Search

MRI brain images are always of low contrast, which makes it difficult to identify to which area the information at the boundary of brain images belongs. This can make the extraction of features at the boundary more challenging, since those features can be misleading as they might mix properties of different brain regions. Hence, to alleviate such a problem, image boundary detection plays a vital role in medical image segmentation, and brain segmentation in particular, as unclear boundaries can worsen brain segmentation results. Yet, given the low quality of brain images, boundary detection in the context of brain image segmentation remains challenging. Despite the research invested to improve boundary detection and brain segmentation, these two problems were addressed independently, i.e., little attention was paid to applying boundary detection to brain segmentation tasks. Therefore, in this paper, we propose a boundary detection-based model for brain image segmentation. To this end, we first design a boundary segmentation network for detecting and segmenting images brain tissues. Then, we design a boundary information module (BIM) to distinguish boundaries from the three different brain tissues. After that, we add a boundary attention gate (BAG) to the encoder output layers of our transformer to capture more informative local details. We evaluate our proposed model on two datasets of brain tissue images, including infant and adult brains. The extensive evaluation experiments of our model show better performance (a Dice Coefficient (DC) accuracy of up to $$5.3\%$$ 5.3 % compared to the state-of-the-art models) in detecting and segmenting brain tissue images.

Boundary detection is a challenging problem in medical image segmentation. Clear boundaries yield a good segmentation result. In this paper, firstly, we design a boundary segmentation network for the detection and segmentation of brain tissues. Secondly, to help distinguishing between the boundaries for the three different brain tissues, we design the boundary information module (BIM ). Then, we added a boundary attention gate (BAG) to each end layer of the encoder to capture more local details. Extensive experiments verified the high performance of our proposed model for the detection and segmentation of brain tissues.

Heterogeneous multicore processors have recently become de facto computing engines for state-of-the-art embedded applications. Nonetheless, very little research focuses on the scheduling of periodic (implicit-deadline) real-time tasks upon heterogeneous multicores under the requirements of task synchronization, which is stemmed from resource access conflicts and can greatly affect the schedulability of tasks. In view of partitioned Earliest Deadline First and Multiprocessor Stack Resource Policy, we first discuss the blocking-aware utilization bound for uniform heterogeneous multicores and then illustrate its non-monotonicity, where the bound may decrease with more deployed cores. Following the insights obtained from the bound analysis, taking the system heterogeneity into consideration, we propose a Synchronization-Aware Task Partitioning Algorithm for Heterogeneous Multicores (SA-TPA-HM)). Several resource-guided and heterogeneity-oriented mapping heuristics are incorporated to reduce the negative impacts of blocking interferences for better schedulability performance of tasks and balanced workload distribution across cores. The extensive simulation results show that SA-TPA-HM can obtain the schedulability ratios approximate to an Integer Non-Linear Programming--based solution, and much higher (e.g., 60% more) in contrast to the existing partitioning algorithms targeted at homogeneous multicores. The measurement results in Linux kernel further reveal the practical viability of SA-TPA-HM that can experience lower runtime overhead (e.g., 15% less) when compared to other mapping schemes.

As the computing devices and software executions are susceptible to manifold faults, fault tolerance has been an important research topic in safety-critical real-time systems. Moreover, multicore processors have recently emerged as prevailing computing engines for modern embedded systems. However, there exists rather rare work on the fault-tolerant scheduling of real-time tasks executing on multicores with shared resources, where the task synchronization originated from resource access contention may significantly degrade the schedulability of task system. With the focus on the partitioned-EDF scheduler with the MSRP (Multiprocessor Stack Resource Policy) protocol and primary/backup recovery mechanism, we first investigate a utilization bound and then identify its anomaly where the bound may decrease when more cores are deployed. Next, following the insights gained by the analysis of the bound, we propose a reliability and synchronization aware task partitioning algorithm (RSA-TPA) together with an efficient version to implement the joint management of task synchronization and system reliability, where several resource-oriented heuristics are developed to improve both the schedulability performance and workload balancing. The extensive simulation results show that the RSA-TPA schemes can obtain higher acceptance ratio (e.g., 60 percent more) and generate more balanced partitions, when compared to the existing schemes that consider either reliability management or task synchronization. Finally, with the different fault arrival rates being considered, the actual implementation in Linux kernel further demonstrates the applicability of RSA-TPA that has lower run-time overhead (e.g., 20 percent less) in comparison with other mapping algorithms.

