Automatic organ validation of b-mode ultrasound images for transmission to cloud

Miniaturization in size of Medical ultrasound scanning machine made it to use in point of care applications. Lack of sonographers and their unwillingness to work in rural areas limit the benefits of ultrasound system in rural healthcare. Diagnosis of patients through ultrasound is done by visualizing the ultrasound scanned images of organs. Diagnosis through telemedicine involves transmitting of ultrasound images from rural locations to cloud, where sonographer can remotely access the ultrasound data from cloud and generate the report, thus reducing the geographical separation between patients and doctors. Due to lack of adequate sonographers, ultrasound scanning in remote areas is operated by semi-skilled clinicians. Most of the images generated by semi-skilled clinicians are not useful for diagnosis. Transmitting all these images increases the data in cloud, drains the battery of portable ultrasound machine and increases latency in medication. This paper provides automatic B-mode ultrasound image validation based on organ information present in the image for diagnosis, thus avoiding transmission of invalid images to cloud. Linear kernel SVM classifier trained with first order statistic features of image with/without organs is used to classify the images into valid and invalid for diagnosis. The algorithm resulted with a recognition efficiency of 94.2% in classifying the ultrasound images

Hardware-software co-design of AES on FPGA

This paper presents a compact hardware-software co-design of Advanced Encryption Standard (AES) on the field programmable gate arrays (FPGA) designed for low-cost embedded systems. The design uses MicroBlaze, a soft-core processor from Xilinx. The computationally intensive operations of the AES are implemented in hardware for better speed. The sub-byte calculation is designed with the help of the processor carrying out the calculations using hardware blocks implemented using FPGA. By incorporating the processor in the AES design, the total number of slices required to implement the AES algorithm on FPGA is proved to be reduced. The entire AES system design is validated using 460 slices in Spartan-3E XC3S500E, which is one of the low-cost FPGA

Fast Region of Interest detection for fetal genital organs in B-mode ultrasound images

Genital organ detection of fetus in B-mode ultrasound images has a considerable significance. It is useful to know any malformations present in the genital organs and also to determine the sex of the fetus. In this paper we propose a Feature from Accelerated Segment Test (FAST) technique for approximate detection of fetal genitals in ultrasound images. FAST algorithm is capable of producing the corner points at a higher speed which falls on the fetal genital organs. A window of size 60×60 pixels being corner point as a center is considered as Region of Interest (ROI), where genital organ of fetus is anticipated. The efficiency of the algorithm is calculated as the ratio of number of images where corner points are placed on the fetus genital organ to the total number of images tested. FAST algorithm is robust to speckles present in the image, machine independent, fast and also computationally less intensive to implement in real time with an efficiency of 96.7%

A study on non-destructive method for detecting Toxin in pepper using Neural networks

Mycotoxin contamination in certain agricultural systems have been a serious concern for human and animal health. Mycotoxins are toxic substances produced mostly as secondary metabolites by fungi that grow on seeds and feed in the field, or in storage. The food-borne Mycotoxins likely to be of greatest significance for human health in tropical developing countries are Aflatoxins and Fumonisins. Chili pepper is also prone to Aflatoxin contamination during harvesting, production and storage periods.Various methods used for detection of Mycotoxins give accurate results, but they are slow, expensive and destructive. Destructive method is testing a material that degrades the sample under investigation. Whereas, non-destructive testing will, after testing, allow the part to be used for its intended purpose. Ultrasonic methods, Multispectral image processing methods, Terahertz methods, X-ray and Thermography have been very popular in nondestructive testing and characterization of materials and health monitoring. Image processing methods are used to improve the visual quality of the pictures and to extract useful information from them. In this proposed work, the chili pepper samples will be collected, and the X-ray, multispectral images of the samples will be processed using image processing methods. The term "Computational Intelligence" referred as simulation of human intelligence on computers. It is also called as "Artificial Intelligence" (AI) approach. The techniques used in AI approach are Neural network, Fuzzy logic and evolutionary computation. Finally, the computational intelligence method will be used in addition to image processing to provide best, high performance and accurate results for detecting the Mycotoxin level in the samples collected.Comment: 11 pages,1 figure; International Journal of Artificial Intelligence & Applications (IJAIA), Vol.3, No.4, July 201

