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
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;
Conference_Titel :
Computational Intelligence in Healthcare and e-health (CICARE), 2013 IEEE Symposium on
Conference_Location :
Singapore
Print_ISBN :
978-1-4673-5882-8
DOI :
10.1109/CICARE.2013.6583076