Case based image retrieval and clinical analysis of tumor and cyst

摘要

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.