The Medical image database is growing day by day. Most of the medical images are stored in DICOM (Digital Imaging and Communications in Medicine) format. There are various categories of medical images such as CT scan, X- Ray, Ultrasound, Pathology, MRI, Microscopy, etc [1]. Physicians compare previous and current medical images associated patients to provide right treatment. Medical Imaging plays a leading role in modern diagnosis. Efficient image retrieval tools are needed to retrieve the intended images from large growing medical image databases. Such tools must provide more precise retrieval results with less computational complexity. This paper compares the proposed technique for DICOM medical image retrieval and shows that the proposed geometric moments and fuzzy connectedness image segmentation algorithm based image retrieval algorithm performs better as compared to other algorithms.
CITATION STYLE
Bhagat, A., & Atique, M. (2014). DICOM Image Retrieval Using Geometric Moments and Fuzzy Connectedness Image Segmentation Algorithm. In Advances in Intelligent Systems and Computing (Vol. 248 VOLUME I, pp. 109–116). Springer Verlag. https://doi.org/10.1007/978-3-319-03107-1_13
Mendeley helps you to discover research relevant for your work.