Actas de congresos
3D Slicer Craniomaxillofacial Modules Support Patient-Specific Decision-Making for Personalized Healthcare in Dental Research
Fecha
2020-01-01Registro en:
Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), v. 12445 LNCS, p. 44-53.
1611-3349
0302-9743
10.1007/978-3-030-60946-7_5
2-s2.0-85092628965
Autor
University of Michigan
Kitware Incorporation
University of North Carolina
Universidade Estadual Paulista (UNESP)
Federal University of Ceara
Universidade de São Paulo (USP)
Oregon Health & Science University
Federal University of Goias
Institución
Resumen
The biggest challenge to improve the diagnosis and therapies of Craniomaxillofacial conditions is to translate algorithms and software developments towards the creation of holistic patient models. A complete picture of the individual patient for treatment planning and personalized healthcare requires a compilation of clinician-friendly algorithms to provide minimally invasive diagnostic techniques with multimodal image integration and analysis. We describe here the implementation of the open-source Craniomaxillofacial module of the 3D Slicer software, as well as its clinical applications. This paper proposes data management approaches for multisource data extraction, registration, visualization, and quantification. These applications integrate medical images with clinical and biological data analytics, user studies, and other heterogeneous data.