Robust treatment planning for small animal radio-neuromodulation using focused kV x-ray beams.

BACKGROUND: In preclinical radio-neuromodulation research, small animal experiments are pivotal for unraveling radiobiological mechanism, investigating prescription and planning techniques, and assessing treatment effects and toxicities. However, the target size inside a rat brain is typically in the order of sub-millimeters. The small target inside the visual cortex neural region in rat brain with a diameter of around 1 mm was focused in this work to observe the physiological change of this region. Delivering uniform doses to the small target while sparing health tissues is challenging. Focused kV x-ray technique based on modern x-ray polycapillary focusing lens is a promising modality for small animal radio-neuromodulation. PURPOSE: The current manual planning method could lead to sub-optimal plans, and the positioning uncertainties due to mechanical accuracy limitations, animal immobilization, and robotic arm motion are not considered. This work aims to design a robust inverse planning method to optimize the intensities of focused kV x-ray beams located in beam trajectories to irradiate small mm-sized targets in rat brains for radio-neuromodulation. METHODS: Focused kV x-ray beams were generated through polycapillary x-ray focusing lenses on achieving small (≤0.3 mm) focus perpendicular to the beam. The beam trajectories were manually designed in 3D space in scanning-while-rotating mode. Geant4 Monte Carlo (MC) simulation generated a dose calculation matrix for each focused kV x-ray beam located in beam trajectories. In the proposed robust inverse planning method, an objective function combining a voxel-wise stochastic programming approach and L1 norm regularization was established to overcome the positioning uncertainties and obtain a high-quality plan. The fast iterative shrinkage thresholding algorithm (FISTA) was utilized to solve the objective function and obtain the optimal intensities. Four cases were employed to validate the feasibility and effectiveness of the proposed method. The manual and non-robust inverse planning methods were also implemented for comparison. RESULTS: The proposed robust inverse planning method achieved superior dose homogeneity and higher robustness against positioning uncertainties. On average, the clinical target volume (CTV) homogeneity index (HI) of robust inverse plan improved to 13.3 from 22.9 in non-robust inverse plan and 53.8 in manual plan if positioning uncertainties were also present. The average bandwidth at D90 was reduced by 6.5 Gy in the robust inverse plan, compared to 9.6 Gy in non-robust inverse plan and 12.5 Gy in manual plan. The average bandwidth at D80 was reduced by 3.4 Gy in robust inverse plan, compared to 5.5 Gy in non-robust inverse plan and 8.5 Gy in manual plan. Moreover, the dose delivery time of manual plan was reduced by an average reduction of 54.7% with robust inverse plan and 29.0% with non-robust inverse plan. CONCLUSION: Compared to manual and non-robust inverse planning methods, the robust inverse planning method improved the dose homogeneity and delivery efficiency and was resistant to the uncertainties, which are crucial for radio-neuromodulation utilizing focused kV x-rays.

Chronic Allergen Exposure Contributes to Steroid Resistance via Increased Phosphorylation of Glucocorticoid Receptors S226 and p38 MAPK in a Mouse Model of Asthma.

Chronic allergen exposure can significantly induce p38 mitogen-activated protein kinase (MAPK) activation in asthma. p38 MAPK is involved in steroid resistance through phosphorylation of glucocorticoid receptors (GR) at S226. This study aims to investigate whether chronic allergen exposure can induce steroid resistance and whether it is associated with p38 MAPK activation in asthma. A mouse model of asthma was prepared by sensitizing and challenging mice with chronic ovalbumin (OVA) exposure. Key features of allergic asthma, encompassing bronchial hyperresponsiveness, pathology of lung tissues, cytokine profiles of inflammation in bronchoalveolar lavage fluid (BALF), and serum immunoglobulin (Ig)E concentration were evaluated. Furthermore, suppressive effects of corticosteroid on the splenocytes under stimulation of lipopolysaccharides, glucocorticoid receptor (GR) DNA binding ability of splenocytes, expression of GRα and phosphorylation of GR s226 in splenocytes, and p38 MAPK phosphorylation in splenocytes and lung tissues were determined. Chronic OVA exposure substantially induced airway hypersensitivity, leading to increased inflammatory infiltration in lung tissues. Additionally, it resulted in elevated levels of interleukin (IL)-4, IL-5, and IL-6 in BALF, as well as heightened levels of IgE in serum. Furthermore, OVA exposure substantially enhanced p38 MAPK phosphorylation in lung tissues. It also weakened the suppressive impacts of corticosteroids on splenocytes, impaired the GR DNA binding ability, and led to an enhanced phosphorylated state of GR S226 and p38 MAPK in splenocytes. Taken together, chronic allergen exposure contributes to steroid resistance in asthma, which is linked to an increased phosphorylated state of GR S226 and p38 MAPK.

