Odorant clustering based on molecular parameter-feature extraction and imaging analysis of olfactory bulb odor maps

2018 ◽  
Vol 255 ◽  
pp. 508-518 ◽  
Author(s):  
Liang Shang ◽  
Chuanjun Liu ◽  
Yoichi Tomiura ◽  
Kenshi Hayashi
Keyword(s):  
Feature Extraction ◽  
Olfactory Bulb ◽  
Molecular Parameter ◽  
Imaging Analysis

scholarly journals Prototype System to Detect Skin Cancer Through Images

2019 ◽  
pp. 42-51
Author(s):  
M. en C. José Luis Calderón Osorno ◽  
M. en C. Edmundo René Durán Camarillo ◽  
M. en C. Silvestre Ascencion Garcia Sanchez
Keyword(s):  
Neural Network ◽  
Artificial Neural Network ◽  
Feature Extraction ◽  
Digital Imaging ◽  
Prototype System ◽  
Spectroscopic Techniques ◽  
Activation Functions ◽  
Imaging Analysis ◽  
Diagnosis Of Cancer ◽  
Artificial Neural Network Ann

This paper proposes the development of a software that performs the pre-diagnosis of malignant melanoma, spincellular carcinoma and basal-cell carcinoma. The software is divided into five modules, these being: digital imaging, analysis and processing, storage, feature extraction and classification by means of an Artificial Neural Network (ANN). The results shown the performance of the software for two different combination of activation functions in the network. With the use of spectroscopic techniques for the acquisition of images and the combination of non-linear and linear activation functions in the ANN, the software shows an effectiveness greater than 80%, concluding that it can be an effective tool as an aid in the diagnosis of cancer of skin.

An Improved Quantitative Image Analyser

1977 ◽  
Vol 35 ◽  
pp. 226-227
Author(s):  
J.P. Fallon ◽  
P.J. Gregory ◽  
C.J. Taylor
Keyword(s):  
Feature Extraction ◽  
Quantitative Analysis ◽  
Frequency Content ◽  
General Sense ◽  
Physical Measurements ◽  
Quantitative Image ◽  
Image Analyser ◽  
Automatic Methods ◽  
Quantitative Results

Quantitative image analysis systems have been used for several years in research and quality control applications in various fields including metallurgy and medicine. The technique has been applied as an extension of subjective microscopy to problems requiring quantitative results and which are amenable to automatic methods of interpretation.Feature extraction. In the most general sense, a feature can be defined as a portion of the image which differs in some consistent way from the background. A feature may be characterized by the density difference between itself and the background, by an edge gradient, or by the spatial frequency content (texture) within its boundaries. The task of feature extraction includes recognition of features and encoding of the associated information for quantitative analysis.Quantitative Analysis. Quantitative analysis is the determination of one or more physical measurements of each feature. These measurements may be straightforward ones such as area, length, or perimeter, or more complex stereological measurements such as convex perimeter or Feret's diameter.

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