most citedDeep Learning-based Radiomic Features for Improving Neoadjuvant Chemoradiation Response Prediction in Locally Advanced Rectal Cancer

57 citations · 57 across the 1 of their papers we have counts for

collaborators

1 paper

physics.med-ph2019★ 57 cited

Deep Learning-based Radiomic Features for Improving Neoadjuvant Chemoradiation Response Prediction in Locally Advanced Rectal Cancer

Jie Fu, Xinran Zhong, Ning Li +6

Radiomic features achieve promising results in cancer diagnosis, treatment response prediction, and survival prediction. Our goal is to compare the handcrafted (explicitly designed…