3D Virtual Pancreatography
| Autor: | Konstantin Dmitriev, Shreeraj Jadhav, Joseph Marino, Matthew A. Barish, Arie E. Kaufman |
|---|---|
| Rok vydání: | 2022 |
| Předmět: |
Pancreatic duct
medicine.medical_specialty Computer science medicine.disease Computer Graphics and Computer-Aided Design Article Visualization Machine Learning Pancreatic Neoplasms medicine.anatomical_structure Pancreatic cancer Signal Processing Computer Graphics medicine Humans Computer Vision and Pattern Recognition Radiology Tomography X-Ray Computed Pancreas Software |
| Zdroj: | IEEE Trans Vis Comput Graph |
| ISSN: | 2160-9306 1077-2626 |
| DOI: | 10.1109/tvcg.2020.3020958 |
| Popis: | 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. |
| Databáze: | OpenAIRE |
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