetes. Inter-observer and intra-observer agreements on image classifications were performed using Cohen’s kappa coefficient(κ). Intraclass correlation coefficient(ICC) and Bland-Altman’s methodology were used for the measurement of the Ch T.RESULTS: There was a moderate(κ=0.42) and perfect(κ =1) inter- and intra-observer agreements on image classifications from healthy eyes images and substantial(κ =0.66) and almost perfect(κ =0.86) agreements from diabetic eyes images. The proposed protocol showed excellent inter- and intra-observer agreements for the Ch T measurements on both, healthy eyes and diabetic eyes(ICC 】0.90 in all image categories). The Bland-Altman plot showed a relatively large Ch T measurement agreement in the scans that contained less visible choroidal outer boundary. CONCLUSION: A protocol to standardize Ch T measurements in EDI OCT images has been developed;the results obtained using this protocol show that the technique is accurate and reliable for routine clinical practice and research.

Peripapillary choroidal thickness in Chinese children using enhanced depth imaging optical coherence tomography

AIM：To evaluate the peripapillary choroidal thickness（PPCT） in Chinese children,and to analyze the influencing factors.METHODS： PPCT was measured with enhanced depth imaging optical coherence tomography（EDI-OCT） in 70children（53 myopes and 17 non-myopes） aged 7 to 18 y,with spherical equivalent refractive errors between 0.50and-5.87 diopters（D）.Peripapillary choroidal imaging was performed using circular scans of a diameter of 3.4 mm around the optic disc.PPCT was measured by EDI-OCT in six sectors： nasal（N）,superonasal（SN）,superotemporal（ST）,temporal（T）,inferotemporal（IT）and inferonasal（IN）,as well as global RNFL thickness（G）.RESULTS： The mean global PPCT was 165.49±33.76 μm.The temporal,inferonasal,inferotemporal PPCT were significantly thinner than the nasal,superonasal,superotemporal segments PPCT were significantly thinner in the myopic group at temporal,superotemporal and inferotemporal segments.The axial length was significantly associated with the average global（β=-0.419,P =0.014）,superonasal（β=-2.009,P=0.049） and inferonasal（β=-2.000,P=0.049） PPCT.The other factors（gender,age,SE） were not significantly associated with PPCT.CONCLUSION： PPCT was thinner in the myopic group at temporal,superotemporal and inferotemporal segments.The axial length was found to be negatively correlated to PPCT.We need more further studies about the relationship between PPCT and myopia.

Role of pulmonary perfusion magnetic resonance imaging for the diagnosis of pulmonary hypertension:A review

Among five types of pulmonary hypertension,chronic thromboembolic pulmonary hypertension(CTEPH)is the only curable form,but prompt and accurate diagnosis can be challenging.Computed tomography and nuclear medicine-based techniques are standard imaging modalities to non-invasively diagnose CTEPH,however these are limited by radiation exposure,subjective qualitative bias,and lack of cardiac functional assessment.This review aims to assess the methodology,diagnostic accuracy of pulmonary perfusion imaging in the current literature and discuss its advantages,limitations and future research scope.

Hyperspectral image super resolution using deep internal and self-supervised learning

By automatically learning the priors embedded in images with powerful modelling ca-pabilities,deep learning-based algorithms have recently made considerable progress in reconstructing the high-resolution hyperspectral(HR-HS)image.With previously collected large-amount of external data,these methods are intuitively realised under the full supervision of the ground-truth data.Thus,the database construction in merging the low-resolution(LR)HS(LR-HS)and HR multispectral(MS)or RGB image research paradigm,commonly named as HSI SR,requires collecting corresponding training triplets:HR-MS(RGB),LR-HS and HR-HS image simultaneously,and often faces dif-ficulties in reality.The learned models with the training datasets collected simultaneously under controlled conditions may significantly degrade the HSI super-resolved perfor-mance to the real images captured under diverse environments.To handle the above-mentioned limitations,the authors propose to leverage the deep internal and self-supervised learning to solve the HSI SR problem.The authors advocate that it is possible to train a specific CNN model at test time,called as deep internal learning(DIL),by on-line preparing the training triplet samples from the observed LR-HS/HR-MS(or RGB)images and the down-sampled LR-HS version.However,the number of the training triplets extracted solely from the transformed data of the observation itself is extremely few particularly for the HSI SR tasks with large spatial upscale factors,which would result in limited reconstruction performance.To solve this problem,the authors further exploit deep self-supervised learning(DSL)by considering the observations as the unlabelled training samples.Specifically,the degradation modules inside the network were elaborated to realise the spatial and spectral down-sampling procedures for transforming the generated HR-HS estimation to the high-resolution RGB/LR-HS approximation,and then the reconstruction errors of the observations were formulated for measuring the network modelling performance.By consolidating the DIL and DSL into a unified deep framework,the authors construct a more robust HSI SR method without any prior training and have great potential of flexible adaptation to different settings per obser-vation.To verify the effectiveness of the proposed approach,extensive experiments have been conducted on two benchmark HS datasets,including the CAVE and Harvard datasets,and demonstrate the great performance gain of the proposed method over the state-of-the-art methods.

