Title :
An Enhancement Method for Small Brain Metastases in T1w MRI
Author :
Liu Xing-Sheng ; Nie Sheng-dong ; Sun Xi-wen
Author_Institution :
Sch. of Med. Instrum. & Food Eng., Univ. of Shanghai for Sci. & Technol., Shanghai, China
Abstract :
Brain metastases are becoming an increasingly important cause of mortality among metastatic cancers, which accounts for over half of brain tumors. Early detection of brain metastases could have a significant impact on treatment outcomes and therefore essentially circumvent the spread of such tumors. In this work, a computerized image enhancement algorithm has been exploited to the benefit of improving detection of brain metastases. The algorithm first applied a clustering algorithm over each image pixel and then carried out the histogram normalization according to the parameters achieved by the clustering algorithm. Experimental results demonstrated that the contrast between BM and surrounding tissues was enhanced significantly by the proposed algorithm.
Keywords :
biomedical MRI; brain; cancer; image enhancement; medical image processing; tumours; T1w MRI; brain tumors; clustering algorithm; computerized image enhancement; histogram normalization; metastatic cancers; mortality; patient treatment; small brain metastases; Biomedical imaging; Cancer; Clustering algorithms; Gray-scale; High-resolution imaging; Histograms; Lesions; Magnetic resonance imaging; Metastasis; Neoplasms; MRI; brain metastases; nonlinear transformation;
Conference_Titel :
Fuzzy Systems and Knowledge Discovery, 2009. FSKD '09. Sixth International Conference on
Conference_Location :
Tianjin
Print_ISBN :
978-0-7695-3735-1
DOI :
10.1109/FSKD.2009.256