Identifying STRN3-RARA as a new fusion gene for acute promyelocytic leukemia.

Here we report a new fusion gene, STRN3-RARA, in acute promyelocytic leukemia (APL). It cooperates with UTX deficiency to drive full-blown APL in mice. Although STRN3-RARA leukemia quickly relapses after all-trans retinoic acid treatment, it can be restrained by cepharanthine.

Myelomonocytic and monocytic acute myeloid leukemia demonstrate comparable poor outcomes with venetoclax-based treatment: a monocentric real-world study.

Venetoclax (VEN), a BCL-2 inhibitor, has transformed treatment strategies for elderly and unfit acute myeloid leukemia (AML) patients by significantly improving response rates and survival. However, the predictive factors for VEN efficacy differ from traditional chemotherapy. The clinical relevance of the FAB (French-American-British) monocytic subtype, including M4 and M5, has been debated as a marker for VEN resistance. This real-world study examined 162 newly diagnosed (ND) and 85 relapsed/refractory (R/R) AML patients who received VEN-based therapy at West China Hospital, Sichuan University, from January 2019 to January 2023. We retrospectively collected clinical and treatment data from electronic medical records. The median age of the cohort was 55.5 years (range: 16.5-83.5). The composite complete remission (cCR) rate in the entire cohort was 60.7%. Specifically, among newly diagnosed (ND) patients, FAB monocytic subtypes exhibited lower cCR compared to non-monocytic subtypes (55.1% vs. 76.3%, P = 0.007). Additionally, there were no significant differences observed between M4 and M5 subtypes, both in the ND group (61.7% vs. 40.9%, p = 0.17) and the R/R group (38.2% vs. 40%, p > 0.9). Furthermore, the median follow-up was 238 (range: 7-1120) days. ND patients with monocytic subtypes had shorter overall survival compared to non-monocytic subtypes (295 days vs. not reached, p = 0.0017). Conversely, R/R patients showed no such difference (204 vs. 266 days, p = 0.72). In summary, our study suggests that the FAB monocytic subtype can predict VEN resistance and shorter survival in ND AML patients. Moreover, there is no significant distinction between M4 and M5 subtypes.

Exposure to endocrine disruptor DEHP promotes the progression and radiotherapy resistance of pancreatic cancer cells by increasing BMI1 expression and properties of cancer stem cells.

Most patients diagnosed with pancreatic cancer are initially at an advanced stage, and radiotherapy resistance impact the effectiveness of treatment. This study aims to investigate the effects of endocrine disruptor Di-(2-ethylhexyl) phthalate (DEHP) on various biological behaviors and the radiotherapy sensitivity of pancreatic cancer cells, as well as its potential mechanisms. Our findings indicate that exposure to DEHP promotes the proliferation of various cancer cells, including those from the lung, breast, pancreas, and liver, in a time- and concentration-dependent manner. Furthermore, DEHP exposure could influence several biological behaviors of pancreatic cancer cells in vivo and vitro. These effects include reducing cell apoptosis, causing G0/G1 phase arrest, increasing migration capacity, enhancing tumorigenicity, elevating the proportion of cancer stem cells (CSCs), and upregulating expression levels of CSCs markers such as CD133 and BMI1. DEHP exposure can also increase radiation resistance, which can be reversed by downregulating BMI1 expression. In summary our research suggests that DEHP exposure can lead to pancreatic cancer progression and radiotherapy resistance, and the mechanism may be related to the upregulation of BMI1 expression, which leads to the increase of CSCs properties.

A Multi-Stage Progressive Pansharpening Network Based on Detail Injection with Redundancy Reduction.

