Please use this identifier to cite or link to this item: https://hdl.handle.net/20.500.11851/1791
Title: Multi-Regional Adaptive Image Compression (AIC) for Hip Fractures in Pelvis Radiography
Authors: Nasıfoğlu, Hüseyin
Eroğul, Osman
Ataç, Gökçe Kaan
Özdemir, Galip
10187
201173
Keywords: adaptive compression
dicom
jpeg
loss-less
lossy
medical image
radiography
region of interest (roi)
Issue Date: 2017
Publisher: Springer-Verlag Singapore Pte Ltd
Source: Nasifoglu, H., Erogul, O., Atac, G. K., & Ozdemir, G. (2017). Multi-Regional Adaptive Image Compression (AIC) for Hip Fractures in Pelvis Radiography. In CMBEBIH 2017 (pp. 61-67). Springer, Singapore.
Series/Report no.: Proceedings Of The International Conference On Medical And Biological Engineering 2017 (CMBEBIH 2017)
Abstract: High resolution digital medical images are stored in DICOM (Digital Imaging and Communications in Medicine) format that requires high storage space in database. Therefore reducing the image size while maintaining diagnostic quality can increase the memory usage efficiency in PACS. In this study, diagnostic regions of interest (ROI) of pelvis radiographs marked by the radiologist are segmented and adaptively compressed by using image processing algorithms There are three ROIs marked by red, blue and green in every image. ROI contoured by red is defined as the most significant region in the image and compressed by lossless JPEG algorithm. Blue and green regions have less importance than the red region but still contain diagnostic data compared to the rest of the image. Therefore, these regions are compressed by lossy JPEG algorithm with higher quality factor than rest of the image. Non-contoured region is compressed by low quality factor which does not have any diagnostic information about the patient. Several compression ratios are used to determine sufficient quality and appropriate compression level. Compression ratio (CR), peak signal to noise ratio (PSNR), bits per pixel (BPP) and signal to noise ratio (SNR) values are calculated for objective evaluation of image quality. Experimental results show that original images can approximately be compressed six times without losing any diagnostic data. In pelvis radiographs marking multiple regions of interest and adaptive compression of more than one ROI is a new approach. It is believed that this method will improve database management efficiency of PACS while preserving diagnostic image content.
URI: https://doi.org/10.1007/978-981-10-4166-2_10
https://hdl.handle.net/20.500.11851/1791
ISBN: 978-981-10-4166-2; 978-981-10-4165-5
ISSN: 1680-0737
Appears in Collections:Biyomedikal Mühendisliği Bölümü / Department of Biomedical Engineering
Scopus İndeksli Yayınlar Koleksiyonu / Scopus Indexed Publications Collection
WoS İndeksli Yayınlar Koleksiyonu / WoS Indexed Publications Collection

Show full item record

CORE Recommender

WEB OF SCIENCETM
Citations

1
checked on Sep 24, 2022

Page view(s)

26
checked on Dec 26, 2022

Google ScholarTM

Check

Altmetric


Items in GCRIS Repository are protected by copyright, with all rights reserved, unless otherwise indicated.