Authors:
Mohamed Nagy Saad
1
and
Ahmed Hisham Kandil
2
Affiliations:
1
Misr University for Science and Technology, Egypt
;
2
Cairo University, Egypt
Keyword(s):
Medical Image Compression, Huffman Coding, Arithmetic Coding, Discrete Cosine Transform, Wavelet.
Related
Ontology
Subjects/Areas/Topics:
Biomedical Engineering
;
Biomedical Instruments and Devices
;
Imaging and Visualization Devices
Abstract:
The digital medical images have become an essential part of the electronic patient record. These images may be used for screening, diagnosis, treatment and educational purposes. These images have to be stored, archived, retrieved, and transmitted. Compression techniques are extremely useful when considering large quantities of these images. In this paper, four compression techniques are applied on three medical image modalities. The compression techniques are either lossless or lossy techniques. The applied lossless techniques are Huffman and Arithmetic. The applied lossy techniques are Discrete Cosine Transform (DCT) and Wavelet. The modalities are Ultrasound (US), Computed Tomography (CT) and Magnetic Resonance Imaging (MRI). The observed parameters are both the compression ratio (CR) and total compression time (TCT) (compression time + decompression time). The target is to maximize the CR while preserving images’ information using the best compression technique. The maximum accept
ed CR for each image is chosen by three experts. The last enhancement is done by isolating the region of interest (ROI) in the image then applying the compression procedure. Applying the ROI technique on the studied cases by the experts gave promising results.
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