on a preset coordinate scheme for the anatomy, arranging the plurality of x-ray images into a predetermined order based on the species of the patient, and generating and outputting a data file including the plurality of x-ray images in the predetermined order, positioned upright, and labeled.Mi...
The x-ray images are compared with electron micrographs of the same labeled, unsectioned, whole cell. It is verified that the dark-field x-ray signal is primarily due to the label and the bright-field x-ray signal, showing absorption due to carbon, is largely unaffected by the label. ...
BRAX, Brazilian labeled chest x-ray dataset Article Open access 10 August 2022 Introduction The implementation of medical artificial intelligence (AI) into clinical practice in general, and radiology practice in particular, has in large part been limited by the time, cost, and expertise required ...
The database includes five groups of X-ray images: castings, welds, baggage, natural objects and settings. Each group has several series, and each series several X-ray images. Most of the series are annotated or labeled. In such cases, the coordinates of the bounding boxes of the objects ...
X-ray computed tomography (CT) is a commercially established modality for imaging large objects like passenger luggage. CT can provide the density and the effective atomic number, which is not always sufficient to identify threats like explosives and narcotics, since they can have a similar composit...
In medical imaging, the last decade has witnessed a remarkable increase in the availability and diversity of chest X-ray (CXR) datasets. Concurrently, ther
Two public chest x-ray datasets for computer-aided screening of pulmonary diseases Quant. Imag. Med. Surg., 4 (6) (2014), p. 475 Google Scholar [39] D. Kermany, K. Zhang, M. Goldbaum, et al., Labeled optical coherence tomography (OCT) and chest x-ray images for classification, ...
Most of the existing chest X-ray datasets include labels from a list of findings without specifying their locations on the radiographs. This limits the development of machine learning algorithms for the detection and localization of chest abnormalities. In this work, we describe a dataset of more ...
In this study, we propose a two-stage workflow used for the segmentation and scoring of lung diseases. The workflow inherits quantification, qualification, and visual assessment of lung diseases on X-ray images estimated by radiologists and clinicians. I
X-ray absorption spectroscopy (XAS) has become an indispensable tool to in situ investigate dynamic natures of electrocatalysts but still suffers from limited energy resolution, leading to significant electronic transitions poorly resolved. Herein, we highlight advanced X-ray spectroscopies beyond ...