Deep negative volume segmentation
Abstract Clinical examination of three-dimensional image data of compound anatomical objects, such as complex joints, remains a tedious process, demanding the time and the expertise of physicians. For instance, automation of the segmentation task of the TMJ (temporomandibular joint) has been hindere...
Guardado en:
Autores principales: | Kristina Belikova, Oleg Y. Rogov, Aleksandr Rybakov, Maxim V. Maslov, Dmitry V. Dylov |
---|---|
Formato: | article |
Lenguaje: | EN |
Publicado: |
Nature Portfolio
2021
|
Materias: | |
Acceso en línea: | https://doaj.org/article/facf56d5699a455aaece8a3512fb8e38 |
Etiquetas: |
Agregar Etiqueta
Sin Etiquetas, Sea el primero en etiquetar este registro!
|
Ejemplares similares
-
Automatic Segmentation of Kidneys using Deep Learning for Total Kidney Volume Quantification in Autosomal Dominant Polycystic Kidney Disease
por: Kanishka Sharma, et al.
Publicado: (2017) -
Harnessing clinical annotations to improve deep learning performance in prostate segmentation.
por: Karthik V Sarma, et al.
Publicado: (2021) -
Automated Training of Deep Convolutional Neural Networks for Cell Segmentation
por: Sajith Kecheril Sadanandan, et al.
Publicado: (2017) -
Fully automatic wound segmentation with deep convolutional neural networks
por: Chuanbo Wang, et al.
Publicado: (2020) -
Deep Learning-Augmented Head and Neck Organs at Risk Segmentation From CT Volumes
por: Wei Wang, et al.
Publicado: (2021)