Detecting Pancreatic Ductal Adenocarcinoma in Multi-phase CT Scans via Alignment Ensemble

• URL: http://arxiv.org/abs/2003.08441v3
• Date: Wed, 1 Jul 2020 19:34:38 GMT
• Title: Detecting Pancreatic Ductal Adenocarcinoma in Multi-phase CT Scans via Alignment Ensemble
• Authors: Yingda Xia, Qihang Yu, Wei Shen, Yuyin Zhou, Elliot K. Fishman, Alan L. Yuille
• Abstract summary: Pancreatic ductal adenocarcinoma (PDAC) is one of the most lethal cancers among the population. Multiple phases provide more information than single phase, but they are unaligned and inhomogeneous in texture. We suggest an ensemble of all these alignments as a promising way to boost the performance of PDAC detection.
• Score: 77.5625174267105
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• Abstract: Pancreatic ductal adenocarcinoma (PDAC) is one of the most lethal cancers among the population. Screening for PDACs in dynamic contrast-enhanced CT is beneficial for early diagnosis. In this paper, we investigate the problem of automated detecting PDACs in multi-phase (arterial and venous) CT scans. Multiple phases provide more information than single phase, but they are unaligned and inhomogeneous in texture, making it difficult to combine cross-phase information seamlessly. We study multiple phase alignment strategies, i.e., early alignment (image registration), late alignment (high-level feature registration), and slow alignment (multi-level feature registration), and suggest an ensemble of all these alignments as a promising way to boost the performance of PDAC detection. We provide an extensive empirical evaluation on two PDAC datasets and show that the proposed alignment ensemble significantly outperforms previous state-of-the-art approaches, illustrating the strong potential for clinical use.

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