Insight of the State for Deliberately Introduced A-Site Defect in Nanofibrous LaFeO3 for Boosting Artificial Photosynthesis of CH3OH.

Perovskite-type LaFeO3 is regarded as a potentially efficient visible-light photocatalyst owing to its narrow bandgap energy and unique photovoltaic properties. However, the insufficient active sites and the unsatisfactory utilization of photogenerated carriers severely restrict the realistic application of pure LaFeO3. Herein, we fabricated a series of LaxFeO3-δ nanofibers (x = 1.0, 0.95, 0.9, 0.85, 0.8) with an A-site defect via sol-gel combined with the electrospinning technique. Wherein, the nonstoichiometric La0.9FeO3-δ possessed the highest CH3OH yield of 5.30 µmol·g-1·h-1 with good chemical stability. A series of advanced characterizations were applied to investigate the physicochemical properties and charge-carrier behaviors of the samples. The results illustrated that the one-dimensional (1D) nanostructures combined with the appropriate concentration of vacancy defects on the surface contributed to the radial migration of photogenerated carriers, inhibited the recombination of carriers, and provided more CO2 adsorption-activation sites. Furthermore, density functional theory (DFT) calculations were employed to reveal the influence mechanism of vacancy defects on LaFeO3. This work provides a strategy to enhance the performance of photocatalytic CO2 reduction by modulating the induced oxygen vacancies caused by the A-site defect in perovskite oxides.

Automated Skeletal Bone Age Assessment with Two-Stage Convolutional Transformer Network Based on X-ray Images.

Human skeletal development is continuous and staged, and different stages have various morphological characteristics. Therefore, bone age assessment (BAA) can accurately reflect the individual's growth and development level and maturity. Clinical BAA is time consuming, highly subjective, and lacks consistency. Deep learning has made considerable progress in BAA in recent years by effectively extracting deep features. Most studies use neural networks to extract global information from input images. However, clinical radiologists are highly concerned about the ossification degree in some specific regions of the hand bones. This paper proposes a two-stage convolutional transformer network to improve the accuracy of BAA. Combined with object detection and transformer, the first stage mimics the bone age reading process of the pediatrician, extracts the hand bone region of interest (ROI) in real time using YOLOv5, and proposes hand bone posture alignment. In addition, the previous information encoding of biological sex is integrated into the feature map to replace the position token in the transformer. The second stage extracts features within the ROI by window attention, interacts between different ROIs by shifting the window attention to extract hidden feature information, and penalizes the evaluation results using a hybrid loss function to ensure its stability and accuracy. The proposed method is evaluated on the data from the Pediatric Bone Age Challenge organized by the Radiological Society of North America (RSNA). The experimental results show that the proposed method achieves a mean absolute error (MAE) of 6.22 and 4.585 months on the validation and testing sets, respectively, and the cumulative accuracy within 6 and 12 months reach 71% and 96%, respectively, which is comparable to the state of the art, markedly reducing the clinical workload and realizing rapid, automatic, and high-precision assessment.

Three-Dimensional Voxel-Wise Quantitative Assessment of Imaging Features in Hepatocellular Carcinoma.