Image segmentation is a new challenge prob- lem in medical application. The use of medical imaging has become an integral part of research, as it allows us to see inside the human body without surgical intervention. Many researcher have studied brain segmentation. One stage method is used to segment the brain tissues. In this paper, we proposed the multi-stage generative ad- versarial network to solve the problem of information loss in the one-stage. We utilize the coarse-to-fine to improve brain segmentation using multi-stage generative adversar- ial networks (GAN). In the first stage, our model generated a coarse outline for (i) background and (ii) brain tissues. Then, in the second stage, the model generated outline for (i) white matter (WM), (ii) gray matter (GM) and (iii) cerebrospinal fluid (CSF). A good result can be achieved by fusing the coarse outline and refine outline. We conclude that our model is more efficient and accu- rate in practice for both infant and adult brain segmenta- tion. Moreover, we observe that multi-stage model is faster than prior models. To be more specific, the main goal of multi-stage model is to see the performance of the model in a few shot learning case where a few labeled data are available. For medical image, this proposed model can work in a wide range of image segmentation where the convolution neural networks and one-stage methods have failed.

Prostate cancer occurs in the prostatic epithelium and poses a threat to the health of middle-aged and older males. The objective of the present study was to explore the roles of microRNA (miRNA/miR)-130b in prostate cancer and potential molecular mechanisms in order to control the migration and invasion of prostate cancer. For this purpose, reverse transcription-PCR was performed to evaluate the mRNA levels of DLL1, phosphoinositide-3 kinase (PI3K), protein kinase B (Akt) and matrix metalloproteinase (MMP)9, and western blot analysis was carried out to detect the protein expression levels of DLL1, phosphorylated (p)-PI3K, p-Akt and MMP9. A Transwell assay was conducted to examine the invasion rate of prostate cancer cells. Furthermore, a scratch wound assay was performed to examine the migration rate of prostate cancer cells. A luciferase assay was performed to examine the interaction between miRNA and its target mRNA. The results revealed that miR-130b had abnormal (low) expression in tumor tissues compared with that in the adjacent normal tissue. An miR-130b mimic suppressed the expression of DLL1. The expression of p-PI3K, p-Akt and MMP9 in prostate cancer cells transfected with the miR-130b mimic was decreased in comparison to the negative control and control groups. Furthermore, migration and invasion were significantly suppressed in the miR-130b mimic group. In conclusion, a novel pathway interlinking miR-130b and MMP9, p-Akt and p-PI3K, which regulates the migration and invasion of prostate cancer cells, was identified. These findings provide an intriguing biomarker and treatment strategy for patients with prostate cancer.

With an objective to provide the proactive and personalized services for human beings, Cyber-Physical-Social Systems (CPSS), which combine the cyber space, physical space, and social space together, need to process the large scale heterogenous data first. Tensor, as an appropriate data representation tool, has been widely used for representation of heterogeneous Cyber-Physical-Social big data. When computationally processing such tensor, many necessary constraints have to be taken into account, e.g., the execution time, energy consumption, economic cost, security as well as reliability. However, the systematic integration of these constraints and then the modelling of general optimization for tensor processing become more challenging. In this paper, with such constraints being considered together, a general model for tensor computation that optimizes the execution time, energy consumption, and economic cost with acceptable security and reliability is proposed. From diverse perspectives of user requirements, a case study for the tree-based distributed High-Order Singular Value Decomposition (HOSVD) is measured. With the focus on multi-objective combination, the experimental results validate the applicability and generality of the proposed model.

Radio frequency identification (RFID) systems, as one of the key components in the Internet of Things (IoT), have attracted much attention in the domains of industry and academia. In practice, the performance of RFID systems rather relies on the effectiveness and efficiency of anti-collision algorithms. A large body of studies have recently focused on the anti-collision algorithms, such as the Q-algorithm ( QA ), which has been successfully utilized in EPCglobal Class-1 Generation-2 protocol. However, the performance of those anti-collision algorithms needs to be further improved. Observe that fully exploiting the pre-processing time can improve the efficiency of the QA algorithm. With an objective of improving the performance for anti-collision, we propose a Nested Q-algorithm ( NQA ), which makes full use of such pre-processing time and incorporates the advantages of both Binary Tree ( BT ) algorithm and QA algorithm. Specifically, based on the expected number of collision tags, the NQA algorithm can adaptively select either BT or QA to identify collision tags. Extensive simulation results validate the efficiency and effectiveness of our proposed NQA (i.e., less running time for processing the same number of active tags) when compared to the existing algorithms.

