During clinical evaluation of patients and planning orthopedic treatments, the periodic assessment of lower limb alignment is critical. Currently, physicians use physical tools and radiographs to directly observe limb alignment. However, this process is manual, time consuming, and prone to human error....
Automated abnormality detection in lower extremity radiographs using deep learning. Nat. Mach. Intell. 1, 578–583 (2019). Article Google Scholar Zhang, L. et al. Rapid histology of laryngeal squamous cell carcinoma with deep-learning based stimulated Raman scattering microscopy. Theranostics 9, ...
intersection over union (IoU) (also known as the Jaccard index), mean boundary F1 score (MeanBFScore), and Dice similarity coefficient (DSC)35. The accuracy is the ratio of the number of correctly classified pixels to all the classified pixels of one label. The IoU is the ratio of ...
et al., “Evaluation of image features and search strategies for segmentation of bone structures in radiographs using Active Shape Models,” Medical Image Analysis, vol. 6, No. 1, Mar. 2002, pp. 47-62. Behiels, G., et al, “Lecture Notes in Computer Science: Medical Image Computing ...
Teleradiology refers to the transmission of radiographic images from one location to another. Most of the work to date has involved scanning of conventional radiographs at clinics and other medical facilities with no full-time radiologist and transmitting the images to a medical center or hospital, ...
Robust 2D-2D image registrations are first used to match digitally reconstructed radiographs, which are generated by simulating X-ray projections of an intensity volumes, with the input X-ray images. The obtained 2D-2D non-rigid transformations are used to update the locations of the 2D ...
Robust 2D-2D image registrations are first used to match digitally reconstructed radiographs, which are generated by simulating X-ray projections of an intensity volumes, with the input X-ray images. The obtained 2D-2D non-rigid transformations are used to update the locations of the 2D ...
Robust 2D-2D image registrations are first used to match digitally reconstructed radiographs, which are generated by simulating X-ray projections of an intensity volumes, with the input X-ray images. The obtained 2D-2D non-rigid transformations are used to update the locations of the 2D ...
The dataset consist of lower extremity radiographs of adults gathered by the Stanford University School of Medicine. The contribution of this paper is threefold. From a medical perspective, we provide a complete solution to obtain femur configuration on two-dimensional X-ray images. From a robotics...
Modern research has demonstrated that deep learning can execute difficult analyses at the level of medical experts [8]. Several research in orthopaedic traumatology have used deep learning in radiographs to diagnose and classify fractures [9,10]. However, deep learning in fracture detection on CT ...