@inproceedings{b30c9c14520e46ee99fd8399619ca31a,
title = "Detecting aggressive papillary thyroid carcinoma using hyperspectral imaging and radiomic features",
abstract = "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.",
keywords = "Head, Hyperspectral Imaging, Neck Cancer, Radiomics, Tissues, Tumor Aggression",
author = "Ka'Toria Leitch and Martin Halicek and Maysam Shahedi and Little, {James V.} and Chen, {Amy Y.} and Baowei Fei",
note = "Publisher Copyright: {\textcopyright} 2022 SPIE.; Medical Imaging 2022: Computer-Aided Diagnosis ; Conference date: 21-03-2022 Through 27-03-2022",
year = "2022",
doi = "10.1117/12.2611842",
language = "English (US)",
series = "Progress in Biomedical Optics and Imaging - Proceedings of SPIE",
publisher = "SPIE",
editor = "Karen Drukker and Iftekharuddin, {Khan M.}",
booktitle = "Medical Imaging 2022",
}