The use of the Hellwig's method for feature selection in the detection of myeloma bone destruction based on radiographic images

Omiotek, Zbigniew; Stepanchenko, Olga; Wójcik, Waldemar; Legieć, Wojciech; Szatkowska, Małgorzata

doi:10.1016/j.bbe.2018.11.008

Cited by 17 publications

(7 citation statements)

References 34 publications

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“…It seems that good results might be achieved by combining the effects of fractal analysis with the results of other methods for texture feature extraction, for example, autoregression model, wavelet transform and statistical methods (greyscale histogram, co-occurrence matrix, higher-order statistics, run-length matrix and gradient matrix). 45,46 The results obtained are difficult to compare with the ones reported by other authors, because (as noted in 'Introduction') there are no known publications presenting the classification results aimed at the detection of osteoporosis, where the fractal analysis of the spine CT images on the thoraco-lumbar region would be used to extract textural features. The advantages of the presented method include the fact that it is non-invasive and offers an acceptable (from a medical point of view) accuracy of recognising the cases belonging to particular categories.…”

Section: Discussionmentioning

confidence: 94%

Fractal analysis of the computed tomography images of vertebrae on the thoraco-lumbar region in diagnosing osteoporotic bone damage

Omiotek

Dzierżak

Uhlig

2019

Proc Inst Mech Eng H

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Fractal analysis was used in the study to determine a set of feature descriptors which could be applied in the process of diagnosing bone damage caused by osteoporosis. The subject of the research involved the computed tomography images of vertebrae on the thoraco-lumbar region. The data set contained the images of healthy patients and patients diagnosed with osteoporosis. On the basis of fractal analysis and feature selection by linear stepwise regression, three descriptors were obtained. They were two fractal dimensions calculated with the variation method (transect – first differences and filter 1 estimators) and one fractal lacunarity calculated by means of the box counting method. The first two descriptors were obtained as a result of the analysis of grey images, and the third was the result of analysis of binary images. The effectiveness of the descriptors was verified using six popular supervised classification methods: linear and quadratic discriminant analysis, naive Bayes classifier, decision tree, K-nearest neighbours and random forests. The best results were obtained using the K-nearest neighbours classifier; they were as follows: overall classification accuracy – 81%, classification sensitivity – 78%, classification specificity – 90%, positive predictive value – 90%, and negative predictive value – 77%. The results of the research showed that fractal analysis can be a useful tool to extract feature vector of spinal computed tomography images in the diagnosis of osteoporotic bone defects.

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Section: Discussionmentioning

confidence: 94%

Fractal analysis of the computed tomography images of vertebrae on the thoraco-lumbar region in diagnosing osteoporotic bone damage

Omiotek

Dzierżak

Uhlig

2019

Proc Inst Mech Eng H

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“…In [ 75 ], the authors extract image feature vectors based on computed radiography and obtain 279 image descriptors. Through the Hellwig method, they find the feature combination set of the overall index with the maximum information capacity.…”

Section: Methods Analysismentioning

confidence: 99%

A State-of-the-Art Review for Gastric Histopathology Image Analysis Approaches and Future Development

et al. 2021

BioMed Research International

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Gastric cancer is a common and deadly cancer in the world. The gold standard for the detection of gastric cancer is the histological examination by pathologists, where Gastric Histopathological Image Analysis (GHIA) contributes significant diagnostic information. The histopathological images of gastric cancer contain sufficient characterization information, which plays a crucial role in the diagnosis and treatment of gastric cancer. In order to improve the accuracy and objectivity of GHIA, Computer-Aided Diagnosis (CAD) has been widely used in histological image analysis of gastric cancer. In this review, the CAD technique on pathological images of gastric cancer is summarized. Firstly, the paper summarizes the image preprocessing methods, then introduces the methods of feature extraction, and then generalizes the existing segmentation and classification techniques. Finally, these techniques are systematically introduced and analyzed for the convenience of future researchers.

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“…In order to select variables that affect the consumer decision whether to install SM at home or not, correlation coefficients between individual variables were calculated. Because some variables show some degree of correlation, we used a method, described in Kamrat (2002); Omiotek et al (2019) to identify central variables of leading importance and subordinate (satellite, isolated) variables (i.e. variables that individually form clusters).…”

Section: Analysis Of Correlations Between Variables In Groups (Pearson Spearman Tau Kendall)mentioning

confidence: 99%

Perspectives of smart meters’ roll-out in India: An empirical analysis of consumers’ awareness and preferences

2020

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This papers focuses on the smart meters' roll-out in India -third largest economy, one of the developing countries with the fastest economic growth rate and third largest power producing nation. The Indian power system is weak and experiences severe problems and challenges that could be solved by means of the smart grid approach and broader implementation of smart meters (SM). Within this study, we focus on the consumers' preferences regarding SM. An empirical study has been conducted among Indian social media users, who are predicted to be potential early adopters or innovators in case of SM further market penetration. By dividing the respondents into a few market segments, the study highlights differences between consumers already having SM installed at their household, consumers in the process of installing SM, consumers who would like to have SM in the future, and consumers' preferences based on potential benefits and information availability. The study also outlines the profile of consumers who currently have SM installed in their household. Results show that tech-savviness of India's consumers, common access to the Internet for citizens, possession of smart phones by most of the population and ambitious goals of the Indian government, are a very productive mix for a nation wide roll-out of SM in India in the coming years.

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The use of the Hellwig's method for feature selection in the detection of myeloma bone destruction based on radiographic images

Cited by 17 publications

References 34 publications

Fractal analysis of the computed tomography images of vertebrae on the thoraco-lumbar region in diagnosing osteoporotic bone damage

Fractal analysis of the computed tomography images of vertebrae on the thoraco-lumbar region in diagnosing osteoporotic bone damage

A State-of-the-Art Review for Gastric Histopathology Image Analysis Approaches and Future Development

Perspectives of smart meters’ roll-out in India: An empirical analysis of consumers’ awareness and preferences

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