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A Review of Medical Image Registration for Different Modalities [PDF]

open access: yesBioengineering
Medical image registration has become pivotal in recent years with the integration of various imaging modalities like X-ray, ultrasound, MRI, and CT scans, enabling comprehensive analysis and diagnosis of biological structures.
Fatemehzahra Darzi, Thomas Bocklitz
doaj   +4 more sources

Deformable Medical Image Registration: A Survey [PDF]

open access: yesIEEE Transactions on Medical Imaging, 2013
Deformable image registration is a fundamental task in medical image processing. Among its most important applications, one may cite: 1) multi-modality fusion, where information acquired by different imaging devices or protocols is fused to facilitate diagnosis and treatment planning; 2) longitudinal studies, where temporal structural or anatomical ...
Aristeidis Sotiras   +2 more
exaly   +6 more sources

Medical image registration utilizing tissue P systems [PDF]

open access: yesFrontiers in Pharmacology, 2022
The tissue P system (TPS) possesses intrinsic attributes of parallel execution in comprehensive data and instruction space, which provides fast convergence during the transition from local to global optima.
Saleem Sanatan Kujur, Sudip Kumar Sahana
doaj   +2 more sources

A review of deep learning-based deformable medical image registration [PDF]

open access: yesFrontiers in Oncology, 2022
The alignment of images through deformable image registration is vital to clinical applications (e.g., atlas creation, image fusion, and tumor targeting in image-guided navigation systems) and is still a challenging problem.
Jing Zou   +3 more
doaj   +2 more sources

Wavelet-Guided Multi-Scale ConvNeXt for Unsupervised Medical Image Registration [PDF]

open access: yesBioengineering
Medical image registration is essential in clinical practices such as surgical navigation and image-guided diagnosis. The Transformer architecture of TransMorph demonstrates better accuracy in non-rigid registration tasks.
Xuejun Zhang   +10 more
doaj   +2 more sources

Non-rigid Multi-Modal Medical Image Registration Based on Improved Maximum Mutual Information PV Image Interpolation Method [PDF]

open access: yesFrontiers in Public Health, 2022
With the continuous improvement of medical imaging equipment, CT, MRI and PET images can obtain accurate anatomical information of the same patient site.
Liting He
doaj   +2 more sources

Medical image registration and its application in retinal images: a review [PDF]

open access: yesVisual Computing for Industry, Biomedicine, and Art
Medical image registration is vital for disease diagnosis and treatment with its ability to merge diverse information of images, which may be captured under different times, angles, or modalities. Although several surveys have reviewed the development of
Qiushi Nie   +4 more
doaj   +2 more sources

Current trends in medical image registration and fusion

open access: yesEgyptian Informatics Journal, 2016
Recently, medical image registration and fusion processes are considered as a valuable assistant for the medical experts. The role of these processes arises from their ability to help the experts in the diagnosis, following up the diseases’ evolution ...
Fatma El-Zahraa Ahmed El-Gamal   +2 more
doaj   +3 more sources

An effective deep learning algorithm for medical image registration. [PDF]

open access: yesPLOS Digital Health
Image registration is crucial for many medical imaging applications, including longitudinal monitoring and multimodal information fusion. A key challenge is to achieve accurate alignment while strictly preserving topology and invertibility.
Jinqiu Deng   +5 more
doaj   +2 more sources

The Influence of Intensity Standardization on Medical Image Registration [PDF]

open access: yesSPIE Proceedings, 2010
Acquisition-to-acquisition signal intensity variations (non-standardness) are inherent in MR images. Standardization is a post processing method for correcting inter-subject intensity variations through transforming all images from the given image gray ...
Bagci, Ulas, Bai, Li, Udupa, Jayaram K.
core   +2 more sources

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