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 …
A review of deep-learning-based medical image segmentation methods
As an emerging biomedical image processing technology, medical image segmentation has
made great contributions to sustainable medical care. Now it has become an important …
made great contributions to sustainable medical care. Now it has become an important …
Medmnist v2-a large-scale lightweight benchmark for 2d and 3d biomedical image classification
We introduce MedMNIST v2, a large-scale MNIST-like dataset collection of standardized
biomedical images, including 12 datasets for 2D and 6 datasets for 3D. All images are pre …
biomedical images, including 12 datasets for 2D and 6 datasets for 3D. All images are pre …
Artificial intelligence for the detection of COVID-19 pneumonia on chest CT using multinational datasets
SA Harmon, TH Sanford, S Xu, EB Turkbey… - Nature …, 2020 - nature.com
Chest CT is emerging as a valuable diagnostic tool for clinical management of COVID-19
associated lung disease. Artificial intelligence (AI) has the potential to aid in rapid evaluation …
associated lung disease. Artificial intelligence (AI) has the potential to aid in rapid evaluation …
Rapid ai development cycle for the coronavirus (covid-19) pandemic: Initial results for automated detection & patient monitoring using deep learning ct image analysis
Purpose: Develop AI-based automated CT image analysis tools for detection, quantification,
and tracking of Coronavirus; demonstrate they can differentiate coronavirus patients from …
and tracking of Coronavirus; demonstrate they can differentiate coronavirus patients from …
MedSegDiff-V2: Diffusion-Based Medical Image Segmentation with Transformer
The Diffusion Probabilistic Model (DPM) has recently gained popularity in the field of
computer vision, thanks to its image generation applications, such as Imagen, Latent …
computer vision, thanks to its image generation applications, such as Imagen, Latent …
Development and evaluation of an artificial intelligence system for COVID-19 diagnosis
Early detection of COVID-19 based on chest CT enables timely treatment of patients and
helps control the spread of the disease. We proposed an artificial intelligence (AI) system for …
helps control the spread of the disease. We proposed an artificial intelligence (AI) system for …
Medical image segmentation using deep learning: A survey
Deep learning has been widely used for medical image segmentation and a large number of
papers has been presented recording the success of deep learning in the field. A …
papers has been presented recording the success of deep learning in the field. A …
Unet++: Redesigning skip connections to exploit multiscale features in image segmentation
The state-of-the-art models for medical image segmentation are variants of U-Net and fully
convolutional networks (FCN). Despite their success, these models have two limitations:(1) …
convolutional networks (FCN). Despite their success, these models have two limitations:(1) …
Artificial intelligence in lung cancer diagnosis and prognosis: Current application and future perspective
Lung cancer is one of the malignant tumors with the highest incidence and mortality in the
world. The overall five-year survival rate of lung cancer is relatively lower than many leading …
world. The overall five-year survival rate of lung cancer is relatively lower than many leading …