Title of the Paper: Comparison of Hopfield Neural Network and Fuzzy Clustering in Segmenting Sputum Color Images for Lung Cancer Diagnosis
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Authors: Rachid Sammouda and Fatma Taher
Abstract: The analysis of sputum taken from patients can be an extremely valuable technique for an early detection
diagnosis of lung cancer. There is a great need for an automated system which can provide accurate analysis of the
morphology of the sputum cells on a microscope slide, or diagnose their color digital image using special software.
In this work, we compare two unsupervised segmentation methods of sputum color images, a modified Hopfield Neural Network
(HNN), and a Fuzzy C-Mean (FCM) Clustering Algorithm. The segmentation results will be used as a base for a Computer Aided
Diagnosis (CAD) system for early detection of lung cancer. Both methods are designed to classify the image of N pixels
among M classes or regions. Due to intensity variations in background of the raw images, a pre-segmentation process is
developed to standardize the segmentation process. In this study, we have used 1000 sputum color images to test both methods.
Experimental evidence of the effectiveness and limitation of each method is reported.
Keywords: Hopfield Neural Network, Fuzzy Clustering, Segmentation, Sputum Color Images, Lung Cancer Diagnosis
Title of the Paper: Real Time Monitoring System for ECG Signal Using
Virtual Instrumentation
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Authors: Amit Kumar, Lillie Dewan, Mukhtiar Singh
Abstract: The paper introduces the designed aspects of the real time monitoring of the ECG signal on virtual
cardiograph. The designed system is consisting of four parts as below.
Data acquisition of ECG signal
Filtering of data logger
Representations of Acquired ECG signal on virtual graphs.
Making the data logger.
The 6013 E Analog card is used for the acquisition of ECG signal from ECG simulator and LabVIEW 7.0 professional
development tool is used to designed the system. The designed system is advantageous in automatic removal of noises
and filtration of acquired signal on virtual cardiographs.
Keywords: Data Acquisition, ECG, LabVIEW, Virtual instrumentation
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