Background Radiofrequency ablation and microwave ablation are frequently prescribed for thoracic cancer. However, few writers have been able to draw on any systematic research into the differences between the two ablation methods. Methods A literature search was carried out using Embase, PUBMED, Web of Science, Cochrane Library, and CNKI databases, with additional searches carried out manually using terms associated with thoracic cancer and thermal ablation. Then we used Google Scholar for a complementary search. Data were extracted from studies of patients that underwent radiofrequency ablation or microwave ablation, and the investigator carried out efficacy evaluation and follow up. The data obtained from the literature were summarized and analyzed using Cochrane Revman software Version 5.3 and SPSS 22.0. Results There were seven comparative studies, but no randomized studies identified for data extraction; 246 patients received radiofrequency ablation therapy and 319 controls received microwave ablation. There was no significant difference in the six-month, one-year, two-year, and three-year survival rates, and adverse reactions were found in the two treatments. For patients' long-term survival rate, the two treatments can achieve a similar survival time. Conclusion In the treatment of thoracic cancer, microwave ablation can achieve the same efficacy as radiofrequency ablation.

Background Patients with advanced body/tail pancreatic cancer have poor quality of life and low overall survival rate. In recent years, interventional diagnosis and treatment of advanced pancreatic cancer have become increasingly widespread. This retrospective cohort study investigated the efficacy of routine intravenous chemotherapy (the control group), transcatheter arterial infusion (TAI) chemotherapy, and TAI combined with radioactive particles as therapeutic methods for advanced body/tail cancer pancreatic by assessing the short-term and overall survival rates. Methods We screened our prospective database for patients with advanced body/tail pancreatic cancer, which tumor deemed unresectable and no other confirmed malignant tumors, patients were assigned into three groups according to their treatment. Analyses with regard to the clinical responses, the 6, 12, and 18-month survival rates and overall survival rates were performed. Results The median survival time was 6 months in the control group, 10 months in the TAI group and 13 months in the TAI combined group. The Kaplan–Meier estimates of the OS among the three groups, indicating that there is significant difference among three groups (P༜0.000). The clinical remission rates were 17.5% in the control group, 41.5% in the TAI group, and 48.0% in the TAI combined group. Covariates analyzed showed that different treatment methods and times affected the results significantly (P༜0.002). Conclusions In the treatment of advanced body/tail pancreatic cancer, TAI and TAI combined with radioactive particles significantly improved the clinical outcomes in patients compared with routine intravenous chemotherapy.

Background: This study systematically reviews the data for transcatheter arterial chemoembolization (TACE) alone or combined TACE and cryoablation therapy of hepatocellular carcinoma, aiming to provide clinical choice references for treatment of cancer. Methods: Electronic databases (PubMed, EMBASE, China National Knowledge Infrastructure, and Google Scholar) were systematically searched to include relevant studies published in English and Chinese between Jan 1, 2000, to July 31, 2017. The analysis was conducted in RevMan 5.3 based on random effects models. Results: Nineteen trials (n = 1427) were included. Combined TACE and cryoablation therapy had higher survival rate (1-year survival [RR 1.37; 95%-CI 1.26,1.49], 2-year survival [RR 1.50; 95%-CI 1.25,1.79], 3-year survival [RR 1.67; 95%-CI 1.16,2.40]), complete necrosis [RR 2.53; 95%-CI 2.07,3.10] and tumor control [RR 1.57; 95%-CI 1.40,1.75], which is more favorable for long-term efficacy of non-surgical hepatocellular carcinoma. Tumor recurrence of control group was above combination therapy [RR 0.27; 95%-CI 0.17, 0.43]. Compared with transcatheter arterial chemoembolization, effect of combination therapy occurred mainly in the survival, complete necrosis, tumor control, and recurrence. Taking combination therapy was generally more effective than taking TACE only. Conclusion: Compared with TACE only used to treat cancer, combination therapy had the best effect profile in general, and it had better survival in HCC when taking an integrated approach. The prognosis of treatments based on combination therapy is modulated by cryoablation.

