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Adaptive Enhancement and Visualization Techniques for 3D Terahertz Images of Breast Cancer Tumors

机译:乳腺癌肿瘤的3D太赫兹图像的自适应增强和可视化技术

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This paper evaluates image enhancement and visualization techniques for pulsed terahertz (THz) images of tissue samples. Specifically, our research objective is to effectively differentiate between heterogeneous regions of breast tissues that contain tumors diagnosed as triple negative infiltrating ductal carcinoma (IDC). Tissue slices and blocks of varying thicknesses were prepared and scanned using our lab's THz pulsed imaging system. One of the challenges we have encountered in visualizing the obtained images and differentiating between healthy and cancerous regions of the tissues is that most THz images have a low level of details and narrow contrast, making it difficult to accurately identify and visualize the margins around the IDC. To overcome this problem, we have applied and evaluated a number of image processing techniques to the scanned 3D THz images. In particular, we employed various spatial filtering and intensity transformation techniques to emphasize the small details in the images and adjust the image contrast. For each of these methods, we investigated how varying filter sizes and parameters affect the amount of enhancement applied to the images. Our experimentation shows that several image processing techniques are effective in producing THz images of breast tissue samples that contain distinguishable details, making further segmentation of the different image regions promising.
机译:本文评估了组织样本的脉冲太赫兹(THz)图像的图像增强和可视化技术。具体而言,我们的研究目标是有效地区分包含诊断为三阴性浸润性导管癌(IDC)的肿瘤的乳腺组织异质区域。使用我们实验室的THz脉冲成像系统准备并扫描厚度不同的组织切片和块。我们在可视化获得的图像以及区分组织的健康区域和癌性区域时遇到的挑战之一是大多数THz图像的细节水平较低且对比度较窄,从而难以准确识别和可视化IDC周围的边缘。为克服此问题,我们已对扫描的3D THz图像应用并评估了多种图像处理技术。特别是,我们采用了各种空间滤波和强度变换技术来强调图像中的小细节并调整图像对比度。对于每种方法,我们研究了变化的滤镜大小和参数如何影响应用于图像的增强量。我们的实验表明,几种图像处理技术可以有效地产生包含可区分细节的乳腺组织样品的太赫兹图像,从而进一步分割不同的图像区域很有希望。

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