高光谱成像
无线电技术
甲状腺癌
医学
放射科
甲状腺
恶性肿瘤
癌
人工智能
作者
Ka'Toria Leitch,Martin Halicek,Maysam Shahedi,James V. Little,Amy Y. Chen,Baowei Fei
摘要
Hyperspectral imaging (HSI) and radiomics have the potential to improve the accuracy of tumor malignancy prediction and assessment. In this work, we extracted radiomic features of fresh surgical papillary thyroid carcinoma (PTC) specimen that were imaged with HSI. A total of 107 unique radiomic features were extracted. This study includes 72 ex-vivo tissue specimens from 44 patients with pathology-confirmed PTC. With the dilated hyperspectral images, the shape feature of least axis length was able to predict the tumor aggressiveness with a high accuracy. The HSI-based radiomic method may provide a useful tool to aid oncologists in determining tumors with intermediate to high risk and in clinical decision making.
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