Cargando…
LungINFseg: Segmenting COVID-19 Infected Regions in Lung CT Images Based on a Receptive-Field-Aware Deep Learning Framework
COVID-19 is a fast-growing disease all over the world, but facilities in the hospitals are restricted. Due to unavailability of an appropriate vaccine or medicine, early identification of patients suspected to have COVID-19 plays an important role in limiting the extent of disease. Lung computed tom...
Autores principales: | Kumar Singh, Vivek, Abdel-Nasser, Mohamed, Pandey, Nidhi, Puig, Domenec |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2021
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7910858/ https://www.ncbi.nlm.nih.gov/pubmed/33498999 http://dx.doi.org/10.3390/diagnostics11020158 |
Ejemplares similares
-
Effective Approaches to Fetal Brain Segmentation in MRI and Gestational Age Estimation by Utilizing a Multiview Deep Inception Residual Network and Radiomics
por: Mazher, Moona, et al.
Publicado: (2022) -
Fully Automated Breast Density Segmentation and Classification Using Deep Learning
por: Saffari, Nasibeh, et al.
Publicado: (2020) -
Discriminative Random Field Segmentation of Lung Nodules in CT Studies
por: Liu, Brian, et al.
Publicado: (2013) -
Predicting Breast Tumor Malignancy Using Deep ConvNeXt Radiomics and Quality-Based Score Pooling in Ultrasound Sequences
por: Hassanien, Mohamed A., et al.
Publicado: (2022) -
ResBCDU-Net: A Deep Learning Framework for Lung CT Image Segmentation
por: Jalali, Yeganeh, et al.
Publicado: (2021)