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Multiresolution Signal Processing on Meshes for Automatic Pathological Shape Characterization

Jaume S., Ferrant M., Schreyer A., Hoyte L., Macq B., Fielding J., Kikinis R., Warfield S.K..


Institution:	Department of Radiology, Brigham and Women’s Hospital and Harvard Medical School, 75 Francis St, Boston, MA, 02115, USA,
Publisher:	Med Image Comput Comput Assist Interv. MICCAI 2001
Publication Date:	Oct-2001
Volume Number:	4
Pages:	1398-1400
Citation:	Int Conf Med Image Comput Comput Assist Interv. 2001;4:1398-1400.
Keywords:	Multiresolution Signal Processing, Shape Characterization
Appears in Collections:	CRL, NAC, SPL
Sponsors:	NIH P41 RR13218 NIH P01 CA67165 NIH R01 RR11747
Generated Citation:	Jaume S., Ferrant M., Schreyer A., Hoyte L., Macq B., Fielding J., Kikinis R., Warfield S.K.. Multiresolution Signal Processing on Meshes for Automatic Pathological Shape Characterization. Int Conf Med Image Comput Comput Assist Interv. 2001;4:1398-1400.
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We present a method based on multiresolution signal processing on meshes to create a thickness atlas. We applied this method to construct an atlas of bladder wall thickness. Bladder cancer is associated with increased bladder wall thickness. A thickness atlas helps to detect abnormal thickening in the bladder wall. Extracting inner and outer surface meshes from segmented images, we compute the thickness on the inner surface and map it to a sphere. We average the thickness at each position on the sphere to create a thickness atlas. We then compute Z-score values on the configuration of the patient’s bladder to show regions of unusual thickness.

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