• Journal of Electrical Engineering and Technology
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• 제11권2호
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• pp.499-507
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• 2016

Medical imaging techniques such as Magnetic Resonance Imaging (MRI), Computed Tomography (CT) and Ultrasound (US) produce a large amount of digital medical images. Hence, compression of digital images becomes essential and is very much desired in medical applications to solve both storage and transmission problems. But at the same time, an efficient image compression scheme that reduces the size of medical images without sacrificing diagnostic information is required. This paper proposes a novel threshold-based medical image compression algorithm to reduce the size of the medical image without degradation in the diagnostic information. This algorithm discusses a novel type of thresholding to maximize Compression Ratio (CR) without sacrificing diagnostic information. The compression algorithm is designed to get image with high optimum compression efficiency and also with high fidelity, especially for Peak Signal to Noise Ratio (PSNR) greater than or equal to 36 dB. This value of PSNR is chosen because it has been suggested by previous researchers that medical images, if have PSNR from 30 dB to 50 dB, will retain diagnostic information. The compression algorithm utilizes one-level wavelet decomposition with threshold-based coefficient selection.

• 대한의용생체공학회:의공학회지
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• 제15권2호
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• pp.175-182
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• 1994

The international standard for digital compression and coding of continuous-tone still image known as JPEG (Joint Photographic Experts Group) standard is investigated for medical image archiving and communication. The JPEG standard has widely been accepted in the areas of electronic image communication, computer graphics, and multimedia applications, however, due to the lossy character of the JPEG compression its application to the field of medical imaging has been limited. In this paper, the JPEG standard is investigated for medical image compression with a series of head sections of magnetic resonance (MR) images (256 and 4096 graylevels, $256 {\times}256$size). Two types of Huffman codes are employed, i. e., one is optimized to the image statistics to be encoded and the other is a predetermined code, and their coding efficiencies are examined. From experiments, compression ratios of higher than 15 were obtained for the MR images without noticeable distortion. Error signal in the reconstructed images by the JPEG standard appears close to random noise. Compared to existing full-frame bit-allocation technique used for radiological image compression, the JPEG standard achieves higher compression with less Gibb's artifact. Feature of the progressive image build-up of the JPEG progressive coding may be useful in remote diognosis when data is transmitted through slow public communication channel.

• 한국인터넷방송통신학회논문지
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• 제12권5호
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• pp.39-54
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• 2012

오늘날 의료정보화 수준향상과 디지털 병원화의 흐름에 따라 PACS는 의료기관의 핵심 인프라 중 하나로 자리매김하였다. 이와 함께 생산되는 디지털 의료영상의 종류 및 의료영상 데이터가 양적으로 급증하고 있으며, 이는 의료영상 데이터의 효과적인 보관을 위한 의료영상 압축을 중요한 요소로 부각시킨다. 현재 의료영상에 관한 사실상의 표준인 DICOM 규격에서는 의료영상 압축을 위하여 무손실 압축기법인 RLE를 명시하고 있으나, 무손실 범용 압축기법인 RLE는 인체의 대칭성을 가지는 많은 의료영상에 적용하면 높은 압축율 기대하기 힘들다. 이 논문에서는 다양한 의료영상 중 대칭 특성을 크게 내포하는 뇌 CT 영상을 대상으로 하여 영상 내 관심영역을 검출하고 대칭특성에 따라 영상의 픽셀 값을 재코딩하는 전처리 하고 영상을 압축하는 기법을 제안한다. 실험에 의하면, 제안한 기법은 RLE 압축과 영상 내 관심영역을 검출하지 않고 압축할 때와 비교하여 높은 압축률을 보인다.

• 한국정보통신학회:학술대회논문집
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• 한국해양정보통신학회 2002년도 춘계종합학술대회
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• pp.185-188
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• 2002

컴퓨터의 발달과 네트워크 환경의 개선으로 많은 병원에서는 의료영상을 처리하여 저장하고 전송하는 시스템인 의료영상 저장전송시스템(PACS)을 도입·확대 보급하고 있다. PACS의 도입으로 대용량의 의료 영상을 저장하고 전송하는 문제가 대두되어, 그 해결 방안으로 디지털 영상처리에 사용되고 있는 다양한 영상처리 기법과 압축방법들이 의료영상에 적용되고 있다. 본 논문에서는 의료영상에 다양한 압축방법들을 적용하여 무손실 압축방법으로는 RLC, 손실 압축으로는 DCT를 이용한 JPEG를 DICOM 표준에서 지원하는 방식으로 구현하였다. 또한 현재 영상압축 및 영상처리에 이용되고 있는 Wavelet 변환 방식을 도입하여 의료 영상을 압축하였으며, 의료영상에 적용된 압축방법들의 압축율을 비교·분석하였다.

