A review of medical image data augmentation techniques for deep learning applications
Research in artificial intelligence for radiology and radiotherapy has recently become
increasingly reliant on the use of deep learning‐based algorithms. While the performance of …
increasingly reliant on the use of deep learning‐based algorithms. While the performance of …
Data augmentation for medical imaging: A systematic literature review
Abstract Recent advances in Deep Learning have largely benefited from larger and more
diverse training sets. However, collecting large datasets for medical imaging is still a …
diverse training sets. However, collecting large datasets for medical imaging is still a …
Data augmentation for brain-tumor segmentation: a review
Data augmentation is a popular technique which helps improve generalization capabilities
of deep neural networks, and can be perceived as implicit regularization. It plays a pivotal …
of deep neural networks, and can be perceived as implicit regularization. It plays a pivotal …
A multi-objective semantic segmentation algorithm based on improved U-Net networks
X Hao, L Yin, X Li, L Zhang, R Yang - Remote Sensing, 2023 - mdpi.com
The construction of transport facilities plays a pivotal role in enhancing people's living
standards, stimulating economic growth, maintaining social stability and bolstering national …
standards, stimulating economic growth, maintaining social stability and bolstering national …
Fully-automated deep learning-powered system for DCE-MRI analysis of brain tumors
Dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) plays an important
role in diagnosis and grading of brain tumors. Although manual DCE biomarker extraction …
role in diagnosis and grading of brain tumors. Although manual DCE biomarker extraction …
Deep learning automates bidimensional and volumetric tumor burden measurement from MRI in pre-and post-operative glioblastoma patients
Tumor burden assessment by magnetic resonance imaging (MRI) is central to the evaluation
of treatment response for glioblastoma. This assessment is, however, complex to perform …
of treatment response for glioblastoma. This assessment is, however, complex to perform …
Principled ultrasound data augmentation for classification of standard planes
Deep learning models with large learning capacities often overfit to medical imaging
datasets. This is because training sets are often relatively small due to the significant time …
datasets. This is because training sets are often relatively small due to the significant time …
[HTML][HTML] Labeling lateral prefrontal sulci using spherical data augmentation and context-aware training
The inference of cortical sulcal labels often focuses on deep (primary and secondary) sulcal
regions, whereas shallow (tertiary) sulcal regions are largely overlooked in the literature due …
regions, whereas shallow (tertiary) sulcal regions are largely overlooked in the literature due …
Spherical coordinates transformation pre-processing in Deep Convolution Neural Networks for brain tumor segmentation in MRI
Abstract Magnetic Resonance Imaging (MRI) is used in everyday clinical practice to assess
brain tumors. Deep Convolutional Neural Networks (DCNN) have recently shown very …
brain tumors. Deep Convolutional Neural Networks (DCNN) have recently shown very …
Developing precision agriculture using data augmentation framework for automatic identification of castor insect pests
Nitin, SB Gupta, RK Yadav, F Bovand… - Frontiers in Plant …, 2023 - frontiersin.org
Castor (Ricinus communis L.) is an important nonedible industrial crop that produces oil,
which is used in the production of medicines, lubricants, and other products. However, the …
which is used in the production of medicines, lubricants, and other products. However, the …