In the field of remote sensing image processing, pansharpening technology stands as a critical advancement. This technology aims to enhance multispectral images that possess low resolution by integrating them with high-spatial-resolution panchromatic images, ultimately producing multispectral images with high resolution that are abundant in both spatial and spectral details. Thus, there remains potential for improving the quality of both the spectral and spatial domains of the fused images based on deep-learning-based pansharpening methods. This work proposes a new method for the task of pansharpening: the Multi-Stage Progressive Pansharpening Network with Detail Injection with Redundancy Reduction Mechanism (MSPPN-DIRRM). This network is divided into three levels, each of which is optimized for the extraction of spectral and spatial data at different scales. Particular spectral feature and spatial detail extraction modules are used at each stage. Moreover, a new image reconstruction module named the DRRM is introduced in this work; it eliminates both spatial and channel redundancy and improves the fusion quality. The effectiveness of the proposed model is further supported by experimental results using both simulated data and real data from the QuickBird, GaoFen1, and WorldView2 satellites; these results show that the proposed model outperforms deep-learning-based methods in both visual and quantitative assessments. Among various evaluation metrics, performance improves by 0.92-18.7% compared to the latest methods.

Robust Optimization Research of Cyber-Physical Power System Considering Wind Power Uncertainty and Coupled Relationship.

To mitigate the impact of wind power uncertainty and power-communication coupling on the robustness of a new power system, a bi-level mixed-integer robust optimization strategy is proposed. Firstly, a coupled network model is constructed based on complex network theory, taking into account the coupled relationship of energy supply and control dependencies between the power and communication networks. Next, a bi-level mixed-integer robust optimization model is developed to improve power system resilience, incorporating constraints related to the coupling strength, electrical characteristics, and traffic characteristics of the information network. The upper-level model seeks to minimize load shedding by optimizing DC power flow using fuzzy chance constraints, thereby reducing the risk of power imbalances caused by random fluctuations in wind power generation. Furthermore, the deterministic power balance constraints are relaxed into inequality constraints that account for wind power forecasting errors through fuzzy variables. The lower-level model focuses on minimizing traffic load shedding by establishing a topology-function-constrained information network traffic model based on the maximum flow principle in graph theory, thereby improving the efficiency of network flow transmission. Finally, a modified IEEE 39-bus test system with intermittent wind power is used as a case study. Random attack simulations demonstrate that, under the highest link failure rate and wind power penetration, Model 2 outperforms Model 1 by reducing the load loss ratio by 23.6% and improving the node survival ratio by 5.3%.

Identification of Critical Links Based on Electrical Betweenness and Neighborhood Similarity in Cyber-Physical Power Systems.

Identifying critical links is of great importance for ensuring the safety of the cyber-physical power system. Traditional electrical betweenness only considers power flow distribution on the link itself, while ignoring the local influence of neighborhood links and the coupled reaction of information flow on energy flow. An identification method based on electrical betweenness centrality and neighborhood similarity is proposed to consider the internal power flow dynamic influence existing in multi-neighborhood nodes and the topological structure interdependence between power nodes and communication nodes. Firstly, for the power network, the electrical topological overlap is proposed to quantify the vulnerability of the links. This approach comprehensively considers the local contribution of neighborhood nodes, power transmission characteristics, generator capacity, and load. Secondly, in communication networks, effective distance closeness centrality is defined to evaluate the importance of communication links, simultaneously taking into account factors such as the information equipment function and spatial relationships. Next, under the influence of coupled factors, a comprehensive model is constructed based on the dependency relationships between information flow and energy flow to more accurately assess the critical links in the power network. Finally, the simulation results show the effectiveness of the proposed method under dynamic and static attacks.

Allogeneic cord blood regulatory T cells can resolve lung inflammation.

