KA Imaging brands its digital x-ray technology

AuntMinnie.com staff writers

Jun 22, 2022

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KA Imaging recently branded the patented dual-energy technology built into its Reveal 35C detector, naming it "SpectralDR."

The SpectralDR technology enables dual-energy subtraction, providing bone and tissue differentiation with a single standard x-ray exposure. It acquires three images simultaneously (digital radiography, bone, and soft tissue dual-energy x-ray images). The technology mimics the workflow, dose, and techniques of mobile digital x-ray detectors.

Reveal 35C is the company's single-exposure, dual-energy flat-panel x-ray detector designed for use in fixed, mobile, and portable settings, KA Imaging said. The company recently secured marketing clearance for Reveal 35C in Canada, the U.S., and Australia.

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Test set images with ground truth (teal, red) and model predictions (green, yellow), with true positives (green), false positives (yellow), and false negatives (red). Predictions from the 6x-YOLOv5 ensemble trained on histogram equalized input images with a y = 0.2 avalanche scheme, achieving 0.536 precision, 0.795 recall, and 0.723 F2 score. Image and caption courtesy of Scientific Reports.

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(a) Raw example of a dynamic digital radiograph. (b) Contrast equalization using contrast-limited adaptive equalization shows improved anatomical visualization. (c) Training data is generated through manually labeling using SLEAP’s graphical user interface. (d-e) Neural network detection schematic. For each quadrant a series of two networks were used. The first identifies the quadrant center, the second using input of the first, then identifies individual anatomical landmarks within a quadrant. (d) Four neural networks were trained, each with the objective of identifying a chest quadrant centroid. The four separate quadrants are visualized as colored boxes (right upper quadrant, green; right lower quadrant, blue; left upper quadrant, red; left lower quadrant, yellow). (e) Serial centroid then anatomical identification. Two quadrant examples showing confidence maps of trained neural networks identifying quadrant centroids (left) and then anatomical confidence maps (right). Image and caption courtesy of Chest Pulmonary.

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Image of patient (upper-left) in which, according to the radiologist's report, there is only consolidation, but the algorithm detects an abnormal rib (upper-right), consolidation (lower-left), and two nodules (lower-right). It is worth noting the confusion of a consolidation with mammary tissue and of two nodules with the two mammary areolae. Image courtesy of Scientific Reports.

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