Region-Aware Fashion Contrastive Learning for Unified Attribute Recognition and Composed Retrieval

Clothing attribute recognition has become an essential technology,which enables users to automatically identify the characteristics of clothes and search for clothing images with similar attributes.However,existing methods cannot recognize newly added attributes and may fail to capture region-level visual features.To address the aforementioned issues,a region-aware fashion contrastive language-image pre-training(RaF-CLIP)model was proposed.This model aligned cropped and segmented images with category and multiple fine-grained attribute texts,achieving the matching of fashion region and corresponding texts through contrastive learning.Clothing retrieval found suitable clothing based on the user-specified clothing categories and attributes,and to further improve the accuracy of retrieval,an attribute-guided composed network(AGCN)as an additional component on RaF-CLIP was introduced,specifically designed for composed image retrieval.This task aimed to modify the reference image based on textual expressions to retrieve the expected target.By adopting a transformer-based bidirectional attention and gating mechanism,it realized the fusion and selection of image features and attribute text features.Experimental results show that the proposed model achieves a mean precision of 0.6633 for attribute recognition tasks and a recall@10(recall@k is defined as the percentage of correct samples appearing in the top k retrieval results)of 39.18 for composed image retrieval task,satisfying user needs for freely searching for clothing through images and texts.

Detection of broken manhole cover using improved Hough and image contrast

The damage or loss of urban road manhole covers may cause great risk to residents＇ lives and property if they cannot be discovered in time. Most existing research recommendations for solving this problem are difficult to implement. This paper proposes an algorithm that combines the improved Hough transform and image comparison to identify the damage or loss of the manhole covers in complicated surface conditions by using existing urban road video images. Focusing on the pre-processed images, the edge contour tracking algorithm is applied to find all of the edges. Then with the improved Hough transformation, color recognition and image matching algorithm, the manhole cover area is found and the change rates of the manhole cover area are calculated. Based on the threshold of the change rates, it can be determined whether there is potential damage or loss in the manhole cover. Compared with the traditional Hough transform, the proposed method can effectively improve the processing speed and reduce invalid sampling and accumulation. Experimental results indicate that the proposed algorithm has the functions of effective positioning and early warning in the conditions of complex background, different perspectives, and different videoing time and conditions, such as when the target is partially covered.

An improved detail enhancement algorithm based on difference curvature and contrast field

The gradient image is always sensitive to noise in image detail enhancement. To overcome this shortage, an improved detail enhancement algorithm based on difference curvature and contrast field is proposed. Firstly, the difference curvature is utilized to determine the amplification coefficient instead of the gradient. This new amplification function of the difference curvature takes more neighboring points into account, it is therefore not sensitive to noise. Secondly, the contrast field is nonlinearly amplified according to the new amplification coefficient. And then, with the enhanced contrast field, we construct the energy functional. Finally, the enhanced image is reconstructed by the variational method. Experimental results of standard testing image and industrial X-ray image show that the proposed algorithm can perform well on increasing contrast and sharpening edges of images while suppressing noise at the same time.

Recognition of Similar Weather Scenarios in Terminal Area Based on Contrastive Learning

In order to improve the recognition accuracy of similar weather scenarios(SWSs)in terminal area,a recognition model for SWS based on contrastive learning(SWS-CL)is proposed.Firstly,a data augmentation method is designed to improve the number and quality of weather scenarios samples according to the characteristics of convective weather images.Secondly,in the pre-trained recognition model of SWS-CL,a loss function is formulated to minimize the distance between the anchor and positive samples,and maximize the distance between the anchor and the negative samples in the latent space.Finally,the pre-trained SWS-CL model is fine-tuned with labeled samples to improve the recognition accuracy of SWS.The comparative experiments on the weather images of Guangzhou terminal area show that the proposed data augmentation method can effectively improve the quality of weather image dataset,and the proposed SWS-CL model can achieve satisfactory recognition accuracy.It is also verified that the fine-tuned SWS-CL model has obvious advantages in datasets with sparse labels.

