This paper studies the problem of clinical MRI analysis in the field of lumbar intervertebral disk herniation diagnosis. It discusses the possibility of assisting radiologists in reading the patients MRI images by constructing a 3D model for the region of interest using simple computer vision methods. We use axial MRI slices of the lumbar area. The proposed framework works with a very small number of MRI slices and goes through three main stages. Namely, the region of interest extraction and enhancement, inter-slice interpolation, and 3D model construction. We use the Marching Cubes algorithm to construct the 3D model of the the region of interest. The validation of our 3D models is based on a radiologist’s analysis of the models. We tested the proposed 3D model construction on 83 cases and We have a 95% accuracy according to the radiologist evaluation. This study shows that 3D model construction can greatly ease the task of the radiologist which enhances the working experience. This leads eventually to more accurate and easy diagnosis process.

/pdf/lumbar-disk-3d-modeling-from-limited-number-of-mri-axial-1eloj2e7b1.pdf

Lumbar disk 3D modeling from limited number of MRI axial slices

Multi-criteria decision making (MCDM) algorithms play an important role in ensuring quality of service in an integrated HetNets (Heterogeneous Networks). The primary objective of this paper is to develop a multi-criteria vertical handoff decision algorithm (VHDA) for best access network selection in an integrated Wireless Local Area Network (WLAN)/ Universal Mobile Telecommunications System (UMTS)/ Worldwide Interoperability for Microwave Access (WiMAX) system. The proposed design consists of two parts, the first part is the evaluation of an Analytic Hierarchy Process (AHP) to decide the relative weights of handoff decision criteria and the second part computes the final score of the weights to rank network alternatives using Simple Additive Weighting (SAW). SAW ranks the network alternatives in a faster and simpler manner than AHP. The AHP-SAW mathematical model has been designed, evaluated and simulated for streaming video type of traffic. For other traffic type, such as conversational, background and interactive, only simulation results have been discussed and presented in brief. Simulation results reveal that the hierarchical modelling and computing provides optimum solution for access network selection in an integrated environment as obtained results prove to be an acceptable solution to what could be expected in real life scenarios.

Multi-criteria Vertical Handoff Decision Algorithm Using Hierarchy Modeling and Additive Weighting in an Integrated WLAN/WiMAX/UMTS Environment– A Case Study

A novel hybrid approach for the identification of brain regions using magnetic resonance images accountable for brain tumor is presented in this paper. Classification of medical images is substantial in both clinical and research areas. Magnetic resonance imaging (MRI) modality outperforms towards diagnosing brain abnormalities like brain tumor, multiple sclerosis, hemorrhage, and many more. The primary objective of this work is to propose a three-dimensional (3D) novel brain tumor classification model using MRI images with both micro- and macroscale textures designed to differentiate the MRI of brain under two classes of lesion, benign and malignant. The design approach was initially preprocessed using 3D Gaussian filter. Based on VOI (volume of interest) of the image, features were extracted using 3D volumetric Square Centroid Lines Gray Level Distribution Method (SCLGM) along with 3D run length and cooccurrence matrix. The optimal features are selected using the proposed refined gravitational search algorithm (RGSA). Support vector machines, over backpropagation network, and k-nearest neighbor are used to evaluate the goodness of classifier approach. The preliminary evaluation of the system is performed using 320 real-time brain MRI images. The system is trained and tested by using a leave-one-case-out method. The performance of the classifier is tested using the receiver operating characteristic curve of 0.986 (±002). The experimental results demonstrate the systematic and efficient feature extraction and feature selection algorithm to the performance of state-of-the-art feature classification methods.

/pdf/hybrid-rgsa-and-support-vector-machine-framework-for-three-2fmuggfkn0.pdf

Hybrid RGSA and Support Vector Machine Framework for Three-Dimensional Magnetic Resonance Brain Tumor Classification.

Next-generation wireless network is striving to integrate different wireless access networks leading to a new concept called vertical handoff. Vertical handoff occurs when mobile node moves between different technology networks. Designing intelligent vertical handoff algorithm is a most critical challenge for next generation network. Towards this as a first step, IEEE 802.21 working group proposed a standard called Media Independent Handover (MIH). The IEEE 802.21 MIH is focused on handover facilitation between different wireless networks in heterogeneous environment regardless of the type of medium. In order to simulate MIH standard, National Institute of Standards and Technology (NIST) developed a add-on module compatible with ns2 version 2.29. In this paper we have presented a simulation result of vertical handoff between WiFi and WiMAX networks using IEEE 802.21 MIH standard. The simulation is carried out using ns2 simulator with NIST’s add-on module for IEEE 802.21 MIH standard. Performance of IEEE 802.21 MIH standard is analyzed in terms of throughput, handoff latency, packet drop and end to end delay. General Terms 4G Network, Vertical handoff, Media Independent Handover, ns2 simulator, etc.