Lung cancer ranks first in incidence and mortality in China. Surgery is the primary method to cure cancer, but only 20-30% of patients are eligible for curative resection. In recent years, in addition to surgery, other local therapies have been developed for patients with numerous localized primary and metastatic pulmonary tumors, including stereotactic body radiation therapy and thermal ablative therapies through percutaneously inserted applicators. Percutaneous thermal ablation of pulmonary tumors is minimally invasive, conformal, repeatable, feasible, cheap, has a shorter recovery time, and offers reduced morbidity and mortality. Radiofrequency ablation (RFA), the most commonly used thermal ablation technique, has a reported 80-90% rate of complete ablation, with the best results obtained in tumors < 3 cm in diameter. Because the clinical efficacy of RFA of pulmonary tumors has not yet been determined, this clinical guideline describes the techniques used in the treatment of localized primary and metastatic pulmonary tumors in nonsurgical candidates, including mechanism of action, devices, indications, techniques, potential complications, clinical outcomes, post-ablation surveillance, and use in combination with other therapies. In the future, the role of RFA in the treatment of localized pulmonary tumors should ultimately be determined by evidence from prospective randomized controlled trials comparing sublobar resection or stereotactic body radiation therapy.

Monosized spherical Cu–20% Sn (wt%) alloy particles with diameter ranging from 70.6 to 334.0 µm were prepared by the pulsated orifice ejection method (termed “POEM”). Fully dense without pores and bulk inclusions, the cross-sectional micrographs of the spherical alloy particles indicate an even distribution of Cu and Sn. These spherical Cu–Sn alloy particles exhibit a good spherical shape and a narrow size distribution, suggesting that the liquid Cu–Sn alloy can completely break the balance between the surface tension and the liquid static pressure in the crucible micropores and accurately control the volume of the droplets. Furthermore, the cooling rate of spherical Cu–20% Sn alloy particles is estimated by a Newton’s cooling model. The cooling rate of the Cu–20% Sn alloy particle decreases gradually with the particle diameter increasing. Smaller particles have higher cooling rates and when the particle diameter is less than 70 µm, the cooling rate of particles can reach more than 3.3 × 104 K/s. The secondary dendrite arm spacing has strong dependence on particle diameter which increases gradually with the increase of particle diameter. The results demonstrate that POEM is an effective route for fabrication of high-quality monosized Cu–20% Sn alloy particles.

In mixed-criticality (MC) systems, multiple activities with various certification requirements (thus with different criticality levels) can co-exist on shared hardware platforms, where multicore processors have emerged as the de facto computing engines. In this paper, by using the partitioned earliest-deadline-first with virtual deadlines (EDF-VDs) scheduler for a set of periodic MC tasks running on multicore systems, we derive a criticality-aware utilization bound for efficient feasibility tests and then identify its characteristics . Our analysis shows that the bound increases with increasing number of cores and decreasing system criticality level. We show that, since the utilizations of MC tasks at different criticality levels can vary considerably, the utilization contribution of a task on different cores may have large variations and thus can significantly affect the system schedulability under the EDF-VD scheduler. Based on these observations, we propose a novel and efficient criticality-aware task partitioning algorithm (CA-TPA) to compensate for the inherent pessimism of the utilization bound. In order to improve the system schedulability, the task priorities are determined according to their utilization contributions to the system in CA-TPA. Moreover, by analyzing the utilization variations of tasks at different levels, we develop several heuristics to minimize the utilization increment and balance the workload on cores. The simulation results show that the CA-TPA scheme is very effective in achieving higher schedulability ratio and yielding balanced workloads. The actual implementation in Linux operating system further demonstrates the applicability of CA-TPA with lower run-time overhead, compared to the existing partitioning schemes.