BACKGROUND AIMS: CD4+CD25+CD127lo regulatory T cells (Tregs) are responsible for maintaining immune homeostasis. Tregs can be rendered defective and deficient as a result of the immune imbalance seen in lung injury, and such dysfunction can play a major role in continued tissue inflammation. The authors hypothesized that adoptive therapy with healthy allogeneic umbilical cord blood (UCB)-derived Tregs may be able to resolve inflammation. RESULTS: Ex vivo-expanded UCB Tregs exhibited a unique phenotype with co-expression of CD45RA+CD45RO+ >80% and lung homing markers, including CD49d. UCB Tregs did not turn pathogenic when exposed to IL-6. Co-culture with increasing doses of dexamethasone led to a synergistic increase in UCB Treg-induced apoptosis of conventional T cells (Tcons), which translated into significantly higher suppression of proliferating Tcons, especially at a lower Treg:Tcon ratio. Multiple injections of UCB Tregs led to their preferential accumulation in lung tissue in an immune injury xenogenic model. A significant decrease in lung resident cytotoxic CD8+ T cells (P = 0.0218) correlated with a sustained decrease in their systemic distribution compared with controls (P < 0.0001) (n = 7 per arm) as well as a decrease in circulating human soluble CD40 ligand level (P = 0.031). Tissue architecture was preserved in the treatment arm, and a significant decrease in CD3+ and CD8+ burden was evident in immunohistochemistry analysis. CONCLUSIONS: UCB Treg adoptive therapy is a promising therapeutic strategy for treatment of lung injury.

Prognostic value of IDH2R140 and IDH2R172 mutations in patients with acute myeloid leukemia: a systematic review and meta-analysis.

BACKGROUND: Whether isocitrate dehydrogenase 2 (IDH2) R140 and R172 gene mutations affect the prognosis of patients with acute myeloid leukemia (AML) is controversial. Here, we performed a meta-analysis to assess their prognostic value. METHODS: Eligible studies were systematically searched from PubMed, Embase, the Cochrane Library and Chinese databases up to June 1, 2022. We extracted the hazard ratios (HRs) and their 95% confidence intervals (CIs) of overall survival (OS) and progression-free survival (PFS) to carry out a meta-analysis by a fixed effect model or random effect model according to the heterogeneity between studies. RESULTS: A total of 12725 AML patients from 11 studies were included in this meta-analysis, of which 1111 (8.7%) and 305 (2.4%) had IDH2R140 and IDH2R172 mutations, respectively. The results revealed that both IDH2R140 and IDH2R172 mutations had no significant effect on OS (IDH2R140: HR = 0.92, 95% CI: 0.77-1.10, P = 0.365; IDH2R172: HR = 0.91, 95% CI: 0.65-1.28, P = 0.590) or PFS (IDH2R140: HR = 1.02, 95% CI: 0.75-1.40, P = 0.881; IDH2R172: HR = 1.31, 95% CI: 0.78-2.22, P = 0.306) in AML patients. Subgroup analysis of AML patients with IDH2R140 mutation revealed that studies from the USA (HR = 0.60, 95% CI: 0.41-0.89, P = 0.010) and ≤ 50 years old (HR = 0.63, 95% CI: 0.50-0.80, P = 0.000) had longer OS. However, studies from Sweden (HR = 1.94, 95% CI: 1.07-3.53, P = 0.030) had shorter OS. Meanwhile, subgroup analysis of AML patients with IDH2R172 mutation showed that studies from Germany/Austria (HR = 0.76, 95% CI: 0.61-0.94, P = 0.012) and from Sweden (HR = 0.22, 95% CI: 0.07-0.74, P = 0.014) had longer OS, whereas studies from the UK (HR = 1.49, 95% CI: 1.13-1.96, P = 0.005) and studies with nonmultivariate analysis of data type (HR = 1.35, 95% CI: 1.06-1.73, P = 0.014) had shorter OS. In addition, our study also found that patients with IDH2R140 mutation had significantly longer OS (HR = 0.61, 95% CI: 0.39-0.96, P = 0.032) and PFS (HR = 0.31, 95% CI: 0.18-0.52, P = 0.021) than patients with IDH2R172 mutation, despite some degree of heterogeneity. CONCLUSIONS: This meta-analysis demonstrates that IDH2R140 mutation improves OS in younger AML patients and that the prognostic value of IDH2R172 mutation is significantly heterogeneous. Differences in region and data type have a significant impact on the prognosis of AML patients with IDH2R140 and/or IDH2R172 mutations. Additionally, AML patients with IDH2R140 mutation have a better prognosis than those with IDH2R172 mutations, albeit with some degree of heterogeneity.