Primary clear cell carcinoma in the liver: CT and MRI findings

AIM: To retrospectively analyze the computed tomography (CT) and magnetic resonance imaging (MRI) appearances of primary clear cell carcinoma of the liver (PCCCL) and compare the imaging appearances of PCCCL and common type hepatocellular carcinoma (CHCC) to determine whether any differences exist between the two groups. METHODS: Twenty cases with pathologically proven PCCCL and 127 cases with CHCC in the Second Affiliated Hospital of Sun Yat-sen University were included in this study. CT or MRI images from these patients were retrospectively analyzed. The following imaging findings were reviewed: the presence of liver cirrhosis, tumor size, the enhancement pattern on dynamic contrast scanning, the presence of pseudo capsules, tumor rupture, portal vein thrombosis and lymph node metastasis. RESULTS: Both PCCCL and CHCC were prone to occur in patients with liver cirrhosis, the association rate of liver cirrhosis was 80.0% and 78.7%, respectively (P > 0.05). The mean sizes of PCCCL and CHCC tumors were (7.28 ± 4.25) cm and (6.96 ± 3.98) cm, respectively. Small HCCs were found in 25.0% (5/20) of PCCCL and 19.7% (25/127) of CHCC cases. No significant differences in mean size and ratio of small HCCs were found between the two groups (P = 0.658 and 0.803, respectively). Compared with CHCC patients, PCCCL patients were more prone to form pseudo capsules (49.6% vs 75.0%, P = 0.034). Tumor rupture, typical HCC enhancement patterns and portal vein tumor thrombosis were detected in 15.0% (3/20), 72.2% (13/18) and 20.0% (4/20) of patients with PCCCL and 3.1% (4/127), 83.6% (97/116) and 17.3% (22/127) of patients with CHCC, respectively. There were no significant differences between the two groups (all P > 0.05). No patients with PCCCL and 2.4% (3/127) of patients with CHCC showed signs of lymph node metastasis (P > 0.05). CONCLUSION: The imaging characteristics of PCCCL are similar to those of CHCC and could be useful for differentiating these from other liver tumors (such as hemangioma and hepatic metastases). PCCCLs are more prone than CHCCs to form pseudo capsules.

Derivation of Optimal Global Equalization Function with Variable Size Block Based Local Contrast Enhancement

A conventional global contrast enhancement is difficult to apply in various images because image quality and contrast enhancement are dependent on image characteristics largely. And a local contrast enhancement not only causes a washed-out effect, but also blocks. To solve these drawbacks, this paper derives an optimal global equalization function with variable size block based local contrast enhancement. The optimal equalization function makes it possible to get a good quality image through the global contrast enhancement. The variable size block segmentation is firstly exeoated using intensity differences as a measure of similarity. In the second step, the optimal global equalization function is obtained from the enhanced contrast image having variable size blocks. Conformed experiments have showed that the proposed algorithm produces a visually comfortable result image.

Research on Computer Image Enhancement and Image Scratch Repair

In general there is a digital image with noise, low contrast, blnrred edges and other defects. To effectively enhance the contrast of the image blur to meet the requirements of the subsequent identification and detection. This paper presents a fuzzy adaptive image contrast enhancement algorithm based on gray entropy. This method not only enhances the overall image contrast, but also effectively enrich the target image detail information, and suppress the noise amplification. Meanwhile, the paper proposes an improved K and P parameters image restoration algorithm. The algorithm combines both isotropic and anisotropic diffusion, the use of regional differences in the frequency achieved in the different regions use different iterative equation. Experimental results show that the algorithm with TV model algorithm compared with the same premise of restorative effects, avoiding the staircase effect and better than the TV model repair speed.

A New Method for Human Microcirculation Image Enhancement

Microcirculation images often have uneven illumination and low contrast in the acquisition process, which affect the image reorganization and following process. This paper presents a new method for microcireulatory image illumination correction and contrast enhancement based on the Contourlet transform. Initially, the image illumination model is extracted by Contourlet transform and then uneven illumination is corrected. Next, in order to restrain noise and enhance image contrast, the probability function associated with noise coefficient and edge coefficient is established and applied to all Contourlet coefficients. Then, a nonlinear enhancement function is applied to modified Contourlet coefficient to adaptively enhance image contrast. Finally, the enhanced image is obtained by inverse Contourlet transform. We compare this approach with other contrast enhancement methods, result showing that our method has a better effect than other enhancement methods, which might be helpful for clinical diagnostics of microcirculation.

