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首页> 外文期刊>Journal of Digital Imaging >Thick Slices from Tomosynthesis Data Sets: Phantom Study for the Evaluation of Different Algorithms
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Thick Slices from Tomosynthesis Data Sets: Phantom Study for the Evaluation of Different Algorithms

机译：层析合成数据集中的厚切片：用于评估不同算法的幻像研究

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PURPOSE Tomosynthesis is a 3-dimensional mammography technique that generates thin slices separated one to the other by typically 1 mm from source data sets. The relatively high image noise in these thin slices raises the value of 1-cm thick slices computed from the set of reconstructed slices for image interpretation. In an initial evaluation, we investigated the potential of different algorithms for generating thick slices from tomosynthesis source data (maximum intensity projection—MIP; average algorithm—AV, and image generation by means of a new algorithm, so-called softMip). The three postprocessing techniques were evaluated using a homogeneous phantom with one textured slab with a total thickness of about 5 cm in which two 0.5-cm-thick slabs contained objects to simulate microcalcifications, spiculated masses, and round masses. The phantom was examined by tomosynthesis (GE Healthcare). Microcalcifications were simulated by inclusion of calcium particles of four different sizes. The slabs containing the inclusions were examined in two different configurations: adjacent to each other and close to the detector and with the two slabs separated by two 1-cm thick breast equivalent material slabs. The reconstructed tomosynthesis slices were postprocessed using MIP, AV, and softMip to generate 1-cm thick slices with a lower noise level. The three postprocessing algorithms were assessed by calculating the resulting contrast versus background for the simulated microcalcifications and contrast-to-noise ratios (CNR) for the other objects. The CNRs of the simulated round and spiculated masses were most favorable for the thick slices generated with the average algorithm, followed by softMip and MIP. Contrast of the simulated microcalcifications was best for MIP, followed by softMip and average projections. Our results suggest that the additional generation of thick slices may improve the visualization of objects in tomosynthesis. This improvement differs from the different algorithms for microcalcifications, speculated objects, and round masses. SoftMip is a new approach combining features of MIP and average showing image properties in between MIP and AV.
机译：目的断层合成是一种3维乳房X线照相术，可以生成与源数据集之间通常相距1 mm的薄片。这些薄片中相对较高的图像噪声提高了从重建的切片集合计算出的1厘米厚的切片的值，以进行图像解释。在初步评估中，我们研究了从断层合成源数据生成厚切片的不同算法（最大强度投影-MIP；平均算法-AV，以及通过新算法，即所谓的softMip）生成图像的潜力。三种后处理技术使用均质体模进行评估，其中均模体具有一块总厚度约为5 cm的纹理板，其中两个0.5 cm厚的板包含模拟微钙化，细化质量和圆形质量的对象。通过断层合成（GE Healthcare）检查了体模。通过包含四种不同大小的钙颗粒来模拟微钙化。以两种不同的配置检查了包含夹杂物的平​​板：彼此相邻且靠近检测器，并且两个平板被两个1厘米厚的乳房等效材料平板隔开。使用MIP，AV和softMip对重建的断层合成切片进行后处理，以生成具有较低噪声级别的1厘米厚的切片。通过计算模拟微钙化的结果对比度与背景以及其他对象的对比度噪声比（CNR），评估了三种后处理算法。模拟的圆形和点状块的CNR最适合使用平均算法生成的厚切片，其次是softMip和MIP。对于MIP，模拟微钙化的对比度最佳，其次是softMip和平均预测。我们的结果表明，额外生成的厚切片可以改善断层合成中对象的可视化。这种改进不同于微钙化，推测物体和圆形质量的不同算法。 SoftMip是一种结合了MIP和平均显示图像特性的新方法，介于MIP和AV之间。

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