Chronic active Epstein-Barr virus infection involving gastrointestinal tract with hemophagocytic lymphohistiocytosis.

Chronic active EBV infection (CAEBV) is a lymphoproliferative disorder of T- or NK-cell type in Asian countries. CAEBV involving the gastrointestinal tract (GI CAEBV) is a rare condition with poor prognosis that may rapidly progress with hemophagocytic lymphohistiocytosis (HLH) and life-threatening complications such as GI bleeding and/or perforation. The approach to CAEBV with GI tract involvement (GI CAEBV) is still an unmet clinical need. In this case series study, we summarized the clinical features, treatment, and prognosis of seven cases of GI CAEBV with HLH, particularly focusing on its prognosis and the possible salvage therapy combining surgery, novel therapeutic agents, and/or autologous(auto-) hematopoietic stem cell transplantation (HSCT) based on successful cases from our center. GI CAEBV is often misdiagnosed as inflammatory bowel diseases and certain infections. The key to its early recognition is the integrative consideration of its systemic manifestation, serum virology, endoscopic, and imaging findings along with pathology. Surgical intervention should not be hesitated when life-threatening GI complications occur. Resection of the involved bowel segment is an effective way of controlling bleeding and reducing tumor burden. In addition to upfront allogeneic HSCT, new therapeutic modalities including PD-1 antibody and auto-HSCT may be effective in certain patients.

PIK3R3 Missense and NOTCH2 Synonymous Single Nucleotide Polymorphisms Are Associated with Liver Cancer.

BACKGROUND: Single nucleotide polymorphism (SNP) of candidate genes also affects the occurrence and prognosis of liver cancer. We mainly explored the effects of PIK3R3 and NOTCH2 polymorphisms on liver cancer risk among Chinese people. METHODS: Four SNPs (rs785468, rs785467, rs3795666, and rs17024525 in PIK3R3 and NOTCH2) from 709 liver cancer patients and 700 healthy controls were genotyped using the Agena MassARRAY system. The correlation between SNPs and liver cancer risk was evaluated using logistic regression analysis. The SNP-SNP interactions were conducted by the multifactor dimensionality reduction method. RESULTS: The results revealed that PIK3R3-rs785467 reduced the likelihood of liver cancer among Chinese Han people (p < 0.05). In addition, PIK3R3-rs785467 decreased the susceptibility to liver cancer in different populations (females, non-smokers, and age >55 years, p < 0.05). NOTCH2-rs3795666 reduced the susceptibility to liver cancer among males, drinkers, and patients aged >55 years (p < 0.05). CONCLUSIONS: Our results demonstrate that PIK3R3-rs785476 and NOTCH2-rs3795666 polymorphisms are responsible for decreasing the susceptibility of liver cancer development in the Chinese Han population.

Sparse Representation-Based Multi-Focus Image Fusion Method via Local Energy in Shearlet Domain.

Multi-focus image fusion plays an important role in the application of computer vision. In the process of image fusion, there may be blurring and information loss, so it is our goal to obtain high-definition and information-rich fusion images. In this paper, a novel multi-focus image fusion method via local energy and sparse representation in the shearlet domain is proposed. The source images are decomposed into low- and high-frequency sub-bands according to the shearlet transform. The low-frequency sub-bands are fused by sparse representation, and the high-frequency sub-bands are fused by local energy. The inverse shearlet transform is used to reconstruct the fused image. The Lytro dataset with 20 pairs of images is used to verify the proposed method, and 8 state-of-the-art fusion methods and 8 metrics are used for comparison. According to the experimental results, our method can generate good performance for multi-focus image fusion.

Multi-Focus Image Fusion via Distance-Weighted Regional Energy and Structure Tensor in NSCT Domain.