Detecting early changes in choroidal vascularity and thickness using optical coherence tomography in patients with corneal crosslinking for keratoconus

AIM:To investigate changes in choroidal thickness and vascularity in keratoconus patients treated with corneal crosslinking.METHODS:This study evaluated 28 eyes of 22 patients with keratoconus who underwent corneal crosslinking.The choroidal thicknesses were evaluated on enhanced depth imaging optical coherence tomography at the preoperative and postoperative 3d,1,and 3mo.Choroidal thickness in the four cardinal quadrants and the fovea were evaluated.The choroidal vascularity index was also calculated.RESULTS:There was no significant difference in central choroidal thickness between the preoperative and postoperative 3d,1mo(P>0.05).There was a significant increase in the 3mo(P=0.034)and a significant decrease in the horizontal choroidal vascularity index on the postoperative 3d(P=0.014),there was no statistically significant change in vertical axes and other visits in horizontal sections(P>0.05).CONCLUSION:This study sheds light on choroidal changes in postoperative corneal crosslinking for keratoconus.While it suggests the procedure’s relative safety for submacular choroid,more extensive research is necessary to confirm these findings and their clinical significance.

Image enhancement with intensity transformation on embedding space

In recent times,an image enhancement approach,which learns the global transformation function using deep neural networks,has gained attention.However,many existing methods based on this approach have a limitation:their transformation functions are too simple to imitate complex colour transformations between low-quality images and manually retouched high-quality images.In order to address this limitation,a simple yet effective approach for image enhancement is proposed.The proposed algorithm based on the channel-wise intensity transformation is designed.However,this transformation is applied to the learnt embedding space instead of specific colour spaces and then return enhanced features to colours.To this end,the authors define the continuous intensity transformation(CIT)to describe the mapping between input and output intensities on the embedding space.Then,the enhancement network is developed,which produces multi-scale feature maps from input images,derives the set of transformation functions,and performs the CIT to obtain enhanced images.Extensive experiments on the MIT-Adobe 5K dataset demonstrate that the authors’approach improves the performance of conventional intensity transforms on colour space metrics.Specifically,the authors achieved a 3.8%improvement in peak signal-to-noise ratio,a 1.8%improvement in structual similarity index measure,and a 27.5%improvement in learned perceptual image patch similarity.Also,the authors’algorithm outperforms state-of-the-art alternatives on three image enhancement datasets:MIT-Adobe 5K,Low-Light,and Google HDRþ.

A Novel Multi-Stream Fusion Network for Underwater Image Enhancement

Due to the selective absorption of light and the existence of a large number of floating media in sea water, underwater images often suffer from color casts and detail blurs. It is therefore necessary to perform color correction and detail restoration. However,the existing enhancement algorithms cannot achieve the desired results. In order to solve the above problems, this paper proposes a multi-stream feature fusion network. First, an underwater image is preprocessed to obtain potential information from the illumination stream, color stream and structure stream by histogram equalization with contrast limitation, gamma correction and white balance, respectively. Next, these three streams and the original raw stream are sent to the residual blocks to extract the features. The features will be subsequently fused. It can enhance feature representation in underwater images. In the meantime, a composite loss function including three terms is used to ensure the quality of the enhanced image from the three aspects of color balance, structure preservation and image smoothness. Therefore, the enhanced image is more in line with human visual perception.Finally, the effectiveness of the proposed method is verified by comparison experiments with many stateof-the-art underwater image enhancement algorithms. Experimental results show that the proposed method provides superior results over them in terms of MSE,PSNR, SSIM, UIQM and UCIQE, and the enhanced images are more similar to their ground truth images.

