scholarly journals Feature Extraction and Classification of Thorax X-Ray Image in the Assessment of Osteoporosis

2017 ◽  
Vol 4 (1) ◽  
Author(s):  
Riandini Riandini ◽  
Mera Kartika Delimayanti
Keyword(s):  
Feature Extraction ◽  
X Ray

scholarly journals Classification of Coronavirus Images using Shrunken Features

2020 ◽  
Author(s):  
Saban Ozturk ◽  
Umut Ozkaya ◽  
Mucahid Barstugan
Keyword(s):  
Feature Extraction ◽  
Feature Vector ◽  
Principal Component ◽  
Extraction Methods ◽  
X Ray ◽  
Effective Interventions ◽  
Long Duration ◽  
Clinical Diagnoses ◽  
Short Time

AbstractNecessary screenings must be performed to control the spread of the Corona Virus (COVID-19) in daily life and to make a preliminary diagnosis of suspicious cases. The long duration of pathological laboratory tests and the wrong test results led the researchers to focus on different fields. Fast and accurate diagnoses are essential for effective interventions with COVID-19. The information obtained by using X-ray and Computed Tomography (CT) images is vital in making clinical diagnoses. Therefore it was aimed to develop a machine learning method for the detection of viral epidemics by analyzing X-ray images. In this study, images belonging to 6 situations, including coronavirus images, are classified. Since the number of images in the dataset is deficient and unbalanced, it is more convenient to analyze these images with hand-crafted feature extraction methods. For this purpose, firstly, all the images in the dataset are extracted with the help of four feature extraction algorithms. These extracted features are combined in raw form. The unbalanced data problem is eliminated by producing feature vectors with the SMOTE algorithm. Finally, the feature vector is reduced in size by using a stacked auto-encoder and principal component analysis to remove interconnected features in the feature vector. According to the obtained results, it is seen that the proposed method has leveraging performance, especially in order to make the diagnosis of COVID-19 in a short time and effectively.

New feature extraction method for classification of agricultural products from x-ray images

1999 ◽  
Author(s):  
Ashit Talukder ◽  
David P. Casasent ◽  
Ha-Woon Lee ◽  
Pamela M. Keagy ◽  
Thomas F. Schatzki
Keyword(s):  
Feature Extraction ◽  
Extraction Method ◽  
Agricultural Products ◽  
X Ray ◽  
Feature Extraction Method ◽  
New Feature

scholarly journals Multi-Level of Feature Extraction and Classification for X-Ray Medical Image

2018 ◽  
Vol 10 (1) ◽  
pp. 154 ◽  
Author(s):  
Mohammed Muayad Abdulrazzaq ◽  
Imad FT Yaseen ◽  
SA Noah ◽  
Moayad A. Fadhil
Keyword(s):  
Feature Extraction ◽  
Medical Image ◽  
Medical Images ◽  
Image Features ◽  
X Ray ◽  
Extraction Algorithm ◽  
Semantic Concepts ◽  
Automatic Mechanism ◽  
High Level

There has been a rise in demand for digitized medical images over the last two decades. Medical images' pivotal role in surgical planning is also an essential source of information for diseases and as medical reference as well as for the purpose of research and training. Therefore, effective techniques for medical image retrieval and classification are required to provide accurate search through substantial amount of images in a timely manner. Given the amount of images that are required to deal with, it is a non-viable practice to manually annotate these medical images. Additionally, retrieving and indexing them with image visual feature cannot capture high level of semantic concepts, which are necessary for accurate retrieval and effective classification of medical images. Therefore, an automatic mechanism is required to address these limitations. Addressing this, this study formulated an effective classification for X-ray medical images using different feature extractions and classification techniques. Specifically, this study proposed pertinent feature extraction algorithm for X-ray medical images and determined machine learning methods for automatic X-ray medical image classification. This study also evaluated different image features (chiefly global, local, and combined) and classifiers. Consequently, the obtained results from this study improved results obtained from previous related studies.

Feature Extraction and Classification of COPD Chest X-ray Images

2020 ◽  
Vol 12 (6) ◽  
pp. 1
Author(s):  
A. Brintha Therese ◽  
P. Bhuvaneswari Samuel
Keyword(s):  
Feature Extraction ◽  
X Ray ◽  
Chest X Ray

scholarly journals Rapid classification of commercial teas according to their origin and type using elemental content with X-ray fluorescence (XRF) spectroscopy

2021 ◽  
Vol 4 ◽  
pp. 45-52
Author(s):  
Cia Min Lim ◽  
Manus Carey ◽  
Paul N. Williams ◽  
Anastasios Koidis
Keyword(s):  
Elemental Content ◽  
X Ray ◽  
Xrf Spectroscopy
Sign in / Sign up

Export Citation Format

Share Document