Data augmentation for medical imaging: A systematic literature review
Abstract Recent advances in Deep Learning have largely benefited from larger and more
diverse training sets. However, collecting large datasets for medical imaging is still a …
diverse training sets. However, collecting large datasets for medical imaging is still a …
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 …
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 …
Automatic annotation of hip anatomy in fluoroscopy for robust and efficient 2D/3D registration
Purpose Fluoroscopy is the standard imaging modality used to guide hip surgery and is
therefore a natural sensor for computer-assisted navigation. In order to efficiently solve the …
therefore a natural sensor for computer-assisted navigation. In order to efficiently solve the …
Enabling machine learning in X-ray-based procedures via realistic simulation of image formation
Purpose Machine learning-based approaches now outperform competing methods in most
disciplines relevant to diagnostic radiology. Image-guided procedures, however, have not …
disciplines relevant to diagnostic radiology. Image-guided procedures, however, have not …
Feasibility of automatic measurements of hip joints based on pelvic radiography and a deep learning algorithm
W Yang, Q Ye, S Ming, X Hu, Z Jiang, Q Shen… - European Journal of …, 2020 - Elsevier
Purpose To develop and evaluate an automatic measurement model for hip joints based on
anteroposterior (AP) pelvic radiography and a deep learning algorithm. Methods A total of …
anteroposterior (AP) pelvic radiography and a deep learning algorithm. Methods A total of …
In silico simulation: a key enabling technology for next-generation intelligent surgical systems
To mitigate the challenges of operating through narrow incisions under image guidance,
there is a desire to develop intelligent systems that assist decision making and spatial …
there is a desire to develop intelligent systems that assist decision making and spatial …
Deep learning model for measuring the sagittal Cobb angle on cervical spine computed tomography
C Wang, M Ni, S Tian, H Ouyang, X Liu, L Fan… - BMC Medical …, 2023 - Springer
Purposes To develop a deep learning (DL) model to measure the sagittal Cobb angle of the
cervical spine on computed tomography (CT). Materials and methods Two VB-Net-based DL …
cervical spine on computed tomography (CT). Materials and methods Two VB-Net-based DL …
Multi-task hourglass network for online automatic diagnosis of developmental dysplasia of the hip
Developmental dysplasia of the hip (DDH) is one of the most common diseases in children.
Due to the experience-requiring medical image analysis work, online automatic diagnosis of …
Due to the experience-requiring medical image analysis work, online automatic diagnosis of …