Cargando…
A review on lung boundary detection in chest X-rays
PURPOSE: Chest radiography is the most common imaging modality for pulmonary diseases. Due to its wide usage, there is a rich literature addressing automated detection of cardiopulmonary diseases in digital chest X-rays (CXRs). One of the essential steps for automated analysis of CXRs is localizing...
Autores principales: | Candemir, Sema, Antani, Sameer |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Springer International Publishing
2019
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6420899/ https://www.ncbi.nlm.nih.gov/pubmed/30730032 http://dx.doi.org/10.1007/s11548-019-01917-1 |
Ejemplares similares
-
Visualization and Interpretation of Convolutional Neural Network Predictions in Detecting Pneumonia in Pediatric Chest Radiographs
por: Rajaraman, Sivaramakrishnan, et al.
Publicado: (2018) -
Weakly Labeled Data Augmentation for Deep Learning: A Study on COVID-19 Detection in Chest X-Rays
por: Rajaraman, Sivaramakrishnan, et al.
Publicado: (2020) -
Training deep learning algorithms with weakly labeled pneumonia chest X-ray data for COVID-19 detection
por: Rajaraman, Sivaramakrishnan, et al.
Publicado: (2020) -
A Deep Modality-Specific Ensemble for Improving Pneumonia Detection in Chest X-rays
por: Rajaraman, Sivaramakrishnan, et al.
Publicado: (2022) -
Detecting Tuberculosis-Consistent Findings in Lateral Chest X-Rays Using an Ensemble of CNNs and Vision Transformers
por: Rajaraman, Sivaramakrishnan, et al.
Publicado: (2022)