Matching Medical Images with Deep Learning Networks: A Survey

Many patients' lives are being saved by image-guided interventions, and the image registration issue mustbe regarded as the most difficult and complex problem to solve. However, the latestenormous advancements in machine learning (ML), which include the potential to deploy deep neural networks (DNNs)on modern many-core GPUs, have created a promising opportunity for tackling a variety of medical applications,including registration. The most recent research on medical image registration with DNNsis reviewed in detail in the presented work. All of the relevant papers that have already been published in the subject are included in the systematic review. This thorough overview includes a detailed discussion as well assurvey of important ideas, statistical analysis from many perspectives, novelties and key contributions, confiding challenges,future directions, key-enabling approaches,and prospective trends. Forreaders who are actively involved in the subject, researching state-of-the-art and hoping to present a contribution to future publications, the presented studyoffers a deep grasp and insight.

Authors

Publication Details

Journal
International Journal of Engineering Research and Advanced Technology
Published
2025-01-01
DOI
https://doi.org/10.31695/ijerat.2025.3.1
Primary Topic
Brain Tumor Detection and Classification
Type
article
Field-Weighted Citation Impact
0.00
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article

Matching Medical Images with Deep Learning Networks: A Survey

Ikhlas Watan Ghindawi, Lamyaa Mohammed Kadhim
International Journal of Engineering Research and Advanced Technology
Brain Tumor Detection and Classification
article

Matching Medical Images with Deep Learning Networks: A Survey

Ikhlas Watan Ghindawi, Lamyaa Mohammed Kadhim
article en

Abstract

Many patients' lives are being saved by image-guided interventions, and the image registration issue mustbe regarded as the most difficult and complex problem to solve. However, the latestenormous advancements in machine learning (ML), which include the potential to deploy deep neural networks (DNNs)on modern many-core GPUs, have created a promising opportunity for tackling a variety of medical applications,including registration. The most recent research on medical image registration with DNNsis reviewed in detail in the presented work. All of the relevant papers that have already been published in the subject are included in the systematic review. This thorough overview includes a detailed discussion as well assurvey of important ideas, statistical analysis from many perspectives, novelties and key contributions, confiding challenges,future directions, key-enabling approaches,and prospective trends. Forreaders who are actively involved in the subject, researching state-of-the-art and hoping to present a contribution to future publications, the presented studyoffers a deep grasp and insight.

International Journal of Engineering Research and Advanced TechnologyVol. 11(03)
Openalex Percentile: Top 93%
Brain Tumor Detection and Classification
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Matching Medical Images with Deep Learning Networks: A Survey — Ikhlas Watan Ghindawi, Lamyaa Mohammed Kadhim · International Journal of Engineering Research and Advanced Technology (2025) | TGRS Research Map | TGRS