✦ LIBER ✦

Segmentation of ARX-models using sum-of-norms regularization

✍ Scribed by Henrik Ohlsson; Lennart Ljung; Stephen Boyd

Publisher: Elsevier Science
Year: 2010
Tongue: English
Weight: 497 KB
Volume: 46
Category: Article
ISSN: 0005-1098
DOI: 10.1016/j.automatica.2010.03.013

No coin nor oath required. For personal study only.

📜 SIMILAR VOLUMES

Calibration of POD reduced-order models

Calibration of POD reduced-order models using Tikhonov regularization

✍ L. Cordier; B. Abou El Majd; J. Favier 📂 Article 📅 2009 🏛 John Wiley and Sons 🌐 English ⚖ 648 KB

Automated segmentation of muscle fiber i

Automated segmentation of muscle fiber images using active contour models

✍ Aleš Klemenčič; Stanislav Kovačič; Franjo Pernuš 📂 Article 📅 1998 🏛 John Wiley and Sons 🌐 English ⚖ 564 KB

The cross-sectional area of different fiber types is an important anatomic feature in studying the structure and function of healthy and diseased human skeletal muscles. However, such studies are hampered by the thousands of fibers involved when manual segmentation has to be used. We have developed

3D/2D registration and segmentation of s

3D/2D registration and segmentation of scoliotic vertebrae using statistical models

✍ Said Benameur; Max Mignotte; Stefan Parent; Hubert Labelle; Wafa Skalli; Jacques 📂 Article 📅 2003 🏛 Elsevier Science 🌐 English ⚖ 970 KB

We propose a new 3D/2D registration method for vertebrae of the scoliotic spine, using two conventional radiographic views (postero-anterior and lateral), and a priori global knowledge of the geometric structure of each vertebra. This geometric knowledge is efficiently captured by a statistical defo

An estimation of the sensitivity of nume

An estimation of the sensitivity of numerical error norm using adjoint model

✍ A. K. Alekseev; I. M. Navon 📂 Article 📅 2009 🏛 John Wiley and Sons 🌐 English ⚖ 428 KB

## Abstract __A posteriori__ estimation of the numerical error sensitivity to the local truncation error is addressed using adjoint model endowed with the information on the error field. The numerical error is estimated from the solution of the linear tangent model (LTM) or from a Richardson extrap

Segmentation of the quadratus lumborum m

Segmentation of the quadratus lumborum muscle using statistical shape modeling

✍ Craig M. Engstrom; Jurgen Fripp; Valer Jurcak; Duncan G. Walker; Olivier Salvado 📂 Article 📅 2011 🏛 John Wiley and Sons 🌐 English ⚖ 573 KB

## Abstract ## Purpose: To compare automated segmentation of the quadratus lumborum (QL) based on statistical shape modeling (SSM) with conventional manual processing of magnetic resonance (MR) images for segmentation of this paraspinal muscle. ## Materials and Methods: The automated SSM scheme

3D image segmentation of deformable obje

3D image segmentation of deformable objects with joint shape-intensity prior models using level sets

✍ Jing Yang; James S. Duncan 📂 Article 📅 2004 🏛 Elsevier Science 🌐 English ⚖ 662 KB

We propose a novel method for 3D image segmentation, where a Bayesian formulation, based on joint prior knowledge of the object shape and the image gray levels, along with information derived from the input image, is employed. Our method is motivated by the observation that the shape of an object an