In this paper, a multi-focus image fusion algorithm via the distance-weighted regional energy and structure tensor in non-subsampled contourlet transform domain is introduced. The distance-weighted regional energy-based fusion rule was used to deal with low-frequency components, and the structure tensor-based fusion rule was used to process high-frequency components; fused sub-bands were integrated with the inverse non-subsampled contourlet transform, and a fused multi-focus image was generated. We conducted a series of simulations and experiments on the multi-focus image public dataset Lytro; the experimental results of 20 sets of data show that our algorithm has significant advantages compared to advanced algorithms and that it can produce clearer and more informative multi-focus fusion images.

A Lightweight Feature Distillation and Enhancement Network for Super-Resolution Remote Sensing Images.

Super-resolution (SR) images based on deep networks have achieved great accomplishments in recent years, but the large number of parameters that come with them are not conducive to use in equipment with limited capabilities in real life. Therefore, we propose a lightweight feature distillation and enhancement network (FDENet). Specifically, we propose a feature distillation and enhancement block (FDEB), which contains two parts: a feature-distillation part and a feature-enhancement part. Firstly, the feature-distillation part uses the stepwise distillation operation to extract the layered feature, and here we use the proposed stepwise fusion mechanism (SFM) to fuse the retained features after stepwise distillation to promote information flow and use the shallow pixel attention block (SRAB) to extract information. Secondly, we use the feature-enhancement part to enhance the extracted features. The feature-enhancement part is composed of well-designed bilateral bands. The upper sideband is used to enhance the features, and the lower sideband is used to extract the complex background information of remote sensing images. Finally, we fuse the features of the upper and lower sidebands to enhance the expression ability of the features. A large number of experiments show that the proposed FDENet both produces less parameters and performs better than most existing advanced models.

miR-4443 promotes radiation resistance of esophageal squamous cell carcinoma via targeting PTPRJ.

BACKGROUND: Radiotherapy is one of the main treatments for esophageal squamous cell carcinoma (ESCC), but its efficacy is limited by radioresistance. MicroRNAs play a crucial role in posttranscriptional regulation, which is linked to the cancer response to radiation. METHODS: We successfully established a radioresistant cell line model by using fractionated irradiation. qRT-PCR was adopted to detect the expression of miR-4443 in human normal esophageal cell lines, tumor cells, and radioresistant cells. Next, CCK-8, colony formation, apoptosis, and cell cycle assays were used to assess the biological effect of miR-4443. Weighted gene coexpression network analysis (WGCNA) was performed to identify potential radiosensitivity-related genes. Additionally, we predicted the probable targets of the miRNA using bioinformatic methods and confirmed them using Western blot. RESULTS: miR-4443 was significantly upregulated in radioresistant ESCC cells. Enhancement of miR-4443 further decreased the radiosensitivity of ESCC cells, while inhibition of miR-4443 increased the radiosensitivity of ESCC cells. Notably, miR-4443 modulated radiosensitivity by influencing DNA damage repair, apoptosis, and G2 cycle arrest. By using WGCNA and experimental validation, we identified PTPRJ as a key target for miRNA-4443 to regulate radiosensitivity. The effects of miR-4443 overexpression or inhibition could be reversed by increasing or decreasing PTPRJ expression. CONCLUSION: In this study, miR-4443 is found to promote radiotherapy resistance in ESCC cells by regulating PTPRJ expression, which provides a new perspective and clue to alleviate radioresistance.

Bendamustine versus chlorambucil in treatment of chronic lymphocytic leukaemia in China: a randomized, open-label, parallel-controlled, phase III clinical trial.

