Semidefinite programming heuristics for surface reconstruction ambiguities

Abstract. We consider the problem of reconstructing a smooth surface under constraints that have discrete ambiguities. These problems arise in areas such as shape from texture, shape from shading, photometric stereo and shape from defocus. While the problem is computationally hard, heuristics based on semidefinite programming may reveal the shape of the surface.

Roentgenologische, computertomographische, autoradiographische und histologische Verlaufskontrolle transplantierter Beckenkammapophysen

SIGLECopy held by FIZ Karlsruhe; available from UB/TIB Hannover / FIZ - Fachinformationszzentrum Karlsruhe / TIB - Technische InformationsbibliothekDEGerman

Biconvex Relaxation for Semidefinite Programming in Computer Vision

Semidefinite programming (SDP) is an indispensable tool in computer vision, but general-purpose solvers for SDPs are often too slow and memory intensive for large-scale problems. Our framework, referred to as biconvex relaxation (BCR), transforms an SDP consisting of PSD constraint matrices into a specific biconvex optimization problem, which can then be approximately solved in the original, low-dimensional variable space at low complexity. The resulting problem is solved using an efficient alternating minimization (AM) procedure. Since