المنشورات و المؤلفات
The paper presents a method for automatic segmentation of sputum cells color images, to develop an efficient algorithm for lung cancer diagnosis based on a Hopfield neural network. We formulate the segmentation problem as a minimization of an energy...
This paper presents a study of the sensitivity analysis of the artificial Hopfield Neural Network (HNN) when segmenting natural color images. The color distinction or vision system relies on two step process which, first classifies the different...
In this paper, we propose a methodology (in the form of a software package) for automatic extraction of the cancerous nuclei in lung pathological color images. We first segment the images using an unsupervised Hopfield artificial neural network...
The initial weight matrix to be used in the unsupervised hopfield neural network (HNN) image based classification or segmentation has a strong influence in the quality of the solution obtained after a specified time or iteration number given to the...
In this article, the authors propose a method for automatic diagnosis of liver cancer based on analysis of digitized color images of liver tissue obtained by needle biopsy. The approach is a combination of an unsupervised segmentation algorithm,...
Posterior capsule opacification (PCO) is the most common complication of cataract surgery, occurring in up to 50% of patients by 2–3 years after the operation [Spalton in Eye 13(Pt 3b):489–492, 1999]. This paper proposes a new approach for the...
This paper describes a method for an automatic extraction of lung regions from 3D-CT images using pure basic image processing techniques. This extraction process should be as much as possible accurate and reliable because its results will be used as...
In this paper, we present some contributions to improve a previous work's approach presented for the segmentation of magnetic resonance images of the human brain, based on the unsupervised Hopfield neural network. We formulate the segmentation...
An automatic Computer-Aided Diagnosis (CAD) system for early detection of lung cancer by analysis of chest 3D Computed Tomography (CT) images is proposed
in this paper. Our system differs from previous implementations of CAD systems in two major...
Presents contributions to improve a previously published approach for the segmentation of magnetic resonance images of the human brain, based on an unsupervised Hopfield neural network. The authors formulate the segmentation problem as the...
The Root Mean Square-Deviation (RMSD) or Root Mean Square Error (RMSE) is the frequently used measure of the difference between values predicted by a model or an estimator and the values actually observed from that which is being modelled or...