Bio-medical Ontologies Maintenance and Change Management

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2.3 Extracting Data from DICOM File Multimedia Medical Databases 83 In order to extract data from the DICOM file, we are taking into account every tag from the DICOM dictionary. The tag will be searched in the file and in case of finding it the corresponding value will be extracted. The steps of extracting information from DICOM files, designed at Software Engineering Department, Faculty of Automation, Computers and Electronics, Craiova, are: 1. Verifying the existence of the ‘D’,’I’,’C’,’M’ characters in the file prefix. 2. Establishing the type of VR (ExplicitVR or ImplicitVR). This information is given by the UID (Unique Identifier), information stored in the value field corresponding to the Transfer Syntax Tag. 3. Establishing the Byte Ordering (BigEndian or LittleEndian). The information is also given by UID, stored in the value field of the same Transfer Syntax Tag. The DICOM standard contains all the values that UID can have. 4. Searching a tag in DICOM file according to the VR type and ByteOrdering 5. Value extraction of the corresponding found tag. DICOM Standard contains over 20 types of binary data or ASCII. The type of information stored in the value field is given by VR. In accordance with this type will be extracted strings, integer or byte type information. Next it is described the problem of image extracting from the standard DICOM files, taking into account the method of compression that was used: RLE, JPEG. A single DICOM object can contain only one image, but that image may have multiple “frames”, allowing storage of cine-loops or other multi-frame data. The images from DICOM files can be classified using several criteria: 1. The number of images stored in a file: single frame or multi-frame. 2. Number of bits per pixel: 8 bits, 12 bits, 16 bits or 24 bits. 3. Compression: without compression (raw) or with compression (RLE JPEG, JPEG Lossless, JPEG 2000. LZW (zip) compression can be used for the whole data set (not just the pixel data) but is rarely implemented. 4. Photometric interpretation: gray scale images, color images, palette color images. In the images without compression, the extraction of pictures is made pixel-bypixel, taking into account the number of bits stored for each pixel and the photometric interpretation (for monochrome images a pixel is stored using maximum 2 bytes and for color images, a pixel is stored using 3 bytes). In the images that use compression it is necessary a decompression algorithm before saving. The pseudo code for retrieving the frames is: Set variable number to 0 Loop until all frames are retrieved Set file dimension as Rows*Columns*SamplePerPixel Read all file dimension pixels from file starting With (Header Length + number* file dimension)
84 L. Stanescu, D. Dan Burdescu, and M. Brezovan If MONOCHROME image Save as image Store image using GIF or JPEG image format Return End If If PALETTE COLOR image Get the Palette tables (one for red values, one for green values and one for blue values) Get Pixels color from the Palette. Save as image Store image using GIF or JPEG image format End If If RGB image (24 bits) Get red, green and blue values Compute the color using the formula: ((255
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Amandeep S. Sidhu and Tharam S. Dil
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Amandeep S. Sidhu and Tharam S. Dil
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Preface The molecular biology commu
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Preface VII biomedical systems, and
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X Contents Mining Clinical, Immunol
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2 A.S. Sidhu, M. Bellgard, and T.S.
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Towards Bioinformatics Resourceomes
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2 The New Waves Towards Bioinformat
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2.4 Semantic Web Towards Bioinforma
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134 L. Stanescu, D. Dan Burdescu, a
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Bio-medical Ontologies Maintenance
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TextToOnto (Maedche and Volz 2001)
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Extraction of Constraints from Biol
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Classifying Patterns in Bioinformat
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Mining Clinical, Immunological, and
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Substructure Analysis of Metabolic
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entry compound relation subtype com
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Running Time 4500 4000 3500 3000 25
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6 Conclusion Substructure Analysis
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266 J.Y. Chen, S. Taduri, and F. Ll
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Completing the Total Wellbeing Puzz
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296 M. Fernandez, M. Villasana, and
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Genetic Algorithm in Ab Initio Prot
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Author Index Apiletti, Daniele 169
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Bio-medical Ontologies Maintenance and Change Management

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