Boosting biomedical images indexing

• Published in: IEEE EMBS APBME2003 : 20-22 October 2003, Keihanna Plaza Hotel, the border of Kyoto-Osaka-Nara, Japan : IEEE EMBS Asian-Pacific Conference on Biomedical Engineering, 2003 pp. 74 - 75
• Main Authors: Tsishkou, D.V., Kukharchik, P.D., Bovbel, E.I., Kheidorov, I.E., Liventseva, M.M.
• Format: Conference Proceeding
• Language: English
• Published: IEEE 2003
• Subjects: Biomedical imaging; Boosting; Engines; Image databases; Image retrieval; Indexing; Information retrieval; Large-scale systems; Robustness; Spatial databases
• ISBN: 0780379438; 9780780379435
• DOI: 10.1109/APBME.2003.1302590

Indexing and retrieval in biomedical image databases is a challenging problem. Constructing large-scale indexing solutions is typically limited by a choice of appropriate features, complexity constraints of the engine and a way how to combine retrieval results to have a stronger one. Combination of standard feature extraction routines with specific knowledge on a subject, such as precise automatic object segmentation and medical parameters estimation is the first key factor to achieve high accuracy and robustness of the indexing/retrieval solution. We are developing a search engine based on a TTA10 algorithm, which stores data in hierarchical fashion, with logarithmic complexity to access a large data repository in real-time. We propose to use AdaBoost technique to combine independent search results into more robust and accurate one. Initial results on a database of more than 80.000 ultrasound images demonstrate good accuracy and fast speed.