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Automated lymph node detection and classification on breast and prostate cancer SPECT-CT images

机译:乳腺癌和前列腺癌SPECT-CT图像自动淋巴结检测和分类

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We present a novel detection and classification method to process SPECT-CT images representing breast and prostate lymph nodes. Lymph nodes are those nodes that are near the primer tumor and may become cancerous in time, hence their early detection is a key factor for the successful treatment of the patient. Prior methods focus on the visual aid to manually detect the lymph nodes which still makes the process time-consuming. Other solutions segment the lymph nodes only on CT, where the small lymph nodes may not be located accurately. Our solution processed both SPECT and CT data to provide an accurate classification of all SPECT hot spots. The method has been validated on a huge amount of medical data. Results show that our method is a very effective tool to support physicians working with related images in the field of nuclear medicine.
机译:我们提出了一种新的检测和分类方法来处理代表乳房和前列腺淋巴结的SPECT-CT图像。淋巴结是那些在底漆肿瘤附近的节点,并且可能随时癌症癌,因此他们的早期检测是成功治疗患者的关键因素。先前的方法专注于视觉辅助,以手动检测仍然使过程耗时的淋巴结。其他解决方案仅在CT上段,其中小淋巴结可能不准确地定位。我们的解决方案处理了SPECT和CT数据,以提供所有SPECT热点的准确分类。该方法已在大量的医疗数据上验证。结果表明,我们的方法是支持在核医学领域使用相关图像的医生的一个非常有效的工具。

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