BAGLS, a multihospital Benchmark for Automatic Glottis Segmentation

Fully-automatic glottis segmentation with active shape models

A New Approach for the Glottis Segmentation using Snakes

The present work describes a new methodology for the automatic detection of the glottal space from laryngeal images based on active contour models (snakes). In order to obtain an appropriate image for the use of snakes based techniques, the proposed algorithm combines a pre-processing stage including some traditional techniques (thresholding and median filter) with more sophisticated ones such ...

Automatic high-speed video glottis segmentation using salient regions and 3D geodesic active contours

Verbal communication plays an important role in our economy. Laryngeal high-speed videos have emerged as a state of the art method to investigate vocal fold vibrations in the context of voice disorders affecting verbal communication. Segmentation of the glottis from these videos is required to analyze vocal fold vibrations. The vast amount of data produced makes manual segmentation impossible i...

Automatic Glottis Segmentation from Laryngeal High-Speed Videos Using 3D Active Contours

Laryngeal high-speed videos are a state of the art method to investigate vocal fold vibration but the vast amount of data produced prevents it from being used in clinical applications. Segmentation of the glottal gap is important for excluding irrelevant data from video frames for subsequent analysis. We present a novel, fully automatic segmentation method involving rigid motion compensation, s...

New benchmark for image segmentation evaluation

bstract. Image segmentation and its performance evaluation are ery difficult but important problems in computer vision. A major hallenge in segmentation evaluation comes from the fundamental onflict between generality and objectivity: For general-purpose egmentation, the ground truth and segmentation accuracy may not e well defined, while embedding the evaluation in a specific appliation, the e...