Voxel-wise quantitative assessment of typical characteristics in three-dimensional (3D) multiphase computed tomography (CT) imaging, especially arterial phase hyperenhancement (APHE) and subsequent washout (WO), is crucial for the diagnosis and therapy of hepatocellular carcinoma (HCC). However, this process is still missing in practice. Radiologists often visually estimate these features, which limit the diagnostic accuracy due to subjective interpretation and qualitative assessment. Quantitative assessment is one of the solutions to this problem. However, performing voxel-wise assessment in 3D is difficult due to the misalignments between images caused by respiratory and other physiological motions. In this paper, based on the Liver Imaging Reporting and Data System (v2018), we propose a registration-based quantitative model for the 3D voxel-wise assessment of image characteristics through multiple CT imaging phases. Specifically, we selected three phases from sequential CT imaging phases, i.e., pre-contrast phase (Pre), arterial phase (AP), delayed phase (DP), and then registered Pre and DP images to the AP image to extract and assess the major imaging characteristics. An iterative reweighted local cross-correlation was applied in the proposed registration model to construct the fidelity term for comparison of intensity features across different imaging phases, which is challenging due to their distinct intensity appearance. Experiments on clinical dataset showed that the means of dice similarity coefficient of liver were 98.6% and 98.1%, those of surface distance were 0.38 and 0.54 mm, and those of Hausdorff distance were 4.34 and 6.16 mm, indicating that quantitative estimation can be accomplished with high accuracy. For the classification of APHE, the result obtained by our method was consistent with those acquired by experts. For the WO, the effectiveness of the model was verified in terms of WO volume ratio.

Icariin Improves Glucocorticoid Resistance in a Murine Model of Asthma with Depression Associated with Enhancement of GR Expression and Function.

Icariin, a flavonoid glycoside isolated from Epimedium brevicornum, exerts a variety of biological activities. However, its effects on depression-induced glucocorticoid resistance in asthma and the underlying mechanisms have not been elucidated. In this study, a murine model of asthma with depression was established by exposure to ovalbumin combined with chronic unpredictable mild stress, and icariin was given orally during ovalbumin challenge and chronic unpredictable mild stress exposure. Depression-like behaviors were assessed by the open field test, forced swim test, and tail suspension test. The characteristic features of allergic asthma, including airway hyperreactivity, histopathology, inflammatory cytokine levels in bronchoalveolar lavage fluid, and immunoglobulin E and corticosterone levels in serum, were examined. Following splenocyte isolation in vitro, the inhibitory effects of corticosterone on the proliferation and cytokine secretion of splenocytes, glucocorticoid receptor DNA-binding activity, and expression of p-glucocorticoid receptor s226, glucocorticoid receptor α, and p-p38 mitogen-activated protein kinase in splenocytes were determined. We found that icariin had limited effects on depression-like behaviors, however, it markedly suppressed airway hyperresponsiveness, inflammatory infiltration in lung tissues, levels of interleukin-4, interleukin-5, and interleukin-6 in bronchoalveolar lavage fluid, and immunoglobulin E in serum. Furthermore, icariin improved the inhibitory effects of corticosterone on lipopolysaccharide-stimulated splenocytes, increased the glucocorticoid receptor expression and glucocorticoid receptor DNA-binding activity, and inhibited the phosphorylation of glucocorticoid receptors S226 and p38 mitogen-activated protein kinase. Taken together, icariin improved glucocorticoid resistance in a murine model of asthma with depression associated with enhancement of glucocorticoid receptor function and glucocorticoid receptor expression, and its effects on the glucocorticoid receptor function were related to decreased phosphorylation of glucocorticoid receptors S226 and p38 mitogen-activated protein kinase.

Wenshen Yiqi Keli Mitigates the Proliferation and Migration of Cigarette Smoke Extract-Induced Human Airway Smooth Muscle Cells through miR-155/FoxO3a Axis.

