Artificial neural network-statistical approach for PET volume analysis and classification

Copyright © 2012 The Authors. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.This article has been made available through the Brunel Open Access Publishing Fund.The increasing number of imaging studies and the prevailing application of positron emission tomography (PET) in clinical oncology have led to a real need for efficient PET volume handling and the development of new volume analysis approaches to aid the clinicians in the clinical diagnosis, planning of treatment, and assessment of response to therapy. A novel automated system for oncological PET volume analysis is proposed in this work. The proposed intelligent system deploys two types of artificial neural networks (ANNs) for classifying PET volumes. The first methodology is a competitive neural network (CNN), whereas the second one is based on learning vector quantisation neural network (LVQNN). Furthermore, Bayesian information criterion (BIC) is used in this system to assess the optimal number of classes for each PET data set and assist the ANN blocks to achieve accurate analysis by providing the best number of classes. The system evaluation was carried out using experimental phantom studies (NEMA IEC image quality body phantom), simulated PET studies using the Zubal phantom, and clinical studies representative of nonsmall cell lung cancer and pharyngolaryngeal squamous cell carcinoma. The proposed analysis methodology of clinical oncological PET data has shown promising results and can successfully classify and quantify malignant lesions.This study was supported by the Swiss National Science Foundation under Grant SNSF 31003A-125246, Geneva Cancer League, and the Indo Swiss Joint Research Programme ISJRP 138866. This article is made available through the Brunel Open Access Publishing Fund

Rapid chromosome territory relocation by nuclear motor activity in response to serum removal in primary human fibroblasts

This article has been made available through the Brunel Open Access Publishing Fund.Background: Radial chromosome positioning in interphase nuclei is nonrandom and can alter according to developmental, differentiation, proliferation, or disease status. However, it is not yet clear when and how chromosome repositioning is elicited. Results: By investigating the positioning of all human chromosomes in primary fibroblasts that have left the proliferative cell cycle, we have demonstrated that in cells made quiescent by reversible growth arrest, chromosome positioning is altered considerably. We found that with the removal of serum from the culture medium, chromosome repositioning took less than 15 minutes, required energy and was inhibited by drugs affecting the polymerization of myosin and actin. We also observed that when cells became quiescent, the nuclear distribution of nuclear myosin 1ß was dramatically different from that in proliferating cells. If we suppressed the expression of nuclear myosin 1ß by using RNA-interference procedures, the movement of chromosomes after 15 minutes in low serum was inhibited. When high serum was restored to the serum-starved cultures, chromosome repositioning was evident only after 24 to 36 hours, and this coincided with a return to a proliferating distribution of nuclear myosin 1ß. Conclusions: These findings demonstrate that genome organization in interphase nuclei is altered considerably when cells leave the proliferative cell cycle and that repositioning of chromosomes relies on efficient functioning of an active nuclear motor complex that contains nuclear myosin 1ß.Brunel Open Access Publishing Fun

A committee machine gas identification system based on dynamically reconfigurable FPGA

This paper proposes a gas identification system based on the committee machine (CM) classifier, which combines various gas identification algorithms, to obtain a unified decision with improved accuracy. The CM combines five different classifiers: K nearest neighbors (KNNs), multilayer perceptron (MLP), radial basis function (RBF), Gaussian mixture model (GMM), and probabilistic principal component analysis (PPCA). Experiments on real sensors' data proved the effectiveness of our system with an improved accuracy over individual classifiers. Due to the computationally intensive nature of CM, its implementation requires significant hardware resources. In order to overcome this problem, we propose a novel time multiplexing hardware implementation using a dynamically reconfigurable field programmable gate array (FPGA) platform. The processing is divided into three stages: sampling and preprocessing, pattern recognition, and decision stage. Dynamically reconfigurable FPGA technique is used to implement the system in a sequential manner, thus using limited hardware resources of the FPGA chip. The system is successfully tested for combustible gas identification application using our in-house tin-oxide gas sensors

