Confidence Weighting for Robust Automated Measurements of Popliteal Vessel Wall Magnetic Resonance Imaging

Author:

Hippe Daniel S.1,Balu Niranjan1,Chen Li2,Canton Gador1,Liu Wenjin1,Watase Hiroko3,Waterton John C.4,Hatsukami Thomas S.3,Hwang Jenq-Neng2,Yuan Chun1

Affiliation:

1. Department of Radiology (D.S.H., N.B., G.C., W.L., C.Y.), University of Washington, Seattle.

2. Department of Electrical and Computer Engineering (L.C., J.-N.H.), University of Washington, Seattle.

3. Division of Vascular Surgery, Department of Surgery (H.W., T.S.H.), University of Washington, Seattle.

4. Centre for Imaging Sciences, Division of Informatics Imaging & Data Sciences, School of Health Sciences, Faculty of Biology Medicine & Health, Manchester Academic Health Sciences Centre, The University of Manchester, Manchester, United Kingdom. (J.C.W.).

Publisher

Ovid Technologies (Wolters Kluwer Health)

Subject

General Medicine

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2. The Osteoarthritis Initiative: an overview.;Fawaz-Estrup F;Med Health R I,2004

3. Automated artery localization and vessel wall segmentation of magnetic resonance vessel wall images using tracklet refinement and polar conversion.;Chen L;arXiv

4. Carotid magnetic resonance imaging for monitoring atherosclerotic plaque progression: a multicenter reproducibility study

5. Interstudy reproducibility of dark blood high-resolution MRI in evaluating basilar atherosclerotic plaque at 3 Tesla

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