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Local image registration a comparison for bilateral registration mammography

机译:本地图像配准与双侧乳房X线摄影的比较

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摘要

Early tumor detection is a key factor in reducing breast cancer mortality. Screening mammography is the most widely available method for early cancer detection. However, the large amount of images to be read at each radiological session stress the radiologist ability to process each case with uniform attention. Computer aided detection (CADe) systems can improve tumor detection rate; but the current efficiency of these systems is not adequate and the correct interpretation of CADe outputs requires more time from the experts. Computer aided diagnosis systems (CADx) are being designed to improve cancer diagnosis accuracy and reduce radiological workload; but the efficiency CADx in screening mammography is not yet adequate for clinical use. Our hypothesis is that CADx sensitivity for mammography applications can be enhanced by considering the natural symmetry between the right and left breast. The primary objective of this work is to evaluate co-registration algorithms for the accurate alignment of the left to right breast for CADx applications. Three different set of registrations algorithms were tested: One based on B-Spline deformable transformations and two based on Demon's free form deformations. A set of mammograms was artificially altered to create a ground truth set of 132 images for the evaluation of the registration efficiency. The registration accuracy was visually inspected and quantitatively evaluated using mean square error, mutual information and correlation metrics. The results indicated that the B-Spline deformable registration outperforms Demon's for the task of registering mammography images.
机译:早期发现肿瘤是降低乳腺癌死亡率的关键因素。乳腺钼靶筛查是早期发现癌症最广泛的方法。然而,在每次放射学会议期间要读取的大量图像使放射科医生有能力在统一注意的情况下处理每个病例。计算机辅助检测(CADe)系统可以提高肿瘤检测率;但是这些系统的当前效率还不够,对CADe输出的正确解释需要专家花费更多时间。正在设计计算机辅助诊断系统(CADx),以提高癌症诊断的准确性并减少放射工作量;但是,CADx筛查乳腺摄影的效率尚不足以用于临床。我们的假设是,通过考虑左右乳房之间的自然对称性,可以提高对X线摄影应用的CADx敏感性。这项工作的主要目的是评估共注册算法,以实现CADx应用中左右乳房的精确对齐。测试了三种不同的套准算法:一种基于B样条可变形变换,另一种基于Demon的自由形式变形。人工更改了一组乳房X线照片,以创建132张图像的地面真相集,用于评估套准效率。目视检查配准准确性,并使用均方差,互信息和相关性指标进行定量评估。结果表明,B样条的可变形配准在配准乳腺X线照片方面胜过Demon's。

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  • 会议地点 Mexico City(MX)
  • 作者单位

    Tecnologico de Monterrey, Catedra de Bioinformatica, Escuela de Ingenieria y Tecnologias de Informacion, ITESM, Monterrey, NL, Mexico, 64710;

    Tecnologico de Monterrey, Catedra de Bioinformatica, Escuela de Ingenieria y Tecnologias de Informacion, ITESM, Monterrey, NL, Mexico, 64710;

    Tecnologico de Monterrey, Catedra de Bioinformatica, Escuela de Ingenieria y Tecnologias de Informacion, ITESM, Monterrey, NL, Mexico, 64710,Tecnologico de Monterrey, Catedra de Bioinformatica, Departamento de Investigacion e Innovacion, Escuela de Medicina, ITESM, Monterrey, NL, Mexico, 64710;

    Tecnologico de Monterrey, Catedra de Bioinformatica, Escuela de Ingenieria y Tecnologias de Informacion, ITESM, Monterrey, NL, Mexico, 64710,Tecnologico de Monterrey, Catedra de Bioinformatica, Departamento de Investigacion e Innovacion, Escuela de Medicina, ITESM, Monterrey, NL, Mexico, 64710;

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