Suppr超能文献

数字化乳腺X线摄影的有损JPEG2000和基于对象的分层树集分割压缩的自由响应接收器操作特性评估

Free-response receiver operating characteristic evaluation of lossy JPEG2000 and object-based set partitioning in hierarchical trees compression of digitized mammograms.

作者信息

Penedo Mónica, Souto Miguel, Tahoces Pablo G, Carreira José M, Villalón Justo, Porto Gerardo, Seoane Carmen, Vidal Juan J, Berbaum Kevin S, Chakraborty Dev P, Fajardo Laurie L

机构信息

Laboratorio de Imagen Médica, Hospital General Universitario Gregorio Marañón, C/Ibiza 43, 28009 Madrid, Spain.

出版信息

Radiology. 2005 Nov;237(2):450-7. doi: 10.1148/radiol.2372040996.

Abstract

PURPOSE

To assess the effects of two irreversible wavelet-based compression algorithms--Joint Photographic Experts Group (JPEG) 2000 and object-based set partitioning in hierarchical trees (SPIHT)--on the detection of clusters of microcalcifications and masses on digitized mammograms.

MATERIALS AND METHODS

The use of the images in this retrospective image-collection study was approved by the institutional review board, and patient informed consent was not required. One hundred twelve mammographic images (28 with one or two clusters of microcalcifications, 19 with one mass, 17 with both abnormal findings, and 48 with normal findings) obtained in 60 women who ranged in age from 25 to 79 years were digitized and compressed at 40:1 and 80:1 by using the JPEG2000 and object-based SPIHT methods. Five experienced radiologists were asked to locate and rate clusters of microcalcifications and masses on the original and compressed images in a free-response receiver operating characteristic (FROC) data acquisition paradigm. Observer performance was evaluated with the jackknife FROC method.

RESULTS

The mean FROC figures of merit for detecting clusters of microcalcifications, masses, and both radiographic findings on uncompressed images were 0.80, 0.81, and 0.72, respectively. With object-based SPIHT 80:1 compression, the corresponding values were larger than the values for uncompressed images by 0.005, 0.009, and -0.005, respectively. The 95% confidence interval for the differences in figures of merit between compressed and uncompressed images was -0.039, 0.033 for the microcalcification finding; -0.055, 0.034 for the mass finding; and -0.039, 0.030 for both findings. Because each of these confidence intervals includes zero, no significant difference in detection accuracy between uncompressed and object-based SPIHT 80:1 compression was observed at a P value of 5%. The F test of the null hypothesis that all of the modes (uncompressed and four compressed modes) were equivalent yielded the following results: F = 0.255, P = .903 for the microcalcification finding; F = 0.340, P = .848 for the mass finding; and F = 0.122, P = .975 for both findings.

CONCLUSION

To within the accuracy of these measurements, lossy compression of digital mammographic data at 80:1 with JPEG2000 or the object-based SPIHT algorithm can be performed without decreasing the rate of detection of clusters of microcalcifications and masses.

摘要

目的

评估两种基于不可逆小波的压缩算法——联合图像专家组(JPEG)2000和基于对象的分层树状集分割算法(SPIHT)——对数字化乳腺X线摄影中微钙化簇和肿块检测的影响。

材料与方法

本回顾性图像收集研究中对图像的使用获得了机构审查委员会的批准,且无需患者知情同意。对60名年龄在25至79岁之间的女性所获得的112幅乳腺X线图像(28幅有一或两个微钙化簇,19幅有一个肿块,17幅有两种异常表现,48幅正常)进行数字化处理,并使用JPEG2000和基于对象的SPIHT方法以40:1和80:1的比例进行压缩。邀请5名经验丰富的放射科医生在自由响应接收器操作特性(FROC)数据采集模式下,在原始图像和压缩图像上定位并评估微钙化簇和肿块。采用留一法FROC方法评估观察者的表现。

结果

在未压缩图像上检测微钙化簇、肿块以及两种影像学表现的平均FROC品质因数分别为0.80、0.81和0.72。采用基于对象的SPIHT 80:1压缩时,相应的值分别比未压缩图像的值大0.005、0.009和 -0.005。压缩图像与未压缩图像之间品质因数差异的95%置信区间,对于微钙化表现为 -0.039, 0.033;对于肿块表现为 -0.055, 0.034;对于两种表现均为 -0.039, 0.030。由于这些置信区间均包含零,因此在5%的P值水平下,未观察到未压缩图像与基于对象的SPIHT 80:1压缩图像在检测准确性上有显著差异。对所有模式(未压缩和四种压缩模式)等效的原假设进行F检验,结果如下:对于微钙化表现,F = 0.255,P = 0.903;对于肿块表现,F = 0.340,P = 0.848;对于两种表现均为,F = 0.122,P = 0.975。

结论

在这些测量的精度范围内,使用JPEG2000或基于对象的SPIHT算法对数字乳腺X线摄影数据进行80:1的有损压缩,不会降低微钙化簇和肿块的检测率。

文献检索

告别复杂PubMed语法,用中文像聊天一样搜索,搜遍4000万医学文献。AI智能推荐,让科研检索更轻松。

立即免费搜索

文件翻译

保留排版,准确专业,支持PDF/Word/PPT等文件格式,支持 12+语言互译。

免费翻译文档

深度研究

AI帮你快速写综述,25分钟生成高质量综述,智能提取关键信息,辅助科研写作。

立即免费体验