Some domestic scholars revealed the effectiveness of Wenshen Yiqi Keli (WSYQKL) on chronic obstructive pulmonary disease (COPD). However, the exact mechanism of WSYQKL on COPD is fuzzy and needs further research. We adopted UPLC-Q/TOF-MS to analyze the chemical components of WSYQKL. In in vitro experiments, human airway smooth muscle cells (hASMCs) were intervened with 2.5% cigarette smoke extract (CSE), medicine serum of WSYQKL, miR-155 mimic, and FoxO3a silencing. Cell viability, proliferation, migration, and the expressions of miR-155, PCNA, Ki67, p21, p27, and FoxO3a were examined by cell counting kit-8, EdU staining, Transwell assay, scarification assay, qRT-PCR, immunol cytochemistry, and western blot, respectively. The association between miR-155 and FoxO3a was assessed by database and luciferase reporter gene analysis. We identified 47 kinds of chemical compositions of WSYQKL in ESI+ mode and 42 kinds of components of WSYQKL in ESI- mode. The medicine serum of WSYQKL strongly alleviated the proliferation and migration of hASMCs induced by CSE in a concentration-dependent manner. The medicine serum of WSYQKL enhanced the levels of p21, p27, and FoxO3a and weakened PCNA and Ki67 levels in hASMCs induced by CSE with the increase of concentration. MiR-155 mimic or FoxO3a silencing notably advanced CSE-treated HASMC viability, proliferation, migration, and the levels of PCNA and Ki67 and downregulated the levels of p21, p27, and FoxO3a in CSE-triggered hASMCs, which was reversed by WSYQKL-containing serum. Our results described that WSYQKL alleviated the proliferation and migration of hASMCs induced by CSE by modulating the miR-155/FoxO3a axis.

[Effect and mechanism of microRNA-155 in chronic obstructive pulmonary disease by targeting PIK3R1].

This study aimed to investigate the effect of microRNA-155 (miR-155) in chronic obstructive pulmonary disease (COPD) and cigarette smoke extract (CSE)-treated airway smooth muscle cells (ASMCs) by targeting phosphoinositide-3-kinase regulatory subunit 1 (PIK3R1) to regulate the PTEN/PI3K/Akt signaling pathway. The COPD mouse model was induced by lipopolysaccharide (LPS) combined with passive smoking. After modeling, miR-155 mimics and miR-155 inhibitor were used for intervention treatment. The pulmonary function of each group was detected by an EMKA detector. Hematoxylin-eosin (HE) staining was used to observe the pathological changes and scores of lung tissues. The expression of TNF-α, IL-6, and IL-1ß in bronchial alveolar lavage fluid (BALF) was detected by ELISA. Primary ASMCs were isolated and cultured in adherent tissue culture. The proliferation activity was detected by CCK-8 and EdU assays. Transwell and wound healing assays were used to measure the migration of ASMCs. The targeting relationship between miR-155 and PIK3R1 was validated by a double luciferase reporter gene assay. The expression levels of miR-155 and PIK3R1 mRNA in lung tissues of mice in each group were detected by quantitative reverse transcription-polymerase chain reaction (qRT-PCR). Western blot was used to detect the expression levels of Ki67, PNCA, PTEN, p-PI3K, PI3K, p85α, p-Akt, and Akt in lung tissues and ASMCs. The results showed that lung function was significantly reduced in the miR-155 mimic group, and the levels of PIK3R1 were significantly increased; while lung function in the miR-155 inhibitor group was significantly improved. The results of HE staining showed that there was obvious inflammatory cell infiltration in the miR-155 mimics group compared to that of the model group. Lung histopathological injury was significantly reduced in the miR-155 inhibitor group, accompanied by decreased expression of Ki67, PNCA, PI3K, p-Akt, increased PTEN and p85α protein levels, and reduced levels of TNF-α, IL-6, and IL-1ß in BALF. The results of the double luciferase reporter gene assay showed that miRNA-155 could target bind to PIK3R1. Compared with those in the CSE+miR-155 NC group, the proliferation and migration of ASMCs were significantly increased in the CSE+miR-155 group. The proliferation and migration of ASMCs were significantly attenuated in the CSE+miR-155+pcDNA PIK3R1 group compared with those in the CSE+miR-155 group, accompanied by decreased expression of Ki67, PNCA, p-Akt and increased PTEN and p85α protein levels. These results suggest that miR-155 activates the PTEN/PI3K/Akt signaling pathway by targeting PIK3R1 to promote the occurrence and development of COPD, which provides new evidence for the use of miR-155 in the treatment of COPD.

Identification of key immune genes for sepsis-induced ARDS based on bioinformatics analysis.

