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 …

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 …

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 …

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 …

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 mapping between images. While state-of-the-art image …

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 …

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 …

Anatomy-guided multimodal registration by learning segmentation without ground truth: Application to intraprocedural CBCT/MR liver segmentation and registration

B Zhou, Z Augenfeld, J Chapiro, SK Zhou, C Liu… - Medical image …, 2021 - Elsevier
Multimodal image registration has many applications in diagnostic medical imaging and
image-guided interventions, such as Transcatheter Arterial Chemoembolization (TACE) of …

Fourier-net: Fast image registration with band-limited deformation

X Jia, J Bartlett, W Chen, S Song, T Zhang… - Proceedings of the …, 2023 - ojs.aaai.org
Unsupervised image registration commonly adopts U-Net style networks to predict dense
displacement fields in the full-resolution spatial domain. For high-resolution volumetric …