A review on deep learning in medical image analysis

S Suganyadevi, V Seethalakshmi… - International Journal of …, 2022‏ - Springer
Ongoing improvements in AI, particularly concerning deep learning techniques, are
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

J Chen, Y Liu, S Wei, Z Bian, S Subramanian… - Medical Image …, 2024‏ - Elsevier
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 …

On the analyses of medical images using traditional machine learning techniques and convolutional neural networks

S Iqbal, A N. Qureshi, J Li, T Mahmood - Archives of Computational …, 2023‏ - Springer
Convolutional neural network (CNN) has shown dissuasive accomplishment on different
areas especially Object Detection, Segmentation, Reconstruction (2D and 3D), Information …

Image matching from handcrafted to deep features: A survey

J Ma, X Jiang, A Fan, J Jiang, J Yan - International Journal of Computer …, 2021‏ - Springer
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 …

Breaking the dilemma of medical image-to-image translation

L Kong, C Lian, D Huang, Y Hu… - Advances in Neural …, 2021‏ - proceedings.neurips.cc
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 …

Correlation-aware coarse-to-fine mlps for deformable medical image registration

M Meng, D Feng, L Bi, J Kim - Proceedings of the IEEE/CVF …, 2024‏ - openaccess.thecvf.com
Deformable image registration is a fundamental step for medical image analysis. Recently
transformers have been used for registration and outperformed Convolutional Neural …

H-vit: A hierarchical vision transformer for deformable image registration

M Ghahremani, M Khateri, B Jian… - Proceedings of the …, 2024‏ - openaccess.thecvf.com
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 …

Swin-voxelmorph: A symmetric unsupervised learning model for deformable medical image registration using swin transformer

Y Zhu, S Lu - International Conference on Medical Image Computing …, 2022‏ - Springer
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 …

DeepLeukNet—A CNN based microscopy adaptation model for acute lymphoblastic leukemia classification

U Saeed, K Kumar, MA Khuhro, AA Laghari… - Multimedia Tools and …, 2024‏ - Springer
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 …

Symmetric transformer-based network for unsupervised image registration

M Ma, Y Xu, L Song, G Liu - Knowledge-Based Systems, 2022‏ - Elsevier
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 …