用多期CT提升门静脉期图像质量，助力胰腺分割
Leveraging Multiphase CT for Quality Enhancement of Portal Venous CT: Utility for Pancreas Segmentation
- 利用非增强、动脉和门静脉三期数据融合提升门静脉期图像质量
- 胰腺分割准确率比原始低质扫描提升3%
- 适合需要高精度医学图像分割的临床研究与AI辅助诊断
多期CT在临床中广泛用于癌症等疾病的诊断与管理，但常因辐射剂量低、设备差异及运动、金属伪影导致图像质量下降。以往方法仅针对单一时期（如非增强CT）进行质量优化。本文提出一种3D渐进式融合与非局部（PFNL）网络，利用三个低质量时期（非增强、动脉、门静脉）数据来增强门静脉期图像质量。通过胰腺分割这一代理任务评估效果，结果表明该方法使胰腺分割性能相比原始低质扫描提升3%。据我们所知，这是首个将多期CT用于扫描质量增强并提升胰腺分割的研究。
原文摘要 · Abstract (English)
Multiphase CT studies are routinely obtained in clinical practice for diagnosis and management of various diseases, such as cancer. However, the CT studies can be acquired with low radiation doses, different scanners, and are frequently affected by motion and metal artifacts. Prior approaches have targeted the quality improvement of one specific CT phase (e.g., non-contrast CT). In this work, we hypothesized that leveraging multiple CT phases for the quality enhancement of one phase may prove advantageous for downstream tasks, such as segmentation. A 3D progressive fusion and non-local (PFNL) network was developed. It was trained with three degraded (low-quality) phases (non-contrast, arterial, and portal venous) to enhance the quality of the portal venous phase. Then, the effect of scan quality enhancement was evaluated using a proxy task of pancreas segmentation, which is useful for tracking pancreatic cancer. The proposed approach improved the pancreas segmentation by 3% over the corresponding low-quality CT scan. To the best of our knowledge, we are the first to harness multiphase CT for scan quality enhancement and improved pancreas segmentation.
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