In mixed-criticality (MC) system, diverse application activities with various certification requirements (different criticality) can share a computing platform, where multicore processors have emerged as the prevailing computing engines. Focusing on the problem of resource access contention in multicore MC systems, we analyze the synchronization issues and blocking characteristics of the Multiprocessor Stack Resource Policy (MSRP) with both priority and criticality inversions among MC tasks being considered. We develop the first criticality-aware utilization bound under partitioned Earliest Deadline First (EDF) and MSRP by taking the worst case synchronization overheads of tasks into account. The non-monotonicity of the bound where it may decrease when more cores are deployed is identified, which can cause anomalies in the feasibility tests. With the objective to improve system schedulability, a novel criticality-cognizant and resource-oriented analysis approach is further studied to tighten the bound on the synchronization overheads for MC tasks scheduled under partitioned EDF and MSRP. The simulation results show that the new analysis approach can effectively reduce the blocking times for tasks (up to 30 percent) and thus improve the schedulability ratio (e.g., 10 percent more). The actual implementation in Linux kernel further shows the practicability of partitioned-EDF with MSRP (with run-time overhead being about 3 to 7 percent of the overall execution time) for MC tasks running on multicores with shared resources.

Weakly-hard real-time scheduling enables to tolerate certain execution timeouts of tasks, and has been widely exploited in those intelligent embedded systems over the past two decades. In general, the current weakly-hard real-time scheduling algorithms try to rapidly raise the priorities of jobs (instances) of those tasks that have missed deadlines to guarantee their individual weakly-hard constraints, while neglecting the impacts of whole task system emergency on the schedulability results. From the perspective of increasing the schedulability ratio of weakly-hard real-time task set upon a uniprocessor platform, we develop a Global Emergency-Based Scheduling (GEBS) algorithm. First, with the goal of guaranteeing the weakly-hard timeliness of jobs, the GEBS scheme formulates a set of global job-level policies for priority allocations based on the emergency-classes of jobs. With the emergency degree of whole task system being considered, GEBS intends to fairly tune the priorities of those urgent jobs following our priority adjustment scheme to reduce the possibility of dynamic failures (i.e., deadline misses) of jobs. Moreover, for a task, the minimum arrival-interval of two jobs that have the same emergency-class is thoroughly analyzed, and then its WCRT (Worst-Case Response Time) corresponding to each emergency-class can be obtained recursively. Furthermore, the schedulability test is discussed based on the WCRT analysis, followed by the investigation of a new LCM (Least Common Multiple)-based method under weakly-hard constraints for better feasibility of task set. Finally, the extensive results from simulations and case study demonstrate that the GEBS algorithm can effectively improve the schedulability performance with regard to acceptance ratio (e.g., 50% more) with acceptable running time, when compared to the existing task-level and job-class-level scheduling. The empirical results in Linux kernel further exhibit the applicability of GEBS that can experience comparable online overhead in contrast with other schemes.

Primary/Backup has been well studied as an effective fault-tolerance technique. In this paper, with the objectives of tolerating a single permanent fault and maintaining system reliability with respect to transient faults, we study dynamic-priority based energy-efficient fault-tolerance scheduling algorithms for periodic real-time tasks running on multiprocessor systems by exploiting the primary/backup technique while considering the negative effects of the widely deployed Dynamic Voltage and Frequency Scaling (DVFS) on transient faults. Specifically, by separating primary and backup tasks on their dedicated processors, we first devise two schemes based on the idea of Standby-Sparing (SS): For Paired-SS, processors are organized as groups of two (i.e., pairs) and the existing SS scheme is applied within each pair of processors after partitioning tasks to the pairs. In Generalized-SS, processors are divided into two groups (of potentially different sizes), which are denoted as primary and secondary processor groups, respectively. The main (backup) tasks are scheduled on the primary (secondary) processor group under the partitioned-EDF (partitioned-EDL) with DVFS (DPM) to save energy. Moreover, we propose schemes that allocate primary and backup tasks in a mixed manner to better utilize system slack on all processors for more energy savings. On each processor, the Preference-Oriented Earliest Deadline (POED) scheduler is adopted to run primary tasks at scaled frequencies as soon as possible (ASAP) and backup tasks at the maximum frequency as late as possible (ALAP) to save energy. Our empirical evaluations show that, for systems with a given number of processors, there normally exists a configuration for Generalized-SS with different number of processors in primary and backup groups, which leads to better energy savings when compared to that of the Paired-SS scheme. Moreover, the POED-based schemes normally have more stable performance and can achieve better energy savings.

