Cargando…
Bladder Cancer Segmentation in CT for Treatment Response Assessment: Application of Deep-Learning Convolution Neural Network—A Pilot Study
Assessing the response of bladder cancer to neoadjuvant chemotherapy is crucial for reducing morbidity and increasing quality of life of patients. Changes in tumor volume during treatment is generally used to predict treatment outcome. We are developing a method for bladder cancer segmentation in CT...
Autores principales: | Cha, Kenny H., Hadjiiski, Lubomir M., Samala, Ravi K., Chan, Heang-Ping, Cohan, Richard H., Caoili, Elaine M., Paramagul, Chintana, Alva, Ajjai, Weizer, Alon Z. |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Grapho Publications, LLC
2016
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5241049/ https://www.ncbi.nlm.nih.gov/pubmed/28105470 http://dx.doi.org/10.18383/j.tom.2016.00184 |
Ejemplares similares
-
Bladder Cancer Treatment Response Assessment in CT using Radiomics with Deep-Learning
por: Cha, Kenny H., et al.
Publicado: (2017) -
Deep Learning Approach for Assessment of Bladder Cancer Treatment Response
por: Wu, Eric, et al.
Publicado: (2019) -
Intraobserver Variability in Bladder Cancer Treatment Response Assessment With and Without Computerized Decision Support
por: Hadjiiski, Lubomir M., et al.
Publicado: (2020) -
Survival Prediction of Patients with Bladder Cancer after Cystectomy Based on Clinical, Radiomics, and Deep-Learning Descriptors
por: Sun, Di, et al.
Publicado: (2023) -
Computerized Decision Support for Bladder Cancer Treatment Response Assessment in CT Urography: Effect on Diagnostic Accuracy in Multi-Institution Multi-Specialty Study
por: Sun, Di, et al.
Publicado: (2022)