/pdf/simulation-and-performance-analysis-of-vertical-handoff-1izefsq0t7.pdf

Simulation and Performance analysis of Vertical Handoff between WiFi and WiMAX using Media Independent Handover Services

Seamless Handover between networks in heterogeneous environment is essential to guarantee end-to-end QoS for mobile users. A key requirement is the ability to select the next best network. Currently, the implementation of the IEEE 802.21 standard by National Institute of Standards and Technology (NIST) considers only the signal strength as a parameter to determine the best network. In this paper, we propose including additional parameters such as available bandwidth, mobile node speed and type of network during selecting a new network to improve the QoS for mobile user's application. The results of the experiments that we performed using Network Simulator show that there is a need for a new framework taking into account these parameters to guide network selection process during handover and to provide mobile users with QoS guarantee.

/pdf/smart-network-selection-and-packet-loss-improvement-during-1rp8itrq5w.pdf

Smart Network Selection and Packet Loss Improvement During Handover in Heterogeneous Environment

Efficiency of seamless handover in heterogeneous networks depends on the factors such as handoff delay, number of handovers and packet drop during handovers. Improving the efficiency of seamless handover in multiple mobile broadband access technologies depends on selecting suitable handover time and interface, is the challenging issue in next generation wireless networks. Selecting suitable time and interface for seamless handover depends on the factors like signal strength, available bandwidth, the price of the link, the user mobility and power of the battery etc. IEEE 802.21 provided a framework which facilitates seamless handover in heterogeneous wireless networks. National Institute of Standards and Technology (NIST) provided the IEEE 802.21 add-on modules for network simulator-2, which uses only signal strength and interface type for seamless handover. This paper proposed and implemented an algorithm using NIST's, IEEE 802.21 add-on module which uses available bandwidth, coverage radius, user mobility and power of the battery along with signal strength for improving the efficiency of seamless handover between WiFi and WiMax, heterogeneous wireless networks. Simulation results using ns-2.29 with Modified NIST's add-on module demonstrated reduction in packet drop and number of handovers with the increase speed of a mobile node.

/pdf/improvement-in-packet-drop-during-handover-between-wifi-and-49vb5yvsya.pdf

Improvement in Packet Drop during Handover between WiFi and WiMax

Three dimensional (3D) reconstruction of the tumor from medical images is an important operation in the medical field as it helps the radiologist in the diagnosis, surgical planning and biological research. Thus in this paper, we propose an effective and efficient approach to 3D reconstruction of brain tumor and estimation of its volume from a set of two dimensional (2D) cross sectional magnetic resonance (MR) images of the brain. In the first step, MR images are preprocessed to improve the quality of the image. Next, abnormal slices are identified based on histogram analysis and tumor on those slices is segmented using modified fuzzy c-means (MFCM) clustering algorithm. Next, the proposed enhanced shape based interpolation technique is applied to estimate the missing slices accurately and efficiently. Then, the surface mesh of the tumor is reconstructed by applying the marching cubes (MC) algorithm on a set of abnormal slices. The large number of triangles generated by the MC algorithm was reduced by our proposed mesh simplification algorithm to accelerate the rendering phase. Finally, rendering was performed by applying Phong lighting and shading model on the reconstructed mesh to add realism to the 3D model of the tumor. The volume of the tumor was also computed to assist the radiologist in estimating the stage of the cancer. All experiments were carried out on MR image datasets of brain tumor patients and satisfactory results were achieved. Thus, our proposed method can be incorporated into the computer aided diagnosis (CAD) system to assist the radiologist in finding the tumor location, volume and 3D information.

An Effective and Efficient Approach to 3D Reconstruction and Quantification of Brain Tumor on Magnetic Resonance Images

A wireless sensor network (WSN) consists of spatially distributed autonomous sensors to monitor physical or environmental conditions, such as temperature, sound, pressure, etc. and to cooperatively pass their data through the network to a main location. Energy efficiency is the important key for WSN. To lower the energy consumption, the network is divided into several clusters in cluster routing algorithm LEACH (Low Energy Adaptive Clustering Hierarchy). Even though clustering provides energy efficiency, but uneven load distribution still occurs in general. In this paper an approach is presented which divides the deployment region into sub-regions and thereby uniformly distributing the load among the sensor nodes. Different shapes are considered for dividing the deployment region into equal sub-regions. Keywords—wireless sensor network, energy efficiency, LEACH, load distribution

A Novel Approach to Uniformly Distribute the Load in Wireless Sensor Routing Protocol LEACH

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Papers

Improvement in Packet Drop during Handover between WiFi and WiMax

An Effective and Efficient Approach to 3D Reconstruction and Quantification of Brain Tumor on Magnetic Resonance Images

A Novel Approach to Uniformly Distribute the Load in Wireless Sensor Routing Protocol LEACH