BACKGROUND: Chronic lymphoblastic leukemia (CLL) is the most common adult leukemia and mainly affects the elderly. Chemoimmunotherapy still has a role in the standard frontline therapy for specific population. However, the clinical activity of bendamustine has not been investigated in unfit Chinese patients with CLL. This study aimed to compare the efficacy and safety of bendamustine versus chlorambucil for untreated Chinese patients with Binet stage B/C CLL. METHODS: In this multi-center, randomized, open-label, parallel-controlled, phase III trial, patients with previously untreated CLL were enrolled and randomly assigned (1:1) to receive bendamustine or chlorambucil. The primary endpoint was the objective response rate. Secondary endpoints included progression-free survival, the duration of response, and overall survival. Adverse events were recorded to evaluate safety. RESULTS: Of 158 screened patients, 147 were enrolled and randomly allocated to receive bendamustine (n = 72) or chlorambucil (n = 75). After a median follow-up of 25.6 months (IQR 12.5-27.7), 69.0% (95% CI, 56.9-79.5) of bendamustine-treated patients achieved objective response and 37.0% (95% CI, 26.0-49.1) of chlorambucil with a difference of 32.0% (95%CI: 16.6-47.5), demonstrating the superiority of bendamustine to chlorambucil (p < 0.001). The median progression-free survival was longer for bendamustine (16.5 months; 95% CI, 11.3-24.7) versus chlorambucil (9.6 months; 95% CI, 8.7-11.8; p < 0.001). A longer median duration of response was seen in those receiving bendamustine (19.2 months; 95% CI, 11.8-29.1) than chlorambucil (10.7 months; 95% CI, 5.6-13.6; p = 0.0018). Median overall survival was not reached in either group. Overall survival at 18 months was 88% for bendamustine versus 85% for chlorambucil. Most common adverse events in both groups were neutropenia and thrombocytopenia. CONCLUSION: In untreated Chinese patients with Binet stage B/C CLL, bendamustine induced the better objective response and resulted in longer progression-free survival than chlorambucil. Overall, these results validate the role of bendamustine as an effective and safe first-line therapy in this population.

LncRNA RHPN1-AS1 inhibition induces autophagy and apoptosis in prostate cancer cells via the miR-7-5p/EGFR/PI3K/AKT/mTOR signaling pathway.

LncRNA RHPN1-AS1 (RHPN1-AS1) has been confirmed to promote tumor progression in multiple cancers and is upregulated in prostate cancer (PCa), but whether it has an effect on PCa progression remains unclear. In this study, we found that PCa patients with high RHPN1-AS1 expression had a shorter survival time, and RHPN1-AS1 was significantly upregulated in PCa tissues and cells. Based on informatics analysis we predicted that miR-7-5p binds to 3'UTR of RHPN1-AS1 and epidermal growth factor receptor (EGFR) and verified it by luciferase reporter gene assay. Subsequently, we transfected PCa cells with RHPN1-AS1 overexpression vector (RHPN1-AS1), knockdown plasmids (sh-RHPN1-AS1) and/or miR-7-5p mimics or inhibitor and/or overexpression vector (EGFR) or small interfering RNA of EGFR (si-EGFR) or its control, and found that overexpression of RHPN1-AS1 inhibited miR-7-5p expression and promoted EGFR expression, silencing RHPN1-AS1 inhibited proliferation and invasion, and induced G2/M arrest, apoptosis and autophagy in PCa cells. 3MA (an inhibitor of autophagy)-mediated autophagy inhibition attenuated RHPN1-AS1 inhibition-induced apoptosis. Overexpression miR-7-5p or silencing EGFR promoted LC3-I to LC3-II conversion, enhanced autophagy activity, induced cleaved-caspase-3 expression and apoptosis in PCa cells. Furthermore, overexpression of RHPN1-AS1 promoted phosphorylation of phosphatidylinositol 3-kinase (PI3K), AKT and mTOR, inhibited LC3-I to LC3-II conversion and reduced apoptosis in PCa cells, while GSK2126458 (an inhibitor of PI3K) reversed the effect of RHPN1-AS1 on PCa cells. In summary, RHPN1-AS1 acted as a ceRNA of miR-7-5p to upregulate EGFR expression, silencing RHPN1-AS1 suppressed PCa tumor progression by inducing autophagy and apoptosis in PCa cells through the miR-7-5p/EGFR/PI3K/AKT/mTOR pathway.

RDCTrans U-Net: A Hybrid Variable Architecture for Liver CT Image Segmentation.

