3D Virtual Pancreatography.
3D Virtual Pancreatography.
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DOI：
10.1109/tvcg.2020.3020958
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发表时间：
2022-03
影响因子：
5.2
通讯作者：
Kaufman AE
中科院分区：
文献类型：
--
作者：
Jadhav S;Dmitriev K;Marino J;Barish M;Kaufman AE
本文提出了一种新的可视化技术--三维虚拟胰腺成像(VP)，并将其应用于胰腺癌的前驱病变--胰腺病变的非侵入性诊断和分类。目前，对患者的非侵入性筛查是通过对2D轴向CT图像的视觉检查来执行的，尽管相关特征通常不清楚可见或自动检测。VP是一个端到端的视觉诊断系统，它包括：基于机器学习的胰腺和病变的自动分割，半自动提取主胰管的方法，基于机器学习的病变分为四种突出类型的自动分类，以及胰腺、病变和周围解剖的专门3D和2D探索性可视化。我们将体积再现与以胰腺和病变为中心的可视化和测量相结合，以实现有效的诊断。我们通过密切合作和专家放射科医生的反馈设计了VP，并在多个真实世界的CT数据集上进行了评估，这些数据集包括各种胰腺病变和专家放射科医生检查的案例研究。
We present 3D virtual pancreatography (VP), a novel visualization procedure and application for non-invasive diagnosis and classification of pancreatic lesions, the precursors of pancreatic cancer. Currently, non-invasive screening of patients is performed through visual inspection of 2D axis-aligned CT images, though the relevant features are often not clearly visible nor automatically detected. VP is an end-to-end visual diagnosis system that includes: a machine learning based automatic segmentation of the pancreatic gland and the lesions, a semi-automatic approach to extract the primary pancreatic duct, a machine learning based automatic classification of lesions into four prominent types, and specialized 3D and 2D exploratory visualizations of the pancreas, lesions and surrounding anatomy. We combine volume rendering with pancreas- and lesion-centric visualizations and measurements for effective diagnosis. We designed VP through close collaboration and feedback from expert radiologists, and evaluated it on multiple real-world CT datasets with various pancreatic lesions and case studies examined by the expert radiologists.