局部晚期乳腺癌患者超声图像中肿瘤ROI的Radon条形码估计
Tumour ROI Estimation in Ultrasound Images via Radon Barcodes in Patients with Locally Advanced Breast Cancer
摘要：
定量超声（QUS）方法提供了一个有前途的框架，可以非侵入性和廉价地用于预测或评估肿瘤对癌症治疗的反应。使用QUS方法的第一步是在超声图像中选择肿瘤内部的感兴趣区域（ROI）。然而，手动分割是非常耗时和繁琐的。在本文中，将提出一种半自动化的方法来粗略定位局部晚期乳腺癌（LABC）患者的超声图像中的肿瘤的ROI。基于内容的条形码是最近引入的基于Radon变换的二进制描述符，用于查找类似病例并估计肿瘤周围的限界框。33 B扫描图像的实验结果与$81\%$的准确性有希望的结果。
英文摘要：
Quantitative ultrasound (QUS) methods provide a promising framework that can non-invasively and inexpensively be used to predict or assess the tumour response to cancer treatment. The first step in using the QUS methods is to select a region of interest (ROI) inside the tumour in ultrasound images. Manual segmentation, however, is very time consuming and tedious. In this paper, a semi-automated approach will be proposed to roughly localize an ROI for a tumour in ultrasound images of patients with locally advanced breast cancer (LABC). Content-based barcodes, a recently introduced binary descriptor based on Radon transform, were used in order to find similar cases and estimate a bounding box surrounding the tumour. Experiments with 33 B-scan images resulted in promising results with an accuracy of $81\%$.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
