Carregant...
Tipus de document
Part del llibreVersió
Versió publicadaData de publicació
Llicència de publicació
Si us plau utilitzeu sempre aquest identificador per citar o enllaçar aquest document: https://hdl.handle.net/2445/219442
Landmark anything: multi-view consensus convolutional networks applied to the 3D landmarking of Anatomical Structures
Títol de la revista
Director/Tutor
ISSN de la revista
Títol del volum
Recurs relacionat
Resum
As shape alterations in three-dimensional biological structures are as-
sociated to numerous pathological processes, quantitative shape analysis for obtaining phenotypic biomarkers of diagnostic potential has become a prominent research area. In this context, the automatic detection of landmarks on 3D anatomical structures is crucial for developing high-throughput phenotyping tools. This study evaluates the performance of multi-view consensus convolutional networks -originally developed for facial landmarking– in automatically detecting landmarks on three different 3D anatomical structures: the face, the upper respiratory airways and the brain hippocampi. Leveraging magnetic resonance imaging datasets, we trained multiple models and assessed their accuracy against manual annotations,
while analyzing the impact of different network hyperparameters on the results.
Matèries (anglès)
Citació
Citació
HEREDIA LIDÓN, Álvaro, GARCÍA MASCAREL, Christian, ECHEVERRY, Luis miguel, HERRERA ESCARTÍN, Daniel, FORTEA ORMAECHEA, Juan, POMAROL-CLOTET, Edith, FATJÓ-VILAS MESTRE, Mar, MARTÍNEZ ABADÍAS, Neus, SEVILLANO, Xavier. Landmark anything: multi-view consensus convolutional networks applied to the 3D landmarking of Anatomical Structures. _Capítol del llibre: Alsinet_. Teresa. Vol. Vilasís, núm. Xavier, pàgs. García. [consulta: 1 de gener de 2026]. [Disponible a: https://hdl.handle.net/2445/219442]