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Wavelet-Based 3D Reconstruction of Microcalcification Clusters from Two Mammographic Views: New Evidence That Fractal Tumors Are Malignant and Euclidean Tumors Are Benign

机译:从两种乳腺X线摄影术的观点出发基于小波的3D重建微钙化簇:分形肿瘤为恶性而欧氏肿瘤为良性的新证据

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摘要

The 2D Wavelet-Transform Modulus Maxima (WTMM) method was used to detect microcalcifications (MC) in human breast tissue seen in mammograms and to characterize the fractal geometry of benign and malignant MC clusters. This was done in the context of a preliminary analysis of a small dataset, via a novel way to partition the wavelet-transform space-scale skeleton. For the first time, the estimated 3D fractal structure of a breast lesion was inferred by pairing the information from two separate 2D projected mammographic views of the same breast, i.e. the cranial-caudal (CC) and mediolateral-oblique (MLO) views. As a novelty, we define the “CC-MLO fractal dimension plot”, where a “fractal zone” and “Euclidean zones” (non-fractal) are defined. 118 images (59 cases, 25 malignant and 34 benign) obtained from a digital databank of mammograms with known radiologist diagnostics were analyzed to determine which cases would be plotted in the fractal zone and which cases would fall in the Euclidean zones. 92% of malignant breast lesions studied (23 out of 25 cases) were in the fractal zone while 88% of the benign lesions were in the Euclidean zones (30 out of 34 cases). Furthermore, a Bayesian statistical analysis shows that, with 95% credibility, the probability that fractal breast lesions are malignant is between 74% and 98%. Alternatively, with 95% credibility, the probability that Euclidean breast lesions are benign is between 76% and 96%. These results support the notion that the fractal structure of malignant tumors is more likely to be associated with an invasive behavior into the surrounding tissue compared to the less invasive, Euclidean structure of benign tumors. Finally, based on indirect 3D reconstructions from the 2D views, we conjecture that all breast tumors considered in this study, benign and malignant, fractal or Euclidean, restrict their growth to 2-dimensional manifolds within the breast tissue.
机译:二维小波变换模量最大值(WTMM)方法用于检测乳房X线照片中可见的人乳房组织中的微钙化(MC),并表征良性和恶性MC团簇的分形几何形状。这是在对小数据集进行初步分析的情况下完成的,它是通过一种新颖的方法来划分小波变换的空间比例骨架。第一次,通过对来自同一乳房的两个单独的2D投影乳腺X线照片的信息进行配对,推断出乳腺病变的估计3D分形结构,即颅尾(CC)和中外侧斜(MLO)视图。作为一种新颖性,我们定义了“ CC-MLO分形维数图”,其中定义了“分形区域”和“欧几里得区域”(非分形)。分析了从具有已知放射科医生诊断的乳房X线照片的数字数据库中获得的118幅图像(59例,25例恶性25例,良性34例),以确定哪些病例将在分形区内绘制,哪些病例将落在欧几里得地区。研究的92%的恶性乳腺病变(25例中的23例)位于分形区,而良性病变的88%位于欧几里得区(34例中的30例)。此外,贝叶斯统计分析表明,以95%的可信度,分形乳腺病变为恶性的可能性在74%至98%之间。备选地,具有95%的可信度,欧几里得乳腺病变为良性的可能性在76%至96%之间。这些结果支持以下观点:与良性肿瘤的侵入性较小的欧几里得结构相比,恶性肿瘤的分形结构更可能与对周围组织的侵入行为有关。最后,基于从2D角度进行的间接3D重建,我们推测本研究中考虑的所有乳腺肿瘤(良性和恶性,分形或欧几里得)都将其生长限制在乳腺组织内的二维歧管上。

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