Regarding the extremely high mortality caused by sepsis-induced acute respiratory distress syndrome (ARDS), it is urgent to develop new biomarkers of sepsis-induced ARDS for treatment. Here, 532 differential expression genes (DEGs) related to sepsis and 433 DEGs related to sepsis-induced ARDS were screened in the GSE32707 dataset. Compared with sepsis samples, sepsis ARDS samples showed a higher infiltration of activated memory CD4 T cells and naive B cells, but a relatively lower infiltration of CD8 T cells. The pink and green modules which are significantly associated with sepsis-induced ARDS were then screened through co-expression network analysis. Differentially up-regulated GYPE and aberrantly down-regulated HSPB1, were subsequently found in the pink module of ARDS. CD81 and RPL22, two differentially low-expressed genes peculiar to ARDS, were identified in the green module. The function of CD81 was verified at the cellular level, and it was found that the up-regulation of CD81 in A549 could alleviate the LPS-induced injury of A549 cells. More importantly, the overexpressed CD81 can also increase the content of CD4+ CD25+ Foxp3+ Treg in Jurkat cells, and after the co-culture of overexpressed CD81 Jurkat cells with LPS treatment A549 cells, the LPS-induced lung epithelial cell damage can be improved. Overall, four new plasma biomarker candidates were found in sepsis-induced ARDS, and we verified that CD81 may play critical roles in the biological and immunological processes of sepsis-induced ARDS.

Rapid and precise diagnosis of T. marneffei pulmonary infection in a HIV-negative patient with autosomal-dominant STAT3 mutation: a case report.

BACKGROUND: Talaromyces marneffei, also named Penicillium marneffei, is an opportunistic pathogen that can cause systemic or limited infection in human beings. This infection is especially common in human immunodeficiency virus (HIV)-infected hosts; however, it has also been recently reported in HIV-negative hosts. Here, we report a very rarely seen case of T. marneffei pulmonary infection in a non-HIV-infected patient with signal transducer and activator of transcription 3 (STAT3) mutation. CASE PRESENTATION: A 34-year-old woman was admitted to our hospital for uncontrollable nonproductive cough and dyspnea with exercise. She had been immunocompromised since infancy. Computerized tomography scan showed multiple ground glass opacities with multiple bullae in both lungs. Next generation sequencing (NGS) of the bronchoalveolar lavage fluid identified T. marneffei nucleotide sequences. Culture of bronchoscopy specimens further verified the results. The patient was HIV negative, and blood gene detection indicated STAT3 mutation. To date, following the application of itraconazole, the patient has recovered satisfactorily. CONCLUSION: In clinical practice, T. marneffei infection among HIV-negative individuals is relatively rare, and we found that patients who are congenitally immunocompromised due to STAT3 mutation may be potential hosts. Early diagnosis and timely treatment are expected to improve the prognosis of T. marneffei infection. NGS is a powerful technique that may play an important role in this progress. The reviews of this paper are available via the supplemental material section.

Radical local treatment for stage IV non-small cell lung cancer in older adults: a propensity-score matched analysis of the SEER database.

BACKGROUND: Increased incidence of lung cancer in older adults is attributed to increased life expectancy, increased risk for many types of cancer, age-associated comorbidities and physical performance status. Contraindicatory tumor resection is suggested to benefit survival outcomes in stage IV non-small-cell lung cancer (NSCLC). We analyzed the clinical characteristics of older adults ≥70 years old with stage IV NSCLC and investigated whether radical local treatment may benefit this population. METHODS: This retrospective, population-based cohort study analyzed patient data from the USA Surveillance, Epidemiology and End Results (SEER) Program during 2004-2016. Eligible patients were aged ≥70 years and diagnosed with stage IV NSCLC. Primary endpoints were overall survival (OS) and lung-cancer-specific survival (LCSS). Propensity-score matching (PSM) and Cox regression analysis were performed to assess the prognostic role of surgical resection of primary tumor or metastasis. RESULTS: Among 54,310 stage IV NSCLC older patients, 7.50% received radical local treatment of the primary tumor or metastasis. PSM resulted in a balanced study population consisting of a treatment group (n=4,037) and a matched no-local-treatment group (n=15,658). After adjusting for confounders, radical local treatment was significantly associated with increased LCSS [hazard ratio (HR): 0.85, 95% confidence interval (95% CI): 0.72-1.00] but decreased OS (HR: 1.97, 95% CI: 1.31-2.97, P=0.0012). CONCLUSIONS: In older adults ≥70 years old with stage IV NSCLC, radical local treatment is associated with increased LCSS but decreased OS. Additional prospective studies are warranted to confirm the benefit of radical local treatment for primary or metastatic NSCLC.

