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A review on deep learning in medical image analysis
Ongoing improvements in AI, particularly concerning deep learning techniques, are
assisting to identify, classify, and quantify patterns in clinical images. Deep learning is the …
assisting to identify, classify, and quantify patterns in clinical images. Deep learning is the …
A survey on deep learning in medical image registration: New technologies, uncertainty, evaluation metrics, and beyond
Deep learning technologies have dramatically reshaped the field of medical image
registration over the past decade. The initial developments, such as regression-based and U …
registration over the past decade. The initial developments, such as regression-based and U …
On the analyses of medical images using traditional machine learning techniques and convolutional neural networks
Convolutional neural network (CNN) has shown dissuasive accomplishment on different
areas especially Object Detection, Segmentation, Reconstruction (2D and 3D), Information …
areas especially Object Detection, Segmentation, Reconstruction (2D and 3D), Information …
Image matching from handcrafted to deep features: A survey
As a fundamental and critical task in various visual applications, image matching can identify
then correspond the same or similar structure/content from two or more images. Over the …
then correspond the same or similar structure/content from two or more images. Over the …
Breaking the dilemma of medical image-to-image translation
Abstract Supervised Pix2Pix and unsupervised Cycle-consistency are two modes that
dominate the field of medical image-to-image translation. However, neither modes are ideal …
dominate the field of medical image-to-image translation. However, neither modes are ideal …
Correlation-aware coarse-to-fine mlps for deformable medical image registration
Deformable image registration is a fundamental step for medical image analysis. Recently
transformers have been used for registration and outperformed Convolutional Neural …
transformers have been used for registration and outperformed Convolutional Neural …
H-vit: A hierarchical vision transformer for deformable image registration
This paper introduces a novel top-down representation approach for deformable image
registration which estimates the deformation field by capturing various short-and long-range …
registration which estimates the deformation field by capturing various short-and long-range …
Swin-voxelmorph: A symmetric unsupervised learning model for deformable medical image registration using swin transformer
Deformable medical image registration is widely used in medical image processing with the
invertible and one-to-one map** between images. While state-of-the-art image …
invertible and one-to-one map** between images. While state-of-the-art image …
DeepLeukNet—A CNN based microscopy adaptation model for acute lymphoblastic leukemia classification
Abstract Acute Lymphoblastic Leukemia is one of the fatal types of disease which causes a
high mortality rate among children and adults. Traditional diagnosing of this disease is …
high mortality rate among children and adults. Traditional diagnosing of this disease is …
Symmetric transformer-based network for unsupervised image registration
Medical image registration is a fundamental and critical task in medical image analysis. With
the rapid development of deep learning, convolutional neural networks (CNNs) have …
the rapid development of deep learning, convolutional neural networks (CNNs) have …