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Denoised and texture enhanced MVCT to improve soft tissue conspicuity

机译:去噪和增强纹理的MVCT可改善软组织的醒目性

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Purpose: MVCT images have been used in TomoTherapy treatment to align patients based on bony anatomies but its usefulness for soft tissue registration, delineation, and adaptive radiation therapy is limited due to insignificant photoelectric interaction components and the presence of noise resulting from low detector quantum efficiency of megavoltage x-rays. Algebraic reconstruction with sparsity regularizers as well as local denoising methods has not significantly improved the soft tissue conspicuity. The authors aim to utilize a nonlocal means denoising method and texture enhancement to recover the soft tissue information in MVCT (DeTECT).Methods: A block matching 3D (BM3D) algorithm was adapted to reduce the noise while keeping the texture information of the MVCT images. Following imaging denoising, a saliency map was created to further enhance visual conspicuity of low contrast structures. In this study, BM3D and saliency maps were applied to MVCT images of a CT imaging quality phantom, a head and neck, and four prostate patients. Following these steps, the contrast-to-noise ratios (CNRs) were quantified.Results: By applying BM3D denoising and saliency map, postprocessed MVCT images show remarkable improvements in imaging contrast without compromising resolution. For the head and neck patient, the difficult-to-see lymph nodes and vein in the carotid space in the original MVCT image became conspicuous in DeTECT. For the prostate patients, the ambiguous boundary between the bladder and the prostate in the original MVCT was clarified. The CNRs of phantom low contrast inserts were improved from 1.48 and 3.8 to 13.67 and 16.17, respectively. The CNRs of two regions-of-interest were improved from 1.5 and 3.17 to 3.14 and 15.76, respectively, for the head and neck patient. DeTECT also increased the CNR of prostate from 0.13 to 1.46 for the four prostate patients. The results are substantially better than a local denoising method using anisotropic diffusion.Conclusions: The authors showed that it is feasible to extract more soft tissue contrast information from the noisy MVCT images using a nonlocal means 3D block matching method in combination with saliency maps, revealing information that was originally unperceivable to human observers. C 2014 American Association of Physicists in Medicine.
机译:目的:MVCT图像已用于TomoTherapy治疗中,以基于骨解剖体对齐患者,但由于光电相互作用成分不明显以及检测器量子效率低而产生的噪声,其在软组织配准,描绘和自适应放射治疗中的用途受到限制兆电压X射线。使用稀疏正则器进行的代数重建以及局部去噪方法并未显着改善软组织的醒目性。作者旨在利用非局部均值去噪方法和纹理增强来恢复MVCT(DeTECT)中的软组织信息。方法:采用块匹配3D(BM3D)算法来减少噪声,同时保留MVCT图像的纹理信息。 。在图像降噪之后,创建了显着图以进一步增强低对比度结构的视觉显眼性。在这项研究中,将BM3D和显着性图应用于CT成像质量体模,头部和颈部以及四名前列腺患者的MVCT图像。结果:通过应用BM3D去噪和显着图,后处理的MVCT图像显示出显着的成像对比度改善,而没有损害分辨率。对于头颈部患者,原始的MVCT图像中难以看到的颈淋巴结和静脉在DeTECT中变得明显。对于前列腺患者,明确了原始MVCT中膀胱和前列腺之间的边界不明确。幻像低对比度插入物的CNR分别从1.48和3.8提高到13.67和16.17。对于头部和颈部患者,两个感兴趣区域的CNR分别从1.5和3.17改善到3.14和15.76。 DeTECT还使四名前列腺患者的前列腺CNR从0.13增加到1.46。结论显着优于采用各向异性扩散的局部去噪方法。结论:作者表明,使用非局部均值3D块匹配方法结合显着性图,从嘈杂的MVCT图像中提取更多的软组织对比度信息是可行的,这表明原本人类观察者无法感知的信息。 C 2014美国医学物理学会。

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