[HTML][HTML] A gentle introduction to deep learning in medical image processing
This paper tries to give a gentle introduction to deep learning in medical image processing,
proceeding from theoretical foundations to applications. We first discuss general reasons for …
proceeding from theoretical foundations to applications. We first discuss general reasons for …
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 …
Synthetic data accelerates the development of generalizable learning-based algorithms for X-ray image analysis
Artificial intelligence (AI) now enables automated interpretation of medical images. However,
AI's potential use for interventional image analysis remains largely untapped. This is …
AI's potential use for interventional image analysis remains largely untapped. This is …
Cai4cai: the rise of contextual artificial intelligence in computer-assisted interventions
Data-driven computational approaches have evolved to enable extraction of information
from medical images with reliability, accuracy, and speed, which is already transforming …
from medical images with reliability, accuracy, and speed, which is already transforming …
Deep neural network-based sinogram super-resolution and bandwidth enhancement for limited-data photoacoustic tomography
Photoacoustic tomography (PAT) is a noninvasive imaging modality combining the benefits
of optical contrast at ultrasonic resolution. Analytical reconstruction algorithms for …
of optical contrast at ultrasonic resolution. Analytical reconstruction algorithms for …
DeepDRR–a catalyst for machine learning in fluoroscopy-guided procedures
Abstract Machine learning-based approaches outperform competing methods in most
disciplines relevant to diagnostic radiology. Interventional radiology, however, has not yet …
disciplines relevant to diagnostic radiology. Interventional radiology, however, has not yet …
A fully differentiable framework for 2D/3D registration and the projective spatial transformers
Image-based 2D/3D registration is a critical technique for fluoroscopic guided surgical
interventions. Conventional intensity-based 2D/3D registration approa-ches suffer from a …
interventions. Conventional intensity-based 2D/3D registration approa-ches suffer from a …
Clinical application of artificial intelligence-assisted diagnosis using anteroposterior pelvic radiographs in children with developmental dysplasia of the hip
SC Zhang, J Sun, CB Liu, JH Fang… - The Bone & Joint …, 2020 - boneandjoint.org.uk
Aims The diagnosis of developmental dysplasia of the hip (DDH) is challenging owing to
extensive variation in paediatric pelvic anatomy. Artificial intelligence (AI) may represent an …
extensive variation in paediatric pelvic anatomy. Artificial intelligence (AI) may represent an …
Self-supervised 2D/3D registration for X-ray to CT image fusion
Abstract Deep Learning-based 2D/3D registration enables fast, robust, and accurate X-ray to
CT image fusion when large annotated paired datasets are available for training. However …
CT image fusion when large annotated paired datasets are available for training. However …
Automatic 3D landmarking model using patch‐based deep neural networks for CT image of oral and maxillofacial surgery
Background Manual landmarking is a time consuming and highly professional work.
Although some algorithm‐based landmarking methods have been proposed, they lack …
Although some algorithm‐based landmarking methods have been proposed, they lack …