Unsupervised Multi-Expert Learning Model for Underwater Image Enhancement

Underwater image enhancement aims to restore a clean appearance and thus improves the quality of underwater degraded images.Current methods feed the whole image directly into the model for enhancement.However,they ignored that the R,G and B channels of underwater degraded images present varied degrees of degradation,due to the selective absorption for the light.To address this issue,we propose an unsupervised multi-expert learning model by considering the enhancement of each color channel.Specifically,an unsupervised architecture based on generative adversarial network is employed to alleviate the need for paired underwater images.Based on this,we design a generator,including a multi-expert encoder,a feature fusion module and a feature fusion-guided decoder,to generate the clear underwater image.Accordingly,a multi-expert discriminator is proposed to verify the authenticity of the R,G and B channels,respectively.In addition,content perceptual loss and edge loss are introduced into the loss function to further improve the content and details of the enhanced images.Extensive experiments on public datasets demonstrate that our method achieves more pleasing results in vision quality.Various metrics(PSNR,SSIM,UIQM and UCIQE) evaluated on our enhanced images have been improved obviously.

More Than Lightening:A Self-Supervised Low-Light Image Enhancement Method Capable for Multiple Degradations

Low-light images suffer from low quality due to poor lighting conditions,noise pollution,and improper settings of cameras.To enhance low-light images,most existing methods rely on normal-light images for guidance but the collection of suitable normal-light images is difficult.In contrast,a self-supervised method breaks free from the reliance on normal-light data,resulting in more convenience and better generalization.Existing self-supervised methods primarily focus on illumination adjustment and design pixel-based adjustment methods,resulting in remnants of other degradations,uneven brightness and artifacts.In response,this paper proposes a self-supervised enhancement method,termed as SLIE.It can handle multiple degradations including illumination attenuation,noise pollution,and color shift,all in a self-supervised manner.Illumination attenuation is estimated based on physical principles and local neighborhood information.The removal and correction of noise and color shift removal are solely realized with noisy images and images with color shifts.Finally,the comprehensive and fully self-supervised approach can achieve better adaptability and generalization.It is applicable to various low light conditions,and can reproduce the original color of scenes in natural light.Extensive experiments conducted on four public datasets demonstrate the superiority of SLIE to thirteen state-of-the-art methods.Our code is available at https://github.com/hanna-xu/SLIE.

Improving the Transmission Security of Vein Images Using a Bezier Curve and Long Short-Term Memory

The act of transmitting photos via the Internet has become a routine and significant activity.Enhancing the security measures to safeguard these images from counterfeiting and modifications is a critical domain that can still be further enhanced.This study presents a system that employs a range of approaches and algorithms to ensure the security of transmitted venous images.The main goal of this work is to create a very effective system for compressing individual biometrics in order to improve the overall accuracy and security of digital photographs by means of image compression.This paper introduces a content-based image authentication mechanism that is suitable for usage across an untrusted network and resistant to data loss during transmission.By employing scale attributes and a key-dependent parametric Long Short-Term Memory(LSTM),it is feasible to improve the resilience of digital signatures against image deterioration and strengthen their security against malicious actions.Furthermore,the successful implementation of transmitting biometric data in a compressed format over a wireless network has been accomplished.For applications involving the transmission and sharing of images across a network.The suggested technique utilizes the scalability of a structural digital signature to attain a satisfactory equilibrium between security and picture transfer.An effective adaptive compression strategy was created to lengthen the overall lifetime of the network by sharing the processing of responsibilities.This scheme ensures a large reduction in computational and energy requirements while minimizing image quality loss.This approach employs multi-scale characteristics to improve the resistance of signatures against image deterioration.The proposed system attained a Gaussian noise value of 98%and a rotation accuracy surpassing 99%.