The application of DCE-MRI in diagnosing breast cancer

Objective The aim of the study was to further explore the diagnostic value of breast dynamic contrast enhancement (DCE), and improve specificity of breast cancer diagnosis.

Review of dynamic contrast-enhanced ultrasound guidance in ablation therapy for hepatocellular carcinoma

Local ablative techniques-percutaneous ethanol injection, microwave coagulation therapy and radiofrequency ablation (RFA)-have been developed to treat unresectable hepatocellular carcinoma (HCC). The success rate of percutaneous ablation therapy for HCC depends on correct targeting of the tumor via an imaging technique. However, probe insertion often is not completely accurate for small HCC nodules, which are poorly def ined on conventional B-mode ultrasound (US) alone. Thus, multiple sessions of ablation therapy are frequently required in diffi cult cases. By means of two breakthroughs in US technology, harmonic imaging and the development of second-generation contrast agents, dynamic contrast-enhanced harmonic US imaging with an intravenous contrast agent can depict tumor vascularity sensitively and accurately, and is able to evaluate small hypervascular HCCs even when B-mode US cannot adequately characterize the tumors. Therefore, dynamic contrast-enhanced US can facilitate RFA electrode placement in hypervascular HCC, which is poorly depicted by B-mode US. The use of dynamic contrast-enhanced US guidance in ablation therapy for liver cancer is an effi cient approach. Here, we present an overview of the current status of dynamic contrast-enhanced US-guided ablation therapy, and summarize the current indications and outcomes of reported clinical use in comparison with that of other modalities.

Bilding Dmage Level Based According to Distance Image Contrast.

Estimation method of building damage level was introduced for the accurate and effective estimation of damage extent and relief goods demand according to long-distance image contrast. In order to obtain completion degree of building edge extracted from long-distance images before and after disaster, the concentration ratio was analyzed with Hough transformation. Based on the maximum posterior probability, estimation method of affected population was designed to accurately estimate victim population, which can be directly reflected by fugitive population. Moreover, on basis of escape route and fugitive population, demand assignment algorithm by backward calculation was designed to improve rescue efficiency.

Scirrhous hepatocellular carcinoma displaying atypical findings on imaging studies

We describe a 15-mm scirrhous hepatocellular carcinoma （HCC） in a 60-year-old man with B-type cirrhosis. Ultrasound disclosed a 15-mm hypoechoic nodule in segment 7. Contrast-enhanced US revealed heterogeneous, not diffuse, hypervascularity in the early phase and a defect in the Kupffer phase.Contrast-enhanced computed tomography （CT） revealed a heterogeneous hypervascular nodule in the early phase and a low-density area in the late phase.Magnetic resonance imaging （MRI） revealed iso- to hypointensity at T1 and high intensity at T2-weighted sequences. Contrast-enhanced MRI also revealed a heterogeneous hypervascular nodule in the early phase and washout in the late phase. Super-paramagnetic iron oxide-MRI revealed a hvoerintense nodule. CT during hepatic arteriography and CT during arterial portography revealed heterogeneous hyperattenuation and a perfusion defect, respectively. Based on these imaging findings the nodule was diagnosed as a mixed well-differentiated and moderately-differentiated HCC.Histologically, the nodule was moderately-differentiated HCC characterized by typical cytological and structural atypia with dense fibrosis. Immunohistochemically,the nodule was positive for heterochromatin protein 1 and alpha-smooth muscle actin, and negative for cytokeratin 19. From the above findings, the nodule was diagnosed as scirrhous HCC. Clinicians engaged in hepatology should exercise caution with suspected scirrhous HCC when imaging studies reveal atypical findings, as shown in our case on the basis of chronic liver disease.

Automatic Optimization of Chirp Setting Parameters in Medical Ultrasound Contrast Imaging

Medical ultrasound contrast imaging is a powerful modality undergoing successive developments in the last decade to date Lately, pulse inversion has been used in both ultrasound tissue harmonic and contrast imaging. However, there was a tradeoff between resolution and penetration. Chirp excitations partially solved the tradeoff, but the chirp setting parameters were not optimized. The present work proposes for the first time combining chirp inversion with ultrasound contrast imaging, with the motivation to improve the contrast, by automatically optimizing the setting parameters of chirp excitation, it is thus an optimal command problem. Linear chirps, 5 μm diameter microbubbles and gradient ascent algorithm were simulated to optimize the chirp setting parameters. Simulations exhibited a gain of 5 dB by automatic optimization of chirp inversion relative to pulse inversion. The automatic optimization process was quite fast. Combining chirp inversion with ultrasound contrast imaging led to a maximum backscattered power permitting high contrast outcomes and optimum parameters.

