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Case based image retrieval and clinical analysis of tumor and cyst
Author(s): Swarnambiga Ayyachamy; Ganapathy Krishnamurthi
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Paper Abstract

Case based reasoning (CBR) with image retrieval can be used to implement a clinical decision support system for supporting diagnosis of space occupying lesions . We present a case based image retrieval (CBIR) system to retrieve images with lesion similar to the input test image. Here we consider only glioblasoma and lung cancer lesions. The lung cancer lesions can be either nodules or cysts. A feature database has been created and the processing of a query is conducted in real time. By using bag of visual words (BOVW), histogram of features is compared with the codebook to retrieve similar images. The experiments performed at various levels retrieved relevant and similar images of lesion images with a mean average precision of 0.85. The system presented is expected aid and improve the effectiveness of diagnosis performed by radiologist.

Paper Details

Date Published: 15 March 2019
PDF: 6 pages
Proc. SPIE 10954, Medical Imaging 2019: Imaging Informatics for Healthcare, Research, and Applications, 109540Z (15 March 2019); doi: 10.1117/12.2515660
Show Author Affiliations
Swarnambiga Ayyachamy, Indian Institute of Technology Madras (India)
Ganapathy Krishnamurthi, Indian Institute of Technology Madras (India)


Published in SPIE Proceedings Vol. 10954:
Medical Imaging 2019: Imaging Informatics for Healthcare, Research, and Applications
Po-Hao Chen; Peter R. Bak, Editor(s)

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