• Journal of Electrical Engineering and Technology
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• 제7권2호
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• pp.264-272
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• 2012

In the field of medical diagnostics, interested parties have resorted increasingly to medical imaging. It is well established that the accuracy and completeness of diagnosis are initially connected with the image quality, but the quality of the image is itself dependent on a number of factors including primarily the processing that an image must undergo to enhance its quality. This paper introduces an algorithm for medical image compression based on the quincunx wavelets coupled with SPIHT coding algorithm, of which we applied the lattice structure to improve the wavelet transform shortcomings. In order to enhance the compression by our algorithm, we have compared the results obtained with those of other methods containing wavelet transforms. For this reason, we evaluated two parameters known for their calculation speed. The first parameter is the PSNR; the second is MSSIM (structural similarity) to measure the quality of compressed image. The results are very satisfactory regarding compression ratio, and the computation time and quality of the compressed image compared to those of traditional methods.

• 융합신호처리학회논문지
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• 제3권1호
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• pp.33-40
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• 2002

본 연구에서는 의료영상 저장 및 전송 시스템에 필수적인 무손실 의료영상 압축 기법을 제안하였다. 의료영상은 방사선 영상 중에서 유방영상(mammography)과 자기공명영상을 사용하였으며, 이들 영상을 무손실로 압축하기 위하여 영역성장에 의한 영상분할 알고리듬을 제안하였다. 제안된 알고리듬은 원 영상이 에러 영상과 불연속 계수 영상, 그리고 상위 비트 데이터 등 세 가지의 부 영역으로 분할되도록 하였다. 그리고 영역성장 과정 후 생성된 불연속 계수 영상 데이터와 에러 영상을 국제 이진영상압축 표준이며 그레이코드(graycode)화된 영상의 압축에 적합한 JBIG(Joint Bi-level Image expert Group) 알고리듬을 이용하여 압축시켰다. 제안한 알고리듬과 타 연구에서 사용된 기법들을 비교 검토 한 결과 제안한 무손실 압축 기법을 적용하여 얻어지는 압축율은 JBIG, JPEG, LZ 기법에 비해 평균적으로 각각 3.7%, 7.9%, 23.6% 정도 개선됨을 알 수 있었다.

• Journal of Information Processing Systems
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• 제15권2호
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• pp.288-304
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• 2019

The growth of telemedicine-based wireless communication for images-magnetic resonance imaging (MRI) and computed tomography (CT)-leads to the necessity of learning the concept of image compression. Over the years, the transform based and spatial based compression techniques have attracted many types of researches and achieve better results at the cost of high computational complexity. In order to overcome this, the optimization techniques are considered with the existing image compression techniques. However, it fails to preserve the original content of the diagnostic information and cause artifacts at high compression ratio. In this paper, the concept of histogram based multilevel thresholding (HMT) using entropy is appended with the optimization algorithm to compress the medical images effectively. However, the method becomes time consuming during the measurement of the randomness from the image pixel group and not suitable for medical applications. Hence, an attempt has been made in this paper to develop an HMT based image compression by utilizing the opposition based improved harmony search algorithm (OIHSA) as an optimization technique along with the entropy. Further, the enhancement of the significant information present in the medical images are improved by the proper selection of entropy and the number of thresholds chosen to reconstruct the compressed image.

• 대한의용생체공학회:의공학회지
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• 제15권2호
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• pp.121-128
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• 1994

In this paper, MIlS (Medical Image Information System) has been designed and implemented using INGRES RDBMS, which is based on a client/server architecture. The implemnted system allows users to register and retrieve patient information, medical images and diagnostic reports. It also provides the function to display these information on workstation windows simultaneously by using the designed menu-driven graphic user interface. The medical image compression! decompression techniques are implemented and integrated into the medical image database system for the efficient data storage and the fast access through the network.

• 대한의용생체공학회:의공학회지
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• 제15권1호
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• pp.57-62
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• 1994

The demand of image compression is increasing now for the integration of medical images into the hospital information system. Even though the quantitative distortion can be measured from the difference between original and reconstructed images, it doesn't include the nonlinear characteristics of human visual system. In this study, we have evaluated the nonlinear characteristics of human visual system and applied them to the compression of medical images. The distortion measures which reflect the characteristics of human visual system has been considered. This image compression procedure consists of coding scheme using JND (Just Noticeable Difference) curve, polynomial approximation and BTC (Block Truncation Coding). Results show that this method can be applied to CT images, scanned film images and other kinds of medical images with the compression ratio of 5-10:1 without any noticeable distortion.

• Journal of Information Processing Systems
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• 제13권1호
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• pp.40-56
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• 2017

Since the progress of digital medical imaging techniques, it has been needed to compress the variety of medical images. In medical imaging, reversible compression of image's region of interest (ROI) which is diagnostically relevant is considered essential. Then, improving the global compression rate of the image can also be obtained by separately coding the ROI part and the remaining image (called background). For this purpose, the present work proposes an efficient reversible discrete cosine transform (RDCT) based embedded image coder designed for lossless ROI coding in very high compression ratio. Motivated by the wavelet structure of DCT, the proposed rearranged structure is well coupled with a lossless embedded zerotree wavelet coder (LEZW), while the background is highly compressed using the set partitioning in hierarchical trees (SPIHT) technique. Results coding shows that the performance of the proposed new coder is much superior to that of various state-of-art still image compression methods.