Cargando…
A Perlin Noise-Based Augmentation Strategy for Deep Learning with Small Data Samples of HRCT Images
Deep learning is now widely used as an efficient tool for medical image classification and segmentation. However, conventional machine learning techniques are still more accurate than deep learning when only a small dataset is available. In this study, we present a general data augmentation strategy...
Autores principales: | Bae, Hyun-Jin, Kim, Chang-Wook, Kim, Namju, Park, BeomHee, Kim, Namkug, Seo, Joon Beom, Lee, Sang Min |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group UK
2018
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6283833/ https://www.ncbi.nlm.nih.gov/pubmed/30523268 http://dx.doi.org/10.1038/s41598-018-36047-2 |
Ejemplares similares
-
Simulation of Laser Profilometer Measurements in the Presence of Speckle Using Perlin Noise
por: Roos-Hoefgeest, Sara, et al.
Publicado: (2023) -
Comparison of Usual Interstitial Pneumonia and Nonspecific Interstitial Pneumonia: Quantification of Disease Severity and Discrimination between Two Diseases on HRCT Using a Texture-Based Automated System
por: Park, Sang Ok, et al.
Publicado: (2011) -
Content-Based Image Retrieval of Chest CT with Convolutional Neural Network for Diffuse Interstitial Lung Disease: Performance Assessment in Three Major Idiopathic Interstitial Pneumonias
por: Hwang, Hye Jeon, et al.
Publicado: (2021) -
A Curriculum Learning Strategy to Enhance the Accuracy of Classification of Various Lesions in Chest-PA X-ray Screening for Pulmonary Abnormalities
por: Park, Beomhee, et al.
Publicado: (2019) -
Deep Learning in Medical Imaging: General Overview
por: Lee, June-Goo, et al.
Publicado: (2017)