PUMA publications for /user/rainerreichel/imaging;computed%20range%20analysis;ct;hdr-vdp;jpeg2000%20fidelityhttps://puma.ub.uni-stuttgart.de/user/rainerreichel/imaging;computed%20range%20analysis;ct;hdr-vdp;jpeg2000%20fidelityPUMA RSS feed for /user/rainerreichel/imaging;computed%20range%20analysis;ct;hdr-vdp;jpeg2000%20fidelity2024-03-29T09:00:01+01:00A Comparison of Three Image Fidelity Metrics of Different Computational Principles for JPEG2000 Compressed Abdomen CT Imageshttps://puma.ub.uni-stuttgart.de/bibtex/2b3bb778cf3609f98508db5321c4a6f3c/rainerreichelrainerreichel2016-03-03T17:45:04+01:00Abdominal;Reproducibility Compression;Humans;Image Computed Computer-Assisted;Observation;ROC Curve;Data Curve;Radiography, Nonparametric;Tomography, Processing, Results;Statistics, Under X-Ray analysis;CT;HDR-VDP;JPEG2000 biological coding;Computed coding;Medical coding;medical coefficients;abdomen;computed compression;MS-SSIM;PSNR;Spearman compression;diagnostic compression;image correlation diagnostic difference fidelity image imaging;Computed imaging;PSNR;Radiology;Transform metric;Adult;Area metrics;multiscale of organs;computerised predictor;image processing;sensitivity radiography;image range rank ratio;Abdomen;Biomedical science;Hospitals;Image signal-to-noise similarity;peak structural tomography;Computer tomography;JPEG2000;image tomography;data tomography;high-dynamic visual <span data-person-type="author" class="authorEditorList "><span><span itemtype="http://schema.org/Person" itemscope="itemscope" itemprop="author"><a title="Kil Joong Kim" itemprop="url" href="/person/139d4c0d08b7efb8cbf0f7a1c55cf1acd/author/0"><span itemprop="name">K. Kim</span></a></span>, </span><span><span itemtype="http://schema.org/Person" itemscope="itemscope" itemprop="author"><a title="Bohyoung Kim" itemprop="url" href="/person/139d4c0d08b7efb8cbf0f7a1c55cf1acd/author/1"><span itemprop="name">B. Kim</span></a></span>, </span><span><span itemtype="http://schema.org/Person" itemscope="itemscope" itemprop="author"><a title="R. Mantiuk" itemprop="url" href="/person/139d4c0d08b7efb8cbf0f7a1c55cf1acd/author/2"><span itemprop="name">R. Mantiuk</span></a></span>, </span><span><span itemtype="http://schema.org/Person" itemscope="itemscope" itemprop="author"><a title="T. Richter" itemprop="url" href="/person/139d4c0d08b7efb8cbf0f7a1c55cf1acd/author/3"><span itemprop="name">T. Richter</span></a></span>, </span><span><span itemtype="http://schema.org/Person" itemscope="itemscope" itemprop="author"><a title="Hyunna Lee" itemprop="url" href="/person/139d4c0d08b7efb8cbf0f7a1c55cf1acd/author/4"><span itemprop="name">H. Lee</span></a></span>, </span><span><span itemtype="http://schema.org/Person" itemscope="itemscope" itemprop="author"><a title="Heung-Sik Kang" itemprop="url" href="/person/139d4c0d08b7efb8cbf0f7a1c55cf1acd/author/5"><span itemprop="name">H. Kang</span></a></span>, </span><span><span itemtype="http://schema.org/Person" itemscope="itemscope" itemprop="author"><a title="Jinwook Seo" itemprop="url" href="/person/139d4c0d08b7efb8cbf0f7a1c55cf1acd/author/6"><span itemprop="name">J. Seo</span></a></span>, </span> and <span><span itemtype="http://schema.org/Person" itemscope="itemscope" itemprop="author"><a title="Kyoung Ho Lee" itemprop="url" href="/person/139d4c0d08b7efb8cbf0f7a1c55cf1acd/author/7"><span itemprop="name">K. Lee</span></a></span></span>. </span><span class="additional-entrytype-information"><span itemtype="http://schema.org/PublicationIssue" itemscope="itemscope" itemprop="isPartOf"><em><span itemprop="journal">Medical Imaging, IEEE Transactions on</span>, </em> <em><span itemtype="http://schema.org/PublicationVolume" itemscope="itemscope" itemprop="isPartOf"><span itemprop="volumeNumber">29 </span></span>(<span itemprop="issueNumber">8</span>):
<span itemprop="pagination">1496-1503</span></em> </span>(<em><span>August 2010<meta content="August 2010" itemprop="datePublished"/></span></em>)</span>Thu Mar 03 17:45:04 CET 2016Medical Imaging, IEEE Transactions onaug81496-1503{A} {C}omparison of {T}hree {I}mage {F}idelity {M}etrics of {D}ifferent {C}omputational {P}rinciples for {JPEG}2000 {C}ompressed {A}bdomen {CT} {I}mages292010Abdominal;Reproducibility Compression;Humans;Image Computed Computer-Assisted;Observation;ROC Curve;Data Curve;Radiography, Nonparametric;Tomography, Processing, Results;Statistics, Under X-Ray analysis;CT;HDR-VDP;JPEG2000 biological coding;Computed coding;Medical coding;medical coefficients;abdomen;computed compression;MS-SSIM;PSNR;Spearman compression;diagnostic compression;image correlation diagnostic difference fidelity image imaging;Computed imaging;PSNR;Radiology;Transform metric;Adult;Area metrics;multiscale of organs;computerised predictor;image processing;sensitivity radiography;image range rank ratio;Abdomen;Biomedical science;Hospitals;Image signal-to-noise similarity;peak structural tomography;Computer tomography;JPEG2000;image tomography;data tomography;high-dynamic visual This study aimed to evaluate three image fidelity metrics of different computational principles-peak signal-to-noise ratio (PSNR), high-dynamic range visual difference predictor (HDR-VDP), and multiscale structural similarity (MS-SSIM)-in measuring the fidelity of JPEG2000 compressed abdomen computed tomography images from a viewpoint of visually lossless compression. Three hundred images with 0.67- or 5-mm section thickness were compressed to one of five compression ratios ranging from reversible compression to 15:1. The fidelity of each compressed image was measured by five radiologists' visual analyses (distinguishable or indistinguishable from the original) and the three metrics. The Spearman rank correlation coefficients of the PSNR, HDR-VDP, and MS-SSIM values with the number of readers responding as indistinguishable were 0.86, 0.94, and 0.86, respectively. Using the pooled readers' responses as the reference standard, the area under the receiver-operating-characteristic curve for the HDR-VDP (0.99) was significantly greater than that for the PSNR (0.95) (p <; 0.001) and for the MS-SSIM (0.96) (p = 0.003), and there was no significant difference between the PSNR and MS-SSIM (p = 0.70). In measuring the image fidelity, the HDR-VDP outperforms the PSNR and MS-SSIM, and the MS-SSIM and PSNR are comparable.