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Found 4 papers, 1 papers with code
A superpixel-driven deep learning approach for the analysis of dermatological wounds
QTDU consists of a three-stage pipeline for the obtaining of ulcer segmentation, tissues' labeling, and wounded area quantification.
3DBGrowth: volumetric vertebrae segmentation and reconstruction in magnetic resonance imaging
We also take advantage of the slope coefficient from the annotation time to reduce the total number of annotated slices, reducing the time spent on manual annotation.
BGrowth: an efficient approach for the segmentation of vertebral compression fractures in magnetic resonance imaging
Segmentation of medical images is a critical issue: several process of analysis and classification rely on this segmentation.
BoWFire: Detection of Fire in Still Images by Integrating Pixel Color and Texture Analysis
Our method uses a reduced number of parameters if compared to previous works, easing the process of fine tuning the method.
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