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Medical image database is growing day by day. 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 with patients to provide right treatment. Medical Imaging is playing 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 proposed fuzzy connectedness image segmentation for medical image retrieval in Oracle using digital imaging and communications in medicine (DICOM) format. Paper includes the comparison of image retrieval techniques with the proposed fuzzy connectedness image segmentation combined with geometric moment. Paper also gives the implementation details of proposed algorithm in Oracle. For the analysis purpose we have implemented feature extraction methods for color, texture and shape based feature extraction. These methods are compared with the proposed algorithm.

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The Digital Imaging and Communications in Medicine (DICOM) standard was created to aid the distribution and viewing of medical images, such as CT scans, MRIs, and ultrasound by the National Electrical Manufacturers Association (NEMA). This paper includes description of various image formats and image compression algorithms which will be helpful for researcher in the field of medical image processing. The comparison of described formats and compression techniques is also provided in this paper. DICOM is the most common standard for receiving scans from a hospital. The DICOM standard is an evolving standard and it is maintained in accordance with the procedures of the DICOM standards committee. The features, which are extracted from DICOM images, are included in this paper.