Local information enhanced LBP

Based on the observation that there exists multiple information in a pixel neighbor,such as distance sum and gray difference sum,local information enhanced LBP(local binary pattern)approach,i.e.LE-LBP,is presented.Geometric information of the pixel neighborhood is used to compute minimum distance sum.Gray variation information is used to compute gray difference sum.Then,both the minimum distance sum and the gray difference sum are used to build a feature space.Feature spectrum of the image is computed on the feature space.Histogram computed from the feature spectrum is used to characterize the image.Compared with LBP,rotation invariant LBP,uniform LBP and LBP with local contrast,it is found that the feature spectrum image from LE-LBP contains more details,however,the feature vector is more discriminative.The retrieval precision of the system using LE-LBP is91.8%when recall is 10%for bus images.

Extracolonic findings of computed tomographic colonography in Koreans

AIM:To determine the frequency and characteristics of extracolonic lesions detected using computed tomographic(CT)colonography.METHODS:The significance of extracolonic lesions was classified as high,intermediate,or low.Medical records were reviewed to establish whether further investigations were carried out pertaining to the extracolonic lesions that were detected by CT colonography.RESULTS:A total of 920 cases from 7 university hospitals were included,and 692 extracolonic findings were found in 532(57.8%)patients.Of 692 extracolonic findings,60 lesions(8.7%)were highly significant,250(36.1%)were of intermediate significance,and 382(55.2%)were of low significance.CT colonography revealed fewer extracolonic findings in subjects who were without symptoms(P<0.001),younger(P<0.001),or who underwent CT colonography with no contrast enhancement(P=0.005).CT colonography with contrast enhancement showed higher cost-effectiveness in detecting highly significant extracolonic lesions in older subjects and in subjects with symptoms.CONCLUSION:Most of the extracolonic findings detected using CT colonography were of less significant lesions.The role of CT colonography would be optimized if this procedure was performed with contrast enhancement in symptomatic older subjects.

Experimental Study on the Dam-Break Hydrographs at the Gate Location

When studying the dam-break flow phenomenon,the basic hydrodynamic features of the dam-break flow at the gate location should be verified primarily.In this study,laboratory experiments were performed in a rectangular and horizontal flume with the same initial water head setting on the dry and wet downstream bed conditions.Water surface elevation was extracted through image analysis and validated by comparing with the data measured using a wave gauge.Temporal variation of the water surface elevation at the gate location,quantified in terms of high-speed video recorded images,can be divided into three stages,the sharp decreasing stage,the relatively steady stage,and the gradually decreasing stage.Applicability of several classic analytical solutions of the dam-break problem at the gate location was validated using present experimental data.Ritter's solution is effective for the dry bed condition while Stoker's solution could be applied to the wet bed case,and both are only applicable during the steady stage.Lin' solution reproduces the gate-site hydrographs well during both the relatively steady and the gradually decreasing stages,especially for the condition under which the down-upstream water depth ratio is smaller than 0.138.

MRI and magnetic resonance angiography in evaluating simultaneous pancreas-kidney transplantation

OBJECTIVE: To evaluate the value of magnetic resonance imaging (MRI) and three dimensional (3D) contrast magnetic resonance angiography (MRA) in the diagnosis of complications of simultaneous pancreas-kidney transplantation (SPKT), as confirmed by biopsy and digital subtraction angiography (DSA). METHODS: Five MR examinations of five patients were performed within 28 days to 2 years after surgery on GE 1.5T MR system. Imaging techniques included axial and sagittal chemical fat-suppressed T1-weighted image (T1WI) and T2-weighted image (T2WI), additional contrast axial or saggital chemical fat-suppressed T1WI were obtained after 3D contrast MRA for calculating the mean percentage of the parenchymal enhancement (MPPE) of the pancreas and kidney. 3D contrast MRA was performed with Smartprep technique. MRA data were analyzed with maximum intensity projection (MIP) and multi-planner reformat (MPR). RESULTS: In five cases of transplant pancreases, MRI found two normal pancreas grafts, one case of acute rejection, one case of chronic rejection with 70% fibrosis and one case of late pancreatitis. In five transplant kidneys, MRI detected four normal kidney grafts and one case of acute rejection with infarction. MPPE could distinguish infarction from other complications. 3D contrast MRA could display vascular complications of SPKT, such as stenosis or occlusion, aneurysm formation of transplanted vessels and narrowing at the site of anastomosis, as confirmed by DSA. CONCLUSION: With combined application of MRI and 3D contrast MRA, complications of SPKT can be clearly identified.

