International Journal of Engineering Research in Electronics and Communication Engineering(IJERECE)

Monthly Journal for Electronics and Communication Engineering

Volume4,March 2017,

Topic : DICOM Image Compression for Telemedicine based on Region of Interest (ROI)

Authors:K.Gopi || K.M.Hemambaran,T.Ramashri

Abstract:In medical imaging due to increase in demand of storing and transferring the medical images results in need of sufficient memory and transmission bandwidth. Computed Tomography (CT), Magnetic Resonance Image (MRI) procedures produces prohibitive amounts of data, hence compression was introduced in the medical field to renovate these issues. Due to high quantity of information contained in the image, reducing it has become a necessity especially in the medical domain. There exist several compression methods in image processing both lossy and lossless compression. In medical applications Region of Interest (ROI) based compression is preferred to enhance the compression efficiency for transmission and storage. In some areas in medicine, it may be sufficient to maintain high image quality only in the region of interest, i.e., diagnostically important regions, but the cost of a wrong interpretation are high. Due to the reason that in medical filed the diagnostically important region should be compressed with better quality than background. Hence, Region Based Coding (RBC) technique is significant for medical image compression and transmission. Lossless compression schemes with secure transmission play a key role in telemedicine applications that help in accurate diagnosis and research. Block Truncation Coding (BTC) is used for lossy Compression technique and for lossless scalable RBC for Digital Imaging and Communications in Medicine (DICOM) images based on Haar Transform and with distortion limiting compression technique for other regions in image. A detailed analysis is carried out on the basis of parameters like compression ratio (CR), mean square error (MSE) and peak signal to noise ratio (PSNR)..

Keywords: Block Truncation Coding (BTC), Digital Imaging and Communication in Medicine(DICOM), Region of Interest (ROI), Integer wavelet transform(IWT), Mean Square Error (MSE), Compression Ratio(CR), Peak signal to noise ratio(PSNR).

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DOI: 01.1617/vol4/iss3/pid97208

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Dr.Zhongfu Tan
National Professor,
North China Electric Power University,

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ISSN(Online): 2394-6849

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Thomson Reuters ID : q-6288-2016.
ORCiD Research ID : 0000-0001-9540-6799

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Journal Code : IJERECE
Electronic ISSN : 2394-6849
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