Abstract
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.
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Bhagat, A., Atique, M. (2014). DICOM Image Retrieval Using Geometric Moments and Fuzzy Connectedness Image Segmentation Algorithm. In: Satapathy, S., Avadhani, P., Udgata, S., Lakshminarayana, S. (eds) ICT and Critical Infrastructure: Proceedings of the 48th Annual Convention of Computer Society of India- Vol I. Advances in Intelligent Systems and Computing, vol 248. Springer, Cham. https://doi.org/10.1007/978-3-319-03107-1_13
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DOI: https://doi.org/10.1007/978-3-319-03107-1_13
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-03106-4
Online ISBN: 978-3-319-03107-1
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