scholarly journals The reproducibility and accuracy of cephalometric analysis using different digital imaging modalities and image compression

2002 ◽  
Vol 122 (1) ◽  
pp. 118-119 ◽  
Keyword(s):  
Image Compression ◽  
Digital Imaging ◽  
Imaging Modalities ◽  
Cephalometric Analysis

scholarly journals A TWO COMPONENT MEDICAL IMAGE COMPRESSION TECHNIQUES FOR DICOM IMAGES

2013 ◽  
pp. 226-229
Author(s):  
K. S. SELVANAYAKI
Keyword(s):  
Image Compression ◽  
Digital Imaging ◽  
Medical Image ◽  
High Speed ◽  
Medical Images ◽  
Set Partitioning ◽  
The Body ◽  
Compression Technique ◽  
Medical Image Compression ◽  
Two Component

To meet the demand for high speed transmission of image, efficient image storage, remote treatment an efficient image compression technique is essential. Wavelet theory has great potential in medical image compression. Most of the commercial medical image viewers do not provide scalability in image compression. This paper discusses a medical application that contains a viewer for digital imaging and communications in medicine (DICOM) images as a core module. Progressive transmission of medical images through internet has emerged as a promising protocol for teleradiology applications. The major issue that arises in teleradiology is the difficulty of transmitting large volume of medical data with relatively low bandwidth. Recent image compression techniques have increased the viability by reducing the bandwidth requirement and cost-effective delivery of medical images for primary diagnosis. This paper presents an effective algorithm to compress and reconstruct Digital Imaging and Communications in Medicine (DICOM) images. DICOM is a standard for handling, storing, printing and transmitting information in medical imaging. These medical images are volumetric consisting of a series of sequences of slices through a given part of the body. DICOM image is first decomposed by Haar Wavelet Decomposition Method. The wavelet coefficients are encoded using Set Partitioning in Hierarchical Trees (SPIHT) algorithm. Discrete Cosine Transform (DCT) is performed on the images and the coefficients are JPEG coded. The quality of the compressed image by different method are compared and the method exhibiting highest Peak Signal to Noise Ratio (PSNR) is retained for the image. The performance of the compression of medical images using the above said technique is studied with the two component medical image compression techniques.

Survey of Medical Image Compression Techniques and Comparative Analysis

2017 ◽  
pp. 1165-1198
Author(s):  
P. Geetha
Keyword(s):  
Medical Imaging ◽  
Image Compression ◽  
Digital Imaging ◽  
Medical Image ◽  
Satellite Communications ◽  
Digital Data ◽  
High Definition ◽  
Medical Image Compression ◽  
High Definition Television ◽  
Digital Storage

Today digital imaging is widely used in every application around us like Internet, High Definition TeleVision (HDTV), satellite communications, fax transmission, and digital storage of movies and more, because it provide superior resolution and quality. Recently, medical imaging has begun to take advantage of digital technology, opening the way for advanced medical imaging and teleradiology. However, medical imaging requires storing, communicating and manipulating large amounts of digital data. Applying image compression reduces the storage requirements, network traffic, and therefore improves efficiency. This chapter provides the need for medical image compression; different approaches to image compression, emerging wavelet based lossy-lossless compression techniques, how the existing recent compression techniques work and also comparison of results. After completing this chapter, the reader should have an idea of how to increase the compression ratio and at the same time maintain the PSNR level compared to the existing techniques, desirable features of standard compression techniques such as embededness and progressive transmission, how these are very useful and much needed in the interactive teleradiology, telemedicine and telebrowsing applications.

Digital Imaging Modalities for Dental Practice.

2001 ◽  
Vol 42 (1) ◽  
pp. 1-14 ◽  
Author(s):  
MAMORU WAKOH ◽  
KINYA KUROYANAGI
Keyword(s):  
Digital Imaging ◽  
Imaging Modalities ◽  
Dental Practice

Survey of Medical Image Compression Techniques and Comparative Analysis

2014 ◽  
pp. 327-356
Author(s):  
P. Geetha
Keyword(s):  
Medical Imaging ◽  
Image Compression ◽  
Digital Imaging ◽  
Medical Image ◽  
Satellite Communications ◽  
Digital Data ◽  
High Definition ◽  
Medical Image Compression ◽  
High Definition Television ◽  
Digital Storage

Today digital imaging is widely used in every application around us like Internet, High Definition TeleVision (HDTV), satellite communications, fax transmission, and digital storage of movies and more, because it provide superior resolution and quality. Recently, medical imaging has begun to take advantage of digital technology, opening the way for advanced medical imaging and teleradiology. However, medical imaging requires storing, communicating and manipulating large amounts of digital data. Applying image compression reduces the storage requirements, network traffic, and therefore improves efficiency. This chapter provides the need for medical image compression; different approaches to image compression, emerging wavelet based lossy-lossless compression techniques, how the existing recent compression techniques work and also comparison of results. After completing this chapter, the reader should have an idea of how to increase the compression ratio and at the same time maintain the PSNR level compared to the existing techniques, desirable features of standard compression techniques such as embededness and progressive transmission, how these are very useful and much needed in the interactive teleradiology, telemedicine and telebrowsing applications.

PACS Development At Kyoto University Hospital: Toward integrating digital imaging modalities.

1989 ◽  
Author(s):  
Kotaro Minato ◽  
Masaru Komori ◽  
Yoshihisa Nakano ◽  
Takashi Takahashi ◽  
Kazuhiro Satoh
Keyword(s):  
Digital Imaging ◽  
University Hospital ◽  
Imaging Modalities

User-friendly electronic film library for digital imaging modalities

1992 ◽  
Vol 2 (5) ◽  
Author(s):  
W.F. Good ◽  
C.M. Burzik ◽  
P.J. Scanlon ◽  
G.S. Maitz ◽  
J.M. Herron ◽  
...  
Keyword(s):  
Digital Imaging ◽  
Imaging Modalities ◽  
Film Library ◽  
User Friendly

scholarly journals Significance of Image Compression and Its Upshots - A Survey

2019 ◽  
pp. 1203-1208
Author(s):  
S. Boopathiraja ◽  
P. Kalavathi ◽  
C. Dhanalakshmi
Keyword(s):  
Image Compression ◽  
Digital Imaging ◽  
Signal To Noise Ratio ◽  
Similarity Index ◽  
Structural Similarity ◽  
Quality Requirement ◽  
Huge Amount ◽  
Structural Similarity Index ◽  
Transmission Cost ◽  
Large Growth

In the recent years, digital imaging and multimedia are comprising a large growth. It comes to practice that huge amount of image has been utilizing and it probably demand the image compression methods. Image compression is mainly used for reduce the storage size and transmission cost of an image. Based on the quality requirement, it is classified as either lossy or lossless. In this paper, we explore the significance of image compression and the upshot of the survey conducted from the image compression literature. Additionally, we review the various evaluation metrics for image compression such as Compression Ratio, Bit per Pixel, Mean Square Error, Peak Signal to Noise Ratio and Structural Similarity Index.

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