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 …
The impact of machine learning on 2d/3d registration for image-guided interventions: A systematic review and perspective
Image-based navigation is widely considered the next frontier of minimally invasive surgery.
It is believed that image-based navigation will increase the access to reproducible, safe, and …
It is believed that image-based navigation will increase the access to reproducible, safe, and …
A survey on uncertainty quantification methods for deep neural networks: An uncertainty source perspective
GradICON: Approximate diffeomorphisms via gradient inverse consistency
We present an approach to learning regular spatial transformations between image pairs in
the context of medical image registration. Contrary to optimization-based registration …
the context of medical image registration. Contrary to optimization-based registration …
Review and recommendations on deformable image registration uncertainties for radiotherapy applications
Deformable image registration (DIR) is a versatile tool used in many applications in
radiotherapy (RT). DIR algorithms have been implemented in many commercial treatment …
radiotherapy (RT). DIR algorithms have been implemented in many commercial treatment …
Automatic early diagnosis of Alzheimer's disease using 3D deep ensemble approach
Alzheimer's disease (AD) is considered the 6 leading cause of death worldwide. Early
diagnosis of AD is not an easy task, and no preventive cures have been discovered yet …
diagnosis of AD is not an easy task, and no preventive cures have been discovered yet …
Artificial intelligence for image registration in radiation oncology
Automatic image registration plays an important role in many aspects of the radiation
oncology workflow ranging from treatment simulation, image guided and adaptive …
oncology workflow ranging from treatment simulation, image guided and adaptive …
[HTML][HTML] DragNet: Learning-based deformable registration for realistic cardiac MR sequence generation from a single frame
Deformable image registration (DIR) can be used to track cardiac motion. Conventional DIR
algorithms aim to establish a dense and non-linear correspondence between independent …
algorithms aim to establish a dense and non-linear correspondence between independent …
Maisi: Medical ai for synthetic imaging
Medical imaging analysis faces challenges such as data scarcity, high annotation costs, and
privacy concerns. This paper introduces the Medical AI for Synthetic Imaging (MAISI), an …
privacy concerns. This paper introduces the Medical AI for Synthetic Imaging (MAISI), an …