Automated and accurate classification of brain MRI is such important that leads us to present a new robust classification technique for analyzing magnetic response images. The proposed method consists of three stages, namely, feature extraction, dimensionality reduction, and classification. We use gray level co-occurrence matrix (GLCM) to extract features from brain MRI and for selecting the be...

In modern textile industry, Tissue online Automatic Inspection (TAI) is becoming an attractive alternative to Human Vision Inspection (HVI). HVI needs a high level of attention nevertheless leading to low performance in terms of tissue inspection. Based on the co-occurrence matrix and its statistical features, as an approach for defects textile identification in the digital image, TAI can poten...

INTRODUCTION The goals of this study were (i) to compare the prevalence of focal knee abnormalities, the mean cartilage T2 relaxation time, and the spatial distribution of cartilage magnetic resonance (MR) T2 relaxation times between subjects with and without risk factors for Osteoarthritis (OA), (ii) to determine the relationship between MR cartilage T2 parameters, age and cartilage morphology...

Traditional spectral classification of remote sensing data applied on per pixel basis ignores the potentially useful spatial information between the values of proximate pixels. Although spatial information extraction has been greatly explored, there have been limited attempts to enhance classification by combining spectral and spatial information. This improvement would arise from the hypothesi...


 Jerawat merupakan penyakit kulit yang tidak berbahaya, penderita jerawat umunya menyerang 85% usia antara 11 – 30 tahun. dapa memuat penderitanya merasa percaya diri pada penampilan dan membuat nyaman. Terdapat beberapa cara untuk menghilangkan salah satunya adalah dengan datang ke dokter kecantikan, namun kelemahan pengobatan konvensional cenderung mahal membutuhkan waktu cukup lama men...

This study used the second-order Gray Level Co-occurrence Matrix (GLCM) and pearl image classification using Artificial Neural Network (ANN). No previous research combines GLCM method with artificial neural networks in classification. The number of images this is 360 three labels, including 120 A images, AA AAA images. epochs were 10, 20, 30, 40, 50, 60, 70, 80. test results at epoch 10 got 80....

Breast cancer is one of the most common types among Iraqi women. MRI has been used in detection breast tumors for its efficient performance diagnosis process providing high accuracy. In this paper, image data from 89 patients were classified using GLCM and CNN feature extraction methods. Four models evaluated consisting GLCM, CNN, combined features based models. The statistical ANOVA selection ...