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Effect of image processing version on detection of non-calcification cancers in 2D digital mammography imaging

机译:图像处理版本对2D乳腺X线摄影成像中非钙化癌的检测的影响

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Image processing (IP) is the last step in the digital mammography imaging chain before interpretation by a radiologist. Each manufacturer has their own IP algorithm(s) and the appearance of an image after IP can vary greatly depending upon the algorithm and version used. It is unclear whether these differences can affect cancer detection. This work investigates the effect of IP on the detection of non-calcification cancers by expert observers. Digital mammography images for 190 patients were collected from two screening sites using Hologic amorphous selenium detectors. Eighty of these cases contained non-calcification cancers. The images were processed using three versions of IP from Hologic -default (full enhancement), low contrast (intermediate enhancement) and pseudo screen-film (no enhancement). Seven experienced observers inspected the images and marked the location of regions suspected to be non-calcification cancers assigning a score for likelihood of malignancy. This data was analysed using JAFROC analysis. The observers also scored the clinical interpretation of the entire case using the BSBR classification scale. This was analysed using ROC analysis. The breast density in the region surrounding each cancer and the number of times each cancer was detected were calculated. IP did not have a significant effect on the radiologists' judgment of the likelihood of malignancy of individual lesions or their clinical interpretation of the entire case. No correlation was found between number of times each cancer was detected and the density of breast tissue surrounding that cancer.
机译:在放射线医生解释之前,图像处理(IP)是数字乳房X线照相成像链中的最后一步。每个制造商都有自己的IP算法,IP之后的图像外观可能会根据所使用的算法和版本而有很大差异。尚不清楚这些差异是否会影响癌症检测。这项工作调查了IP对专家观察员检测非钙化癌症的影响。使用Hologic非晶态硒探测器从两个筛查位置收集了190例患者的数字乳房X线照片图像。这些病例中有80个包含非钙化癌。使用Hologic的三种IP版本处理图像-默认(完全增强),低对比度(中等增强)和伪屏幕胶卷(不增强)。七名经验丰富的观察者检查了这些图像,并标记了疑似非钙化癌区域的位置,并为恶性可能性评分。使用JAFROC分析来分析该数据。观察者还使用BSBR分类量表对整个病例的临床解释评分。使用ROC分析进行了分析。计算每种癌症周围区域的乳房密度和检测到每种癌症的次数。 IP对放射科医生判断单个病灶的恶性可能性或对整个病例的临床解释没有显着影响。在检测到每种癌症的次数与该癌症周围的乳房组织密度之间没有发现相关性。

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