Statistical Inference of Weibull Extension Distribution under Imprecise Data

In this paper, we present the maximum likelihood (ML) and Bayes estimation of the unknown parameters, the reliability and hazard functions of the Weibull extension distribution based on progressively Type-II censoring scheme from fuzzy lifetime data. For the computation of Bayes estimates, we proposed using Tierney-Kadane’s approximation under square error and LINEX loss functions. The performance of the maximum likelihood and Bayes estimators compared in terms of their mean squared errors (MSEs) through the simulation study. The results indicated that MSEs based on Tierney-Kadane’s approximation are less than based on the ML method. Finally, to demonstrate the efficiency of the proposed methods, two real data sets are analyzed

Waste management and material recycle as a potential of sustainable building envelope for low income housing

Energy crisis and pollution are two main challenges that hinder sustainable development in Egypt. Electricity represents the major part of Egypt energy; however, the Egyptian electricity consumption is increasing much faster than capacity expansions which causes electrical blackout. Egypt’s electricity prices began to rise starting July 2015 as part of a plan to reduce the government subsistence on electricity and force people to rationalize the consumption. Residential buildings are representing 40% of the total energy consumption, in Egypt. This is mainly due to a poor design of buildings, with no concern to neither materials used nor building tightness. This results in high cold bridges that increase the heat transfer from the outside to the inside of building spaces leading to high internal discomfort. Concomitantly, impacting the increase of energy consumption in cooling and heating today in most Egyptian buildings. This paper is part of a multiphase experimental research work that represents an empirical comparative study of different thermal walls’ created from recyclable materials. The results would be analyzed in details, developed, and evaluated in terms of; technical, economic and environmental aspects and conditions. As a result of this study; the walls of such economical homes will be able to resist heat transfer with lowest possible cost and consume less energy

Using thermochromism to simulate blood oxygenation in extracorporeal membrane oxygenation

Introduction: Extracorporeal membrane oxygenation (ECMO) training programs employ real ECMO components, causing them to be extremely expensive while offering little realism in terms of blood oxygenation and pressure. To overcome those limitations, we are developing a standalone modular ECMO simulator that reproduces ECMO’s visual, audio and haptic cues using affordable mechanisms. We present a central component of this simulator, capable of visually reproducing blood oxygenation color change using thermochromism. Methods: Our simulated ECMO circuit consists of two physically distant modules, responsible for adding and withdrawing heat from a thermochromic fluid. This manipulation of heat creates a temperature difference between the fluid in the drainage line and the fluid in the return line of the circuit and, hence, a color difference. Results: Thermochromic ink mixed with concentrated dyes was used to create a recipe for a realistic and affordable blood-colored fluid. The implemented “ECMO circuit” reproduced blood’s oxygenation and deoxygenation color difference or lack thereof. The heat control circuit costs 300 USD to build and the thermochromic fluid costs 40 USD/L. During a ten-hour in situ demonstration, nineteen ECMO specialists rated the fidelity of the oxygenated and deoxygenated “blood” and the color contrast between them as highly realistic. Conclusions: Using low-cost yet high-fidelity simulation mechanisms, we implemented the central subsystem of our modular ECMO simulator, which creates the look and feel of an ECMO circuit without using an actual one.Peer reviewedFinal Accepted Versio

Matching pursuit-based compressive sensing in a wearable biomedical accelerometer fall diagnosis device

There is a significant high fall risk population, where individuals are susceptible to frequent falls and obtaining significant injury, where quick medical response and fall information are critical to providing efficient aid. This article presents an evaluation of compressive sensing techniques in an accelerometer-based intelligent fall detection system modelled on a wearable Shimmer biomedical embedded computing device with Matlab. The presented fall detection system utilises a database of fall and activities of daily living signals evaluated with discrete wavelet transforms and principal component analysis to obtain binary tree classifiers for fall evaluation. 14 test subjects undertook various fall and activities of daily living experiments with a Shimmer device to generate data for principal component analysis-based fall classifiers and evaluate the proposed fall analysis system. The presented system obtains highly accurate fall detection results, demonstrating significant advantages in comparison with the thresholding method presented. Additionally, the presented approach offers advantageous fall diagnostic information. Furthermore, transmitted data accounts for over 80% battery current usage of the Shimmer device, hence it is critical the acceleration data is reduced to increase transmission efficiency and in-turn improve battery usage performance. Various Matching pursuit-based compressive sensing techniques have been utilised to significantly reduce acceleration information required for transmission.Scopu