Binary and Nonbinary Description of Hypointensity for Search and Retrieval of Brain MR Images
Devrim Unay, Xiojing C. Chen, Mujdat Cetin, Aytul Ercil, Radu Jasinschi, Ahmet Ekin
IS&T/SPIE Electronic Imaging, Multimedia Content Access: Algorithms and Systems III, San Jose, California, USA, January 2009
Diagnosis accuracy in the medical field, is mainly affected by either lack of suffcient understanding of some diseases or the inter/intra-observer variability of the diagnoses. We believe that mining of large medical databases can help improve the current status of disease understanding and decision making. In a previous study based on binary description of hypointensity in the brain, it was shown that brain iron accumulation shape provides additional information to the shape-insensitive features, such as the total brain iron load, that are commonly used in clinics. This paper proposes a novel, nonbinary description of hypointensity in the brain based on principal component analysis. We compare the complementary and redundant information provided by the two descriptions using Kendall's rank correlation coeffcient in order to better understand the individual descriptions of iron accumulation in the brain and obtain a more robust and accurate search and retrieval system.