Learning from Ambiguous Labels for Lung Nodule Malignancy Prediction
Sign Up to like & getrecommendations! Published in 2022 at "IEEE transactions on medical imaging"
DOI: 10.1109/tmi.2022.3149344
Abstract: Lung nodule malignancy prediction is an essential step in the early diagnosis of lung cancer. Besides the difficulties commonly discussed, the challenges of this task also come from the ambiguous labels provided by annotators, since… read more here.
Keywords: nodule malignancy; malignancy prediction; set set; prediction ... See more keywords
A Comparative Study of Radiomics and Deep-Learning Based Methods for Pulmonary Nodule Malignancy Prediction in Low Dose CT Images
Sign Up to like & getrecommendations! Published in 2021 at "Frontiers in Oncology"
DOI: 10.3389/fonc.2021.737368
Abstract: Objectives Both radiomics and deep learning methods have shown great promise in predicting lesion malignancy in various image-based oncology studies. However, it is still unclear which method to choose for a specific clinical problem given… read more here.
Keywords: deep learning; feature; malignancy; nodule malignancy ... See more keywords