Computer-Assisted Algorithms for Ultrasound Imaging Systems

Ultrasound imaging works on the principle of transmitting ultrasound waves into the body and reconstructs the images of internal organs based on the strength of the echoes. Ultrasound imaging is considered to be safer, economical and can image the organs in real-time, which makes it widely used diagnostic imaging modality in health-care. Ultrasound imaging covers the broad spectrum of medical diagnostics; these include diagnosis of kidney, liver, pancreas, fetal monitoring, etc. Currently, the diagnosis through ultrasound scanning is clinic-centered, and the patients who are in need of ultrasound scanning has to visit the hospitals for getting the diagnosis. The services of an ultrasound system are constrained to hospitals and did not translate to its potential in remote health-care and point-of-care diagnostics due to its high form factor, shortage of sonographers, low signal to noise ratio, high diagnostic subjectivity, etc. In this thesis, we address these issues with an objective of making ultrasound imaging more reliable to use in point-of-care and remote health-care applications. To achieve the goal, we propose (i) computer-assisted algorithms to improve diagnostic accuracy and assist semi-skilled persons in scanning, (ii) speckle suppression algorithms to improve the diagnostic quality of ultrasound image, (iii) a reliable telesonography framework to address the shortage of sonographers, and (iv) a programmable portable ultrasound scanner to operate in point-of-care and remote health-care applications

Effect of Relay Nodes on End-To-End Delay in Multi-Hop Wireless Ad-Hoc Networks

Channel access delay in a wireless adhoc network is the major source of delay while considering the total end to-end delay. Channel access delays experienced by different relay nodes are different in multi-hop adhoc network scenario. These delays in multi-hop network are analysed in the literature assuming channel access delays are independent and are of same magnitude at all the nodes in the network. In this work, the end to-end delay in a multi-hop adhoc network is analysed taking into account the silent relay nodes. Along with silent relay node effect, Channel access probability (p), transmission radius (r) analogous to transmit power, network throughput and density of nodes arête other factors considered for the end-to-end delay analysis. Effect of network parameters along with silent relay nodes on end-to-end delay is found to be considerably high compared to the previous literature results. Given a bound on end-to-end delay with percentage of silent relay nodes, throughput, node density requirements for a multi-hop adhoc network, optimal ranges of transmission radius and channel access probability can be obtained from the proposed analysis. End-to-end delay increases with silent relay nodes along with transmission radius(r), channel access probability(p), node density and throughput. It is clear from the analysis, that the effect of silent relay nodes on end to-end delay cannot be ignored to maintain certain Quality of service (QoS) metrics for the multi-hop wireless adhoc networ

Effect of relay nodes and transmit power on end-to-end delay in multi-hop wireless ad hoc networks

Channel access delay in a wireless multi-hop ad hoc network is the major source of delay while considering end-to-end delay. In this work, end-to-end delay is analysed considering silent relay nodes and effect of network parameters like node density and throughput. Given network parameter requirements and bound on end-to-end delay, optimal ranges of transmission radius and channel access probability can be obtained from the proposed analysis. Effect of silent relay nodes must be considered to maintain quality of service (QoS) metrics. Transmission power adaptability to reduce end-to-end delay is analysed considering the interference model. Increase in transmission power is not reducing end-to-end delay linearly. Simulation results show that increase in end-to-end delay due to channel access probability and throughput is onsiderably higher than node density. Also given the network parameters, end-to-end delay can be minimised only up to certain value irrespective of increase in transmit power

FLAVONOID CONTENT AND ANTIBACTERIAL ACTIVITY OF ALBIZIA JULIBRISSIN. DURAZZ LEAF, STEM AND FLOWER EXTRACTS AGAINST CLINICALLY ISOLATED BACTERIAL PATHOGENS

Objective: To test the antibacterial efficacy of leaf, stem, and flower extracts of Albizia julibrissin against bacterial pathogens. Methods: Extraction of active metabolites was carried out by using six different solvents, and total flavonoid content in each extract was determined by Aluminium chloride method. To determine the antibacterial activity of extracts, disc diffusion method and tube dilution method were carried out. Zone of inhibition and Minimum inhibitory Concentration (MIC) were calculated. Results: Methanolic extracts of leaf samples of A. julibrissin showed highest extractive value (5.14g/100g) and total flavonoid content (35.14mg/g). In overall leaf extracts of A. julibrissin showed maximum zone of inhibition towards P. vulgaris (10.1 mm*) and least susceptible microorganism is S. typhi (3.5 mm*). Stem and flower extracts inhibited bacterial growth only at higher concentrations (MIC, 160-215 and 65-180µg/ml respectively). Conclusion: Apart from the energy crop, based on the results and value-added compounds present in A. julibrissin, it may be considered as antibacterial agent in future