Role of exocrine cells in pancreatic enhancement using Mn-DPDP-enhanced MR imaging

OBJECTIVE: To investigate role of exocrine cells in the pancreatic enhancement images at Manganese (II) N, N'-dipyridoxylethlenediamine-N, N'-diacetate 5, 5'-bisc (Mn-DPDP)-enhanced magnetic resonance (MR) imaging. METHODS: Artificial pancreatic leakage was constructed in six dogs using a fistula tube inserted into the duodenum papillae. Pancreatic juice was collected before and after intravenous infusion of 2 ml/kg of Mn-DPDP at a rate of 2 - 3 ml/min. The Mn content of pancreatic juice was measured by atomic absorption spectroscopy. T(1)-weighted spin-echo images and T(1)-weighted spoiled phase gradient-echo (SPGR) images were obtained prior and approximately 30 min after the administration of Mn-DPDP at 1.5T. RESULTS: The Mn content of pancreatic secretion increased 60.47 +/- 21.83 micro g/dl after the administration of Mn-DPDP (t = 6.785, P

1.3 μm emitting SrF2：Nd^3＋ nanoparticles for high contrast in vivo imaging in the second biological window

Novel approaches for high contrast, deep tissue, in vivo fluorescence biomedical imaging are based on infrared-emitting nanoparticles working in the so-called second biological window （1,000-1,400 nm）. This allows for the acquisition of high resolution, deep tissue images due to the partial transparency of tissues in this particular spectral range. In addition, the optical excitation with low energy （infrared） photons also leads to a drastic reduction in the contribution of autofluorescence to the in vivo image. Nevertheless, as is demonstrated here, working solely in this biological window does not ensure a complete removal of autofluorescence as the specimens diet shows a remarkable infrared fluorescence that extends up to 1,100 nm. In this work, we show how the 1,340 nm emission band of Nd3. ions embedded in SrF2 nanoparticles can be used to produce autofluorescence free, high contrast in vivo fluorescence images. It is also dem- onstrated that the complete removal of the food-related infrared autofluorescence is imperative for the development of reliable biodistribution studies.

Perfect Single Qubit Mirroring Effects on Two and Three Maximally Entangled Qubits

Perfect quantum state mirroring in a chain of N spins is defined as the condition in which the state 丨i 丨of the chain is swapped into the state 丨N - i丨 within a time evolution interval r. Such a phenomenon is an interesting way of transfering entanglement. An expressions for the perfect mirroring of a single qubit contained in a spin chain were proposed in the past. We exploit such an expressions for calculating the evolution times in chains of both two and three spins. In the case of a chain of two qubits, we derive conditions under which the associated four Bell states diagonalize the Hamiltonian. It is found that for the two Bell states 丨Ф＋） and 丨Ф-）, perfect mirroring does not occur （i.e. entanglement is not preserved under swapping）. On the other hand, perfect single qubit mirror effect （entanglement preservation） indeed occurs for the other two Bell states 丨ψ＋） and 丨ψ-） which are mapped into 丨Ф＋） and 丨Ф-） respectively. For the case of a chain of three qubits, the effects of a perfect single qubit mirroring on a set of four maximally entangled three qubit states ψl, ψ2, X1, and X2are studied. Due to the fact that quantum mirroring preserves maximal entanglement, the states ψ1 and ψ2 are not altered. However, quantum mirroring changes the states X1 and X2 only if we apply perfect quantum state mirroring in the site a = 1 of the three qubits spin chain. The above constrains the preservation of maximal entanglement under qubit mirroring of such a state. Due to the fact that swapping has already been experimentally tested, a posible, experimental implementations of single qubit mirroring is possible.