Title :
A novel method for mass spectrometry data representation and analysis
Author :
Alipoor, Mohammad ; Haddadnia, Javad
Author_Institution :
Eng. Dept., Tarbiat Moallem Univ. of Sabzevar, Sabzevar, Iran
Abstract :
In this paper a novel representation/analysis method on high throughput SELDI-TOF mass-spectroscopy data is developed. To avoid complexity of conventional methods, mass spectrum is converted to an intensity image and then image processing techniques is implemented to solve the cancer classification problem. The proposed system benefits a thoroughly novel and efficient idea to design an image-based pattern recognition system for cancer classification. The system is successfully validated using a well-known ovarian cancer proteomic dataset. Results of applying the method are comparable to state of the art methods in proteomic pattern recognition.
Keywords :
cancer; data mining; image classification; image recognition; medical image processing; proteomics; time of flight mass spectroscopy; cancer classification; cancer classification problem; data analysis; data mining; data representation; high throughput SELDI-TOF mass-spectroscopy; image processing techniques; image-based pattern recognition system; mass spectrometry; ovarian cancer proteomic dataset; proteomic pattern recognition; Biology; Biomedical imaging; Discrete wavelet transforms; Image recognition; cancer classification; image proccessing; mass spectroscopy (MS); mass spectrum intensity image (MSII);
Conference_Titel :
Biomedical Engineering (ICBME), 2010 17th Iranian Conference of
Conference_Location :
Isfahan
Print_ISBN :
978-1-4244-7483-7
DOI :
10.1109/ICBME.2010.5705024
