Fractal analysis for classification of breast lesions

2019 ◽  
Author(s):  
Laura Benita Alvarado Cruz ◽  
Maricela Delgadillo Herrera ◽  
Carina Toxqui-Quitl ◽  
Alfonso Padilla-Vivanco ◽  
Raul Castro Ortega ◽  
...  
Keyword(s):  
Fractal Analysis ◽  
Breast Lesions

scholarly journals An Automated Method for the Quantification and Fractal Analysis of Immunostaining

2004 ◽  
Vol 26 (3) ◽  
pp. 125-134
Author(s):  
Armin Gerger ◽  
Patrick Bergthaler ◽  
Josef Smolle
Keyword(s):  
Fractal Analysis ◽  
Quantitative Description ◽  
Fractal Dimensionality ◽  
Texture Features ◽  
Second Step ◽  
Digital Information ◽  
Automated Method ◽  
Reliable Classification ◽  
The One

Aims. In tissue counter analysis (TCA) digital images of complex histologic sections are dissected into elements of equal size and shape, and digital information comprising grey level, colour and texture features is calculated for each element. In this study we assessed the feasibility of TCA for the quantitative description of amount and also of distribution of immunostained material. Methods. In a first step, our system was trained for differentiating between background and tissue on the one hand and between immunopositive and so‐called other tissue on the other. In a second step, immunostained slides were automatically screened and the procedure was tested for the quantitative description of amount of cytokeratin (CK) and leukocyte common antigen (LCA) immunopositive structures. Additionally, fractal analysis was applied to all cases describing the architectural distribution of immunostained material. Results. The procedure yielded reproducible assessments of the relative amounts of immunopositive tissue components when the number and percentage of CK and LCA stained structures was assessed. Furthermore, a reliable classification of immunopositive patterns was found by means of fractal dimensionality. Conclusions. Tissue counter analysis combined with classification trees and fractal analysis is a fully automated and reproducible approach for the quantitative description in immunohistology.

Ultrasound RF Time Series for Classification of Breast Lesions

2015 ◽  
Vol 34 (2) ◽  
pp. 652-661 ◽  
Author(s):  
Nishant Uniyal ◽  
Hani Eskandari ◽  
Purang Abolmaesumi ◽  
Samira Sojoudi ◽  
Paula Gordon ◽  
...  
Keyword(s):  
Time Series ◽  
Breast Lesions

scholarly journals Automated classification of focal breast lesions according to S-detect: validation and role as a clinical and teaching tool

2018 ◽  
Vol 21 (2) ◽  
pp. 105-118 ◽  
Author(s):  
Mattia Di Segni ◽  
Valeria de Soccio ◽  
Vito Cantisani ◽  
Giacomo Bonito ◽  
Antonello Rubini ◽  
...  
Keyword(s):  
Teaching Tool ◽  
Breast Lesions ◽  
Automated Classification

scholarly journals Classification of breast lesions in ultrasonography using sparse logistic regression and morphology-based texture features

2018 ◽  
Vol 45 (9) ◽  
pp. 4112-4124 ◽  
Author(s):  
Hoda Nemat ◽  
Hamid Fehri ◽  
Nasrin Ahmadinejad ◽  
Alejandro F. Frangi ◽  
Ali Gooya
Keyword(s):  
Logistic Regression ◽  
Texture Features ◽  
Breast Lesions ◽  
Sparse Logistic Regression
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