Cargando…
Deep Learning for the Automatic Diagnosis and Analysis of Bone Metastasis on Bone Scintigrams
OBJECTIVE: To develop an approach for automatically analyzing bone metastases (BMs) on bone scintigrams based on deep learning technology. METHODS: This research included a bone scan classification model, a regional segmentation model, an assessment model for tumor burden and a diagnostic report gen...
Autores principales: | Liu, Simin, Feng, Ming, Qiao, Tingting, Cai, Haidong, Xu, Kele, Yu, Xiaqing, Jiang, Wen, Lv, Zhongwei, Wang, Yin, Li, Dan |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Dove
2022
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8740774/ https://www.ncbi.nlm.nih.gov/pubmed/35018121 http://dx.doi.org/10.2147/CMAR.S340114 |
Ejemplares similares
-
Deep learning for intelligent diagnosis in thyroid scintigraphy
por: Qiao, Tingting, et al.
Publicado: (2021) -
Automatic differentiation of thyroid scintigram by deep convolutional neural network: a dual center study
por: Yang, Pei, et al.
Publicado: (2021) -
Automated measurement of bone scan index from a whole-body bone scintigram
por: Shimizu, Akinobu, et al.
Publicado: (2019) -
Computer-aided diagnosis system for bone scintigrams from Japanese patients: importance of training database
por: Horikoshi, Hiroyuki, et al.
Publicado: (2012) -
Correction to: Automated measurement of bone scan index from a whole-body bone scintigram
por: Shimizu, Akinobu, et al.
Publicado: (2020)