Segmenting medical images is a necessary prerequisite for disease diagnosis and treatment planning. Among various medical image segmentation tasks, U-Net-based variants have been widely used in liver tumor segmentation tasks. In view of the highly variable shape and size of tumors, in order to improve the accuracy of segmentation, this paper proposes a U-Net-based hybrid variable structure-RDCTrans U-Net for liver tumor segmentation in computed tomography (CT) examinations. We design a backbone network dominated by ResNeXt50 and supplemented by dilated convolution to increase the network depth, expand the perceptual field, and improve the efficiency of feature extraction without increasing the parameters. At the same time, Transformer is introduced in down-sampling to increase the network's overall perception and global understanding of the image and to improve the accuracy of liver tumor segmentation. The method proposed in this paper tests the segmentation performance of liver tumors on the LiTS (Liver Tumor Segmentation) dataset. It obtained 89.22% mIoU and 98.91% Acc, for liver and tumor segmentation. The proposed model also achieved 93.38% Dice and 89.87% Dice, respectively. Compared with the original U-Net and the U-Net model that introduces dense connection, attention mechanism, and Transformer, respectively, the method proposed in this paper achieves SOTA (state of art) results.

Infrared Small Target Detection Using Regional Feature Difference of Patch Image.

Aiming at a thorny issue, that conventional small target detection algorithm using local contrast method is not sensitive for residual background clutter, robustness of algorithms is not strong. A Gaussian fusion algorithm using multi-scale regional patch structure difference and Regional Brightness Level Measurement is proposed. Firstly, Regional Energy Cosine (REC) is constructed to measure the structural discrepancy among a small target with neighboring cells. At the same time, Regional Brightness Level Measurement (RBLM) is constructed utilizing the brightness difference characteristics between small target and background areas. Then, a brand new Gaussian fusion algorithm is proposed for the generated saliency map in multi-scale space to characterize the overall heterogeneity in original infrared small target and local neighborhood. Finally, a self-adapting separation algorithm is adopted with the objective to obtain a small target from background interference. This method is able to utmostly restrain background interference and enhance the target. Extensive qualitative and quantitative testing results display that the desired algorithm has remarkable performance in strengthening target region and restraining background interference compared with current algorithms.

Multiscale Geometric Analysis Fusion-Based Unsupervised Change Detection in Remote Sensing Images via FLICM Model.

Remote sensing image change detection is widely used in land use and natural disaster detection. In order to improve the accuracy of change detection, a robust change detection method based on nonsubsampled contourlet transform (NSCT) fusion and fuzzy local information C-means clustering (FLICM) model is introduced in this paper. Firstly, the log-ratio and mean-ratio operators are used to generate the difference image (DI), respectively; then, the NSCT fusion model is utilized to fuse the two difference images, and one new DI is obtained. The fused DI can not only reflect the real change trend but also suppress the background. The FLICM is performed on the new DI to obtain the final change detection map. Four groups of homogeneous remote sensing images are selected for simulation experiments, and the experimental results demonstrate that the proposed homogeneous change detection method has a superior performance than other state-of-the-art algorithms.

Saliency-Guided Nonsubsampled Shearlet Transform for Multisource Remote Sensing Image Fusion.

The rapid development of remote sensing and space technology provides multisource remote sensing image data for earth observation in the same area. Information provided by these images, however, is often complementary and cooperative, and multisource image fusion is still challenging. This paper proposes a novel multisource remote sensing image fusion algorithm. It integrates the contrast saliency map (CSM) and the sum-modified-Laplacian (SML) in the nonsubsampled shearlet transform (NSST) domain. The NSST is utilized to decompose the source images into low-frequency sub-bands and high-frequency sub-bands. Low-frequency sub-bands reflect the contrast and brightness of the source images, while high-frequency sub-bands reflect the texture and details of the source images. Using this information, the contrast saliency map and SML fusion rules are introduced into the corresponding sub-bands. Finally, the inverse NSST reconstructs the fusion image. Experimental results demonstrate that the proposed multisource remote image fusion technique performs well in terms of contrast enhancement and detail preservation.