TY - GEN
T1 - 3D Slicer Craniomaxillofacial Modules Support Patient-Specific Decision-Making for Personalized Healthcare in Dental Research
AU - Bianchi, Jonas
AU - Paniagua, Beatriz
AU - De Oliveira Ruellas, Antonio Carlos
AU - Fillion-Robin, Jean Christophe
AU - Prietro, Juan C.
AU - Gonçalves, João Roberto
AU - Hoctor, James
AU - Yatabe, Marília
AU - Styner, Martin
AU - Li, Teng Fei
AU - Gurgel, Marcela Lima
AU - Chaves Junior, Cauby Maia
AU - Massaro, Camila
AU - Garib, Daniela Gamba
AU - Vilanova, Lorena
AU - Henriques, Jose Fernando Castanha
AU - Castillo, Aron Aliaga Del
AU - Janson, Guilherme
AU - Iwasaki, Laura R.
AU - Nickel, Jeffrey C.
AU - Evangelista, Karine
AU - Cevidanes, Lucia
N1 - Publisher Copyright:
© 2020, Springer Nature Switzerland AG.
PY - 2020
Y1 - 2020
N2 - 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.
AB - 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.
KW - Craniomaxillofacial diseases
KW - Data analytics
KW - Data management
KW - Dental research
KW - Personalized medicine
UR - http://www.scopus.com/inward/record.url?scp=85092628965&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85092628965&partnerID=8YFLogxK
U2 - 10.1007/978-3-030-60946-7_5
DO - 10.1007/978-3-030-60946-7_5
M3 - Conference contribution
AN - SCOPUS:85092628965
SN - 9783030609450
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 44
EP - 53
BT - Multimodal Learning for Clinical Decision Support and Clinical Image-Based Procedures - 10th International Workshop, ML-CDS 2020, and 9th International Workshop, CLIP 2020, Held in Conjunction with MICCAI 2020, Proceedings
A2 - Syeda-Mahmood, Tanveer
A2 - Drechsler, Klaus
A2 - Greenspan, Hayit
A2 - Madabhushi, Anant
A2 - Karargyris, Alexandros
A2 - Oyarzun Laura, Cristina
A2 - Wesarg, Stefan
A2 - Linguraru, Marius George
A2 - Shekhar, Raj
A2 - Erdt, Marius
A2 - González Ballester, Miguel Ángel
PB - Springer Science and Business Media Deutschland GmbH
T2 - 10th International Workshop on Multimodal Learning for Clinical Decision Support, ML-CDS 2020, and the 9th International Workshop on Clinical Image-Based Procedures, CLIP 2020, held in conjunction with the 23rd International Conference on Medical Image Computing and Computer Assisted Intervention, MICCAI 2020
Y2 - 4 October 2020 through 8 October 2020
ER -