Fusion of mis-registered GFP and phase contrast images with convolutional sparse representation and adaptive region energy rule.

Biomedical image fusion is the process of combining the information from different imaging modalities to get a synthetic image. Fusion of phase contrast and green fluorescent protein (GFP) images is significant to predict the role of unknown proteins, analyze the function of proteins, locate the subcellular structure, and so forth. Generally, the fusion performance largely depends on the registration of GFP and phase contrast images. However, accurate registration of multi-modal images is a very challenging task. Hence, we propose a novel fusion method based on convolutional sparse representation (CSR) to fuse the mis-registered GFP and phase contrast images. At first, the GFP and phase contrast images are decomposed by CSR to get the coefficients of base layers and detail layers. Secondly, the coefficients of detail layers are fused by the sum modified Laplacian (SML) rule while the coefficients of base layers are fused by the proposed adaptive region energy (ARE) rule. ARE rule is calculated by discussion mechanism based brain storm optimization (DMBSO) algorithm. Finally, the fused image is achieved by carrying out the inverse CSR. The proposed fusion method is tested on 100 pairs of mis-registered GFP and phase contrast images. The experimental results reveal that our proposed fusion method exhibits better fusion results and superior robustness than several existing fusion methods.

Fractional-order Darwinian PSO-based feature selection for media-adventitia border detection in intravascular ultrasound images.

Media-adventitia (MA) border delineates the outer appearance of arterial wall in intravascular ultrasound (IVUS) image. The detection of MA border is a challenging topic due to many difficulties such as complicated intravascular structures, intrinsic artifacts and image noises. We propose a classification-based MA border detection method with an embedded feature selection technique. The feature selection technique is based on Fractional-order Darwinian particle swarm optimization (FODPSO) algorithm. By employing feature selection, 293-dimension features including multi-scale features, gray-scale features and morphological feature are reducing to 37-dimension. The border detection method with feature selection is tested on a public dataset extracted from in-vivo pullbacks of human coronary arteries, which contains 77 IVUS images. Three indicators, Jaccard (JACC), Hausdorff Distance (HD) and Percentage of Area Difference (PAD), are measured for quantitative evaluation. Detection with 293-dimension features obtains JACC 0.79, HD 1.41 and PAD 0.16, while detection with 37-dimension features obtains JACC 0.83, HD 1.27 and PAD 0.12, indicating that the FODPSO-based feature selection method improves MA border detection by JACC 0.04, HD 0.14 and PAD 0.04. Furthermore, the proposed border detection method acquires better performances compared with two other automatic methods conducted on the same dataset available in literature.

CATARACTS: Challenge on automatic tool annotation for cataRACT surgery.

Surgical tool detection is attracting increasing attention from the medical image analysis community. The goal generally is not to precisely locate tools in images, but rather to indicate which tools are being used by the surgeon at each instant. The main motivation for annotating tool usage is to design efficient solutions for surgical workflow analysis, with potential applications in report generation, surgical training and even real-time decision support. Most existing tool annotation algorithms focus on laparoscopic surgeries. However, with 19 million interventions per year, the most common surgical procedure in the world is cataract surgery. The CATARACTS challenge was organized in 2017 to evaluate tool annotation algorithms in the specific context of cataract surgery. It relies on more than nine hours of videos, from 50 cataract surgeries, in which the presence of 21 surgical tools was manually annotated by two experts. With 14 participating teams, this challenge can be considered a success. As might be expected, the submitted solutions are based on deep learning. This paper thoroughly evaluates these solutions: in particular, the quality of their annotations are compared to that of human interpretations. Next, lessons learnt from the differential analysis of these solutions are discussed. We expect that they will guide the design of efficient surgery monitoring tools in the near future.

