Merit Medical shines in Q2

AuntMinnie.com staff writers

Jul 23, 2018

Disposable products developer Merit Medical Systems announced a more than 20% jump in revenue for its second quarter (end-June 30).

Revenue increased by 20.5% for the quarter, rising from $186.5 million a year ago to $224.8 million for the current quarter. Net income rose from $9.48 million in Q2 of 2017 to $10.9 million for this quarter. However, for the six-month period, net income fell from $24.2 million in 2017 to $16.2 million in 2018.

Merit attributed its growth to demand for legacy products, a full quarter of selling products acquired from Becton Dickinson, and continued growth in international markets.

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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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