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 ...
2d. GAN-DRR generated from actual radiographs retained the distal radioulnar anatomy. Two example results with their MAEs are depicted in Fig. 6. The DRRs in the training dataset were generated by considering the line integral of the linear attenuation coefficient derived from the CT value (in ...
A recent technique that is CNN based deep learning gives the promising result of the segmentation. In this Method, MURA (Musculoskeletal Radiographs) database is used. The CNN based U-Net model is trained using the MURA Database. After the training, the Model is tested on the test images....
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, ...
Evidence-based medicine integrates results from randomized controlled trials (RCTs) and meta-analyses, combining the best external evidence with individual clinical expertise and patients’ preferences. However, RCTs of surgery differ from those of medic
Ulnar nerve cross-sectional area for the diagnosis of cubital tunnel syndrome: A meta-analysis of ultrasonographic measurements. Arch. Phys. Med. Rehabil. 2018, 99, 743–757. [Google Scholar] [CrossRef] Kalia, V.; Jacobson, J.A. Imaging of Peripheral Nerves of the Upper Extremity. Radiol...
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 ...
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...