Detecting the Media-adventitia Border in Intravascular Ultrasound Images through a Classification-based Approach.

The detection of the media-adventitia (MA) border in intravascular ultrasound (IVUS) images is essential for vessel assessment and disease diagnosis. However, it remains a challenging task, considering the existence of plaque, calcification, and various artifacts. In this article, an effective method based on classification is proposed to extract the MA border in IVUS images. First, a novel morphologic feature describing the relative position of each structure relative to the MA border, called RPES for short, is proposed. Then, the RPES feature and other features are employed in a multiclass extreme learning machine (ELM) to classify IVUS images into nine classes including the MA border and other structures. At last, a modified snake model is employed to effectively detect the MA border in the rectangular domain, in which a modified external force field is constructed on the basis of local border appearances and classification results. The proposed method is evaluated on a public dataset with 77 IVUS images by three indicators in eight situations, such as calcification and a guide wire artifact. With the proposed RPES feature, detection performances are improved by more than 39 percent, which shows an apparent advantage in comparative experiments. Furthermore, compared with two other existing methods used on the same dataset, the proposed method achieves 18 of the best indicators among 24, demonstrating its higher capability in detecting the MA border.

A Novel Feature Selection Method Based on Extreme Learning Machine and Fractional-Order Darwinian PSO.

The paper presents a novel approach for feature selection based on extreme learning machine (ELM) and Fractional-order Darwinian particle swarm optimization (FODPSO) for regression problems. The proposed method constructs a fitness function by calculating mean square error (MSE) acquired from ELM. And the optimal solution of the fitness function is searched by an improved particle swarm optimization, FODPSO. In order to evaluate the performance of the proposed method, comparative experiments with other relative methods are conducted in seven public datasets. The proposed method obtains six lowest MSE values among all the comparative methods. Experimental results demonstrate that the proposed method has the superiority of getting lower MSE with the same scale of feature subset or requiring smaller scale of feature subset for similar MSE.

Fusion of GFP and phase contrast images with complex shearlet transform and Haar wavelet-based energy rule.

Image fusion techniques can integrate the information from different imaging modalities to get a composite image which is more suitable for human visual perception and further image processing tasks. Fusing green fluorescent protein (GFP) and phase contrast images is very important for subcellular localization, functional analysis of protein and genome expression. The fusion method of GFP and phase contrast images based on complex shearlet transform (CST) is proposed in this paper. Firstly the GFP image is converted to IHS model and its intensity component is obtained. Secondly the CST is performed on the intensity component and the phase contrast image to acquire the low-frequency subbands and the high-frequency subbands. Then the high-frequency subbands are merged by the absolute-maximum rule while the low-frequency subbands are merged by the proposed Haar wavelet-based energy (HWE) rule. Finally the fused image is obtained by performing the inverse CST on the merged subbands and conducting IHS-to-RGB conversion. The proposed fusion method is tested on a number of GFP and phase contrast images and compared with several popular image fusion methods. The experimental results demonstrate that the proposed fusion method can provide better fusion results in terms of subjective quality and objective evaluation.

Image Fusion of CT and MR with Sparse Representation in NSST Domain.

Multimodal image fusion techniques can integrate the information from different medical images to get an informative image that is more suitable for joint diagnosis, preoperative planning, intraoperative guidance, and interventional treatment. Fusing images of CT and different MR modalities are studied in this paper. Firstly, the CT and MR images are both transformed to nonsubsampled shearlet transform (NSST) domain. So the low-frequency components and high-frequency components are obtained. Then the high-frequency components are merged using the absolute-maximum rule, while the low-frequency components are merged by a sparse representation- (SR-) based approach. And the dynamic group sparsity recovery (DGSR) algorithm is proposed to improve the performance of the SR-based approach. Finally, the fused image is obtained by performing the inverse NSST on the merged components. The proposed fusion method is tested on a number of clinical CT and MR images and compared with several popular image fusion methods. The experimental results demonstrate that the proposed fusion method can provide better fusion results in terms of subjective quality and objective evaluation.