Lu Yao, Chan Heang-Ping, Wei Jun, Hadjiiski Lubomir M, Samala Ravi K
Department of Radiology, University of Michigan, Ann Arbor, Michigan 48109.
Med Phys. 2015 Jan;42(1):182-95. doi: 10.1118/1.4903283.
Detection of subtle microcalcifications in digital breast tomosynthesis (DBT) is a challenging task because of the large, noisy DBT volume. It is important to enhance the contrast-to-noise ratio (CNR) of microcalcifications in DBT reconstruction. Most regularization methods depend on local gradient and may treat the ill-defined margins or subtle spiculations of masses and subtle microcalcifications as noise because of their small gradient. The authors developed a new multiscale bilateral filtering (MSBF) regularization method for the simultaneous algebraic reconstruction technique (SART) to improve the CNR of microcalcifications without compromising the quality of masses.
The MSBF exploits a multiscale structure of DBT images to suppress noise and selectively enhance high frequency structures. At the end of each SART iteration, every DBT slice is decomposed into several frequency bands via Laplacian pyramid decomposition. No regularization is applied to the low frequency bands so that subtle edges of masses and structured background are preserved. Bilateral filtering is applied to the high frequency bands to enhance microcalcifications while suppressing noise. The regularized DBT images are used for updating in the next SART iteration. The new MSBF method was compared with the nonconvex total p-variation (TpV) method for noise regularization with SART. A GE GEN2 prototype DBT system was used for acquisition of projections at 21 angles in 3° increments over a ± 30° range. The reconstruction image quality with no regularization (NR) and that with the two regularization methods were compared using the DBT scans of a heterogeneous breast phantom and several human subjects with masses and microcalcifications. The CNR and the full width at half maximum (FWHM) of the line profiles of microcalcifications and across the spiculations within their in-focus DBT slices were used as image quality measures.
The MSBF method reduced contouring artifacts and enhanced the CNR of microcalcifications compared to the TpV method, thus preserving the image quality of the structured background. The MSBF method achieved the highest CNR of microcalcifications among the three methods. The FWHM of the microcalcifications and mass spiculations resulting from the MSBF method was comparable to that without regularization, and superior to that of the TpV method.
The SART regularized by the multiscale bilateral filtering method enhanced the CNR of microcalcifications and preserved the sharpness of microcalcifications and spiculated masses. The MSBF method provided better image quality of the structured background and was superior to TpV and NR for enhancing microcalcifications while preserving the appearance of mass margins.
由于数字乳腺断层合成（DBT）数据量大且噪声多，检测其中细微的微钙化是一项具有挑战性的任务。提高DBT重建中微钙化的对比度噪声比（CNR）很重要。大多数正则化方法依赖于局部梯度，可能会将肿块边界不清晰或细微的毛刺以及细微的微钙化视为噪声，因为它们的梯度较小。作者开发了一种用于同时代数重建技术（SART）的新型多尺度双边滤波（MSBF）正则化方法，以提高微钙化的CNR，同时不影响肿块的质量。
MSBF利用DBT图像的多尺度结构来抑制噪声并选择性增强高频结构。在每次SART迭代结束时，通过拉普拉斯金字塔分解将每个DBT切片分解为多个频带。对低频带不应用正则化，以便保留肿块的细微边缘和结构化背景。对高频带应用双边滤波以增强微钙化同时抑制噪声。正则化后的DBT图像用于下一次SART迭代中的更新。将新的MSBF方法与用于SART噪声正则化的非凸总p - 变差（TpV）方法进行比较。使用GE GEN2原型DBT系统在±30°范围内以3°增量在21个角度采集投影。使用异质乳腺模型以及几名有肿块和微钙化的人类受试者的DBT扫描，比较无正则化（NR）以及两种正则化方法的重建图像质量。微钙化的线轮廓以及其聚焦DBT切片内毛刺的半高宽（FWHM）和CNR用作图像质量指标。
与TpV方法相比，MSBF方法减少了轮廓伪影并提高了微钙化的CNR，从而保留了结构化背景的图像质量。在三种方法中，MSBF方法实现了微钙化的最高CNR。MSBF方法产生的微钙化和肿块毛刺的FWHM与无正则化时相当，且优于TpV方法。
通过多尺度双边滤波方法正则化的SART提高了微钙化的CNR，并保留了微钙化和毛刺状肿块的清晰度。MSBF方法提供了更好的结构化背景图像质量，在增强微钙化同时保留肿块边缘外观方面优于TpV和NR。
