SeqSeg: A sequential method to achieve nasopharyngeal carcinoma segmentation free from background dominance

• Main Authors: TAO, Guihua, LI, Haojiang, HUANG, Jiabin, HAN, Chu, CHEN, Jiazhou, RUAN, Guangying, HUANG, Wenjie, HU, Yu, DAN, Tingting, ZHANG, Bin, Shengfeng HE
• Format: text
• Language: English
• Published: Institutional Knowledge at Singapore Management University 2022
• Subjects: Nasopharyngeal carcinoma; Background dominance; NPC Detection and segmentation; Deep Q-learning; Recurrent attention; Information Security
• Online Access: https://ink.library.smu.edu.sg/sis_research/7840; https://ink.library.smu.edu.sg/context/sis_research/article/8843/viewcontent/Seq.pdf
• Institution: Singapore Management University

Reliable nasopharyngeal carcinoma (NPC) segmentation plays an important role in radiotherapy planning. However, recent deep learning methods fail to achieve satisfactory NPC segmentation in magnetic resonance (MR) images, since NPC is infiltrative and typically has a small or even tiny volume with i...