DocumentCode
631540
Title
Data mining supported analysis of medical atomic force microscopy images
Author
Hutterer, Stephan ; Mayr, Simon ; Zauner, Gunther ; Silye, Rene ; Schilcher, Kurt
Author_Institution
Sch. of Eng. & Environ. Sci., Univ. of Appl. Sci. Upper Austria, Wels, Austria
fYear
2013
fDate
16-19 April 2013
Firstpage
99
Lastpage
104
Abstract
Taking a look at actual developments in the field of bioinformatics, computer support in different fields of medicine and biology is an increasing field of interest. Especially for recognition and classification of various kinds of diseases, researchers already identified the usage of data mining techniques as supporting tool for computer supported analysis and diagnosis. In order to build such tools, highly accurate and machine-readable data is needed. Therefore, atomic force microscopy (AFM) is shown within this paper as measurement technology, that provides true 3-D data of any tissue and thus is able to build the fundament for further computational processing steps. Within two practical examples dealing with brain tumor tissue on the one hand and myocardial muscle tissue on the other hand, data mining supported analysis of AFM images will be demonstrated. The combination of data mining techniques with AFM measurements at nanoscale therefore forms a promising fundament for future computer enabled support systems in medicine and biology.
Keywords
atomic force microscopy; bioinformatics; biomedical optical imaging; brain; computer aided analysis; data mining; diseases; image classification; medical image processing; muscle; pattern recognition; tumours; AFM image; bioinformatics; biology; brain tumor tissue; computational processing step; computer enabled support system; computer supported analysis; computer supported diagnosis; data mining supported analysis; data mining technique; disease classification; disease recognition; machine-readable data; measurement technology; medical atomic force microscopy image; medicine; myocardial muscle tissue; true tissue 3-D data; Accuracy; Algorithm design and analysis; Feature extraction; Microscopy; Muscles; Tumors; Vectors;
fLanguage
English
Publisher
ieee
Conference_Titel
Computational Intelligence in Healthcare and e-health (CICARE), 2013 IEEE Symposium on
Conference_Location
Singapore
Print_ISBN
978-1-4673-5882-8
Type
conf
DOI
10.1109/CICARE.2013.6583076
Filename
6583076
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