Cost savings are very critical in modern heterogeneous computing systems, especially in embedded systems. Task scheduling plays an important role in cost savings. In this article, we tackle the problem of scheduling tasks on heterogeneous multicore embedded systems with the constraints of time and resources for minimizing the total cost, while considering the communication overhead. This problem is NP-hard and we propose several heuristic techniques— ISGG , RLD , and RLDG —to address the problem. Experimental results show that the proposed algorithms significantly outperform the existing approaches in terms of cost savings.

With the rapid advancement and broad applications of intelligent vehicles, the design towards the on-board intelligent system has emerged as one of research hot spots in the area of automotive software. In addition, graphical HMI (Human-Machine Interaction) has become the most important means of human-machine interaction thanks to its good user experience. For better graphical human-machine interaction, the framebuffer scheme provides a virtual driver scheme for display devices, which not only improves the portability of graphics system but significantly facilitates the development of graphical applications. Based on the framebuffer technique, this work proposes a graphical HMI mechanism for intelligent in-vehicle system, and then a lightweight GUI (Graphical User Interface) system based on our Hive operating system, which is called HiveGUI, is implemented upon embedded ARM platforms. The extensive measurement results show that the framebuffer-based HiveGUI system usually consumes very few memory resources (i.e., less than 50M) and low CPU occupancy (i.e., less than 8%) in our self-developed intelligent in-vehicle system, and thus can offer good experience for automobile users.

Objective: To compare the irradiation volume, short-term and long-term efficacy of conventional radiotherapy (CR), three-dimensional conformal radiotherapy (3D-CRT), and indensity modulated radiotherapy (IMRT) in the treatment of esophageal cancer. Methods: A retrospective analysis method was adopted. The patients were divided into CR group (n=42), 3D-CRT group (n=45), and IMRT group (n=40). A follow-up visit was paid to collect the short-term and long-term efficacy, and the occurrence of adverse reactions. The gross tumor voluem (GTV), clinical target volume (CTV), planning target volume (PTV), and irradiation volume of organs (bilateral lungs, spinal cord, and heart) at risk (OAR) in the three groups were compared. Results: It was found by target volume comparison that the mean values of GTV, CTV, and PTV in the three groups were significantly increased (P0.05). The occurrence rate of adverse reactions in 3D-CRT group and IMRT group was significantly lower than that in CR group (P0.05). The difference of 1-year survival rate among the three groups was not statistically significant (P=0.144), but 3-year and 5-year survival rates in 3D-CRT group and IMRT group were significantly higher than those in CR group (P

Green's function is derived for the bending problem of an infinite thin plate with an elliptic hole under a bending heat source. Then the interaction problem between an elliptic hole and a crack in a thin plate under uniform bending heat flux is analyzed. First, the complex variable method is developed for the thermoelastic problem of bending. Then an exact solution in explicit form is derived for the Green's function by using the complex variable method. Distributions of temperature moment, heat flux moments, bending moments along the hole edge are shown in figures. For solving the interaction problem, a solution for an infinite thin plate with an adiabatic elliptic hole under uniform bending heat flux, and two Green's functions of the plate under a bending heat source couple and a bending dislocation are given. The interaction problem then reduces into singular integral equations using the Green's functions and the principle of superposition. After the equations are solved numerically, the momen...

Lung cancer ranks first in incidence and mortality in China. Surgery is the primary method to cure cancer, but only 20–30% of patients are eligible for curative resection. In recent years, in addition to surgery, other local therapies have been developed for patients with numerous localized primary and metastatic pulmonary tumors, including stereotactic body radiation therapy and thermal ablative therapies through percutaneously inserted applicators. Percutaneous thermal ablation of pulmonary tumors is minimally invasive, conformal, repeatable, feasible, cheap, has a shorter recovery time, and offers reduced morbidity and mortality. Radiofrequency ablation (RFA), the most commonly used thermal ablation technique, has a reported 80–90% rate of complete ablation, with the best results obtained in tumors < 3 cm in diameter. Because the clinical efficacy of RFA of pulmonary tumors has not yet been determined, this clinical guideline describes the techniques used in the treatment of localized primary and metastatic pulmonary tumors in nonsurgical candidates, including mechanism of action, devices, indications, techniques, potential complications, clinical outcomes, post‐ablation surveillance, and use in combination with other therapies. In the future, the role of RFA in the treatment of localized pulmonary tumors should ultimately be determined by evidence from prospective randomized controlled trials comparing sublobar resection or stereotactic body radiation therapy.