Explainable Anatomical Shape Analysis through Deep Hierarchical Generative Models

doi:doi:10.57702/0ksa9lcn

Explainable Anatomical Shape Analysis through Deep Hierarchical Generative Models

A new deep learning approach to learn a hierarchy of conditional latent variables that models a population of anatomical segmentations of interest, enables the classification of distinct clinical conditions, and visualizes the anatomical variability encoded by the learned latent space.

BibTex:

@dataset{Carlo_Bifﬁ_and_Juan_J_Cerrolaza_and_Giacomo_Tarroni_and_Wenjia_Bai_and_Antonio_de_Marvao_and_Ozan_Oktay_and_Christian_Ledig_and_Loic_Le_Folgoc_and_Konstantinos_Kamnitsas_and_Georgia_Doumou_and_Jinming_Duan_and_Sanjay_K_Prasad_and_Stuart_A_Cook_and_Declan_P_O’Regan_and_Daniel_Rueckert_2024,
    abstract = {A new deep learning approach to learn a hierarchy of conditional latent variables that models a population of anatomical segmentations of interest, enables the classification of distinct clinical conditions, and visualizes the anatomical variability encoded by the learned latent space.},
    author = {Carlo Bifﬁ and Juan J. Cerrolaza and Giacomo Tarroni and Wenjia Bai and Antonio de Marvao and Ozan Oktay and Christian Ledig and Loic Le Folgoc and Konstantinos Kamnitsas and Georgia Doumou and Jinming Duan and Sanjay K. Prasad and Stuart A. Cook and Declan P. O’Regan and Daniel Rueckert},
    doi = {10.57702/0ksa9lcn},
    institution = {No Organization},
    keyword = {'anatomical shape analysis', 'deep hierarchical generative models', 'medical imaging', 'shape analysis'},
    month = {dec},
    publisher = {TIB},
    title = {Explainable Anatomical Shape Analysis through Deep Hierarchical Generative Models},
    url = {https://service.tib.eu/ldmservice/dataset/explainable-anatomical-shape-analysis-through-deep-hierarchical-generative-models},
    year = {2024}
}