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AN IMPROVED AIR TISSUE BOUNDARY SEGMENTATION TECHNIQUE FOR REAL TIME MAGNETIC RESONANCE IMAGING VIDEO USING SEGNET

Abstract: 

This paper presents an improved methodology for the segmentation of the Air-Tissue boundaries (ATBs) in the upper airway of the human vocal tract using Real-Time Magnetic Resonance Imaging (rtMRI) videos. Semantic segmentation is deployed in the proposed approach using a Deep learning architecture called SegNet. The network processes an input image to produce a binary output image of the same dimensions having classified each pixel as air cavity or tissue, following which contours are predicted. A Multi-dimensional least square smoothing technique is applied to smoothen the contours. To quantify the precision of predicted contours, Dynamic Time Warping (DTW) distance is calculated between the predicted contours and the manually annotated ground truth contour. Four fold experiments are conducted with four subjects from the USC-TIMIT corpus, which demonstrates that the proposed approach achieves a lower DTW distance of 1.02 and 1.09 for the upper and lower ATB compared to the best baseline scheme. The proposed SegNet based approach has an average pixel classification accuracy of 99.3% across all the subjects with only 2 rtMRI videos (~180 frames) per subject for training.

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Paper Details

Authors:
Valliappan CA, Avinash Kumar, Renuka Mannem, Karthik GR, Prasanta Kumar Ghosh
Submitted On:
8 May 2019 - 6:06am
Short Link:
Type:
Presentation Slides
Event:
Presenter's Name:
MANNEM RENUKA
Paper Code:
4264
Document Year:
2019
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Document Files

Icassp_2019.pdf

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[1] Valliappan CA, Avinash Kumar, Renuka Mannem, Karthik GR, Prasanta Kumar Ghosh, "AN IMPROVED AIR TISSUE BOUNDARY SEGMENTATION TECHNIQUE FOR REAL TIME MAGNETIC RESONANCE IMAGING VIDEO USING SEGNET", IEEE SigPort, 2019. [Online]. Available: http://sigport.org/4062. Accessed: Jun. 25, 2019.
@article{4062-19,
url = {http://sigport.org/4062},
author = {Valliappan CA; Avinash Kumar; Renuka Mannem; Karthik GR; Prasanta Kumar Ghosh },
publisher = {IEEE SigPort},
title = {AN IMPROVED AIR TISSUE BOUNDARY SEGMENTATION TECHNIQUE FOR REAL TIME MAGNETIC RESONANCE IMAGING VIDEO USING SEGNET},
year = {2019} }
TY - EJOUR
T1 - AN IMPROVED AIR TISSUE BOUNDARY SEGMENTATION TECHNIQUE FOR REAL TIME MAGNETIC RESONANCE IMAGING VIDEO USING SEGNET
AU - Valliappan CA; Avinash Kumar; Renuka Mannem; Karthik GR; Prasanta Kumar Ghosh
PY - 2019
PB - IEEE SigPort
UR - http://sigport.org/4062
ER -
Valliappan CA, Avinash Kumar, Renuka Mannem, Karthik GR, Prasanta Kumar Ghosh. (2019). AN IMPROVED AIR TISSUE BOUNDARY SEGMENTATION TECHNIQUE FOR REAL TIME MAGNETIC RESONANCE IMAGING VIDEO USING SEGNET. IEEE SigPort. http://sigport.org/4062
Valliappan CA, Avinash Kumar, Renuka Mannem, Karthik GR, Prasanta Kumar Ghosh, 2019. AN IMPROVED AIR TISSUE BOUNDARY SEGMENTATION TECHNIQUE FOR REAL TIME MAGNETIC RESONANCE IMAGING VIDEO USING SEGNET. Available at: http://sigport.org/4062.
Valliappan CA, Avinash Kumar, Renuka Mannem, Karthik GR, Prasanta Kumar Ghosh. (2019). "AN IMPROVED AIR TISSUE BOUNDARY SEGMENTATION TECHNIQUE FOR REAL TIME MAGNETIC RESONANCE IMAGING VIDEO USING SEGNET." Web.
1. Valliappan CA, Avinash Kumar, Renuka Mannem, Karthik GR, Prasanta Kumar Ghosh. AN IMPROVED AIR TISSUE BOUNDARY SEGMENTATION TECHNIQUE FOR REAL TIME MAGNETIC RESONANCE IMAGING VIDEO USING SEGNET [Internet]. IEEE SigPort; 2019. Available from : http://sigport.org/4062