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用于改善扩散光学断层扫描图像重建的紧凑型乳房形状采集系统。

Compact breast shape acquisition system for improving diffuse optical tomography image reconstructions.

作者信息

Vanegas Morris, Mireles Miguel, Xu Edward, Yan Shijie, Fang Qianqian

机构信息

Department of Bioengineering, Northeastern University, Boston, MA 02115, USA.

Department of Electrical and Computer Engineering, Northeastern University, Boston, MA 02115, USA.

出版信息

Biomed Opt Express. 2023 Mar 22;14(4):1579-1593. doi: 10.1364/BOE.481092. eCollection 2023 Apr 1.

Abstract

Diffuse optical tomography (DOT) has been investigated for diagnosing malignant breast lesions, but its accuracy relies on model-based image reconstructions, which in turn depends on the accuracy of breast shape acquisition. In this work, we have developed a dual-camera structured light imaging (SLI) breast shape acquisition system tailored for a mammography-like compression setting. Illumination pattern intensity is dynamically adjusted to account for skin tone differences, while thickness-informed pattern masking reduces artifacts due to specular reflections. This compact system is affixed to a rigid mount that can be installed into existing mammography or parallel-plate DOT systems without the need for camera-projector re-calibration. Our SLI system produces sub-millimeter resolution with a mean surface error of 0.26 mm. This breast shape acquisition system results in more accurate surface recovery, with an average 1.6-fold reduction in surface estimation errors over a reference method via contour extrusion. Such improvement translates to 25% to 50% reduction in mean squared error in the recovered absorption coefficient for a series of simulated tumors 1-2 cm below the skin.

摘要

扩散光学断层扫描(DOT)已被用于诊断乳腺恶性病变,但其准确性依赖于基于模型的图像重建,而这又取决于乳房形状获取的准确性。在这项工作中,我们开发了一种双相机结构光成像(SLI)乳房形状获取系统,该系统专为类似乳腺X线摄影的压迫设置而设计。照明图案强度会动态调整以适应肤色差异,而厚度信息图案掩膜可减少镜面反射产生的伪影。这个紧凑的系统固定在一个刚性支架上,可以安装到现有的乳腺X线摄影或平行板DOT系统中,无需重新校准相机和投影仪。我们的SLI系统产生的分辨率低于毫米级,平均表面误差为0.26毫米。这种乳房形状获取系统能实现更精确的表面恢复,与通过轮廓挤压的参考方法相比,表面估计误差平均降低了1.6倍。这种改进使得在皮肤下方1-2厘米处的一系列模拟肿瘤的恢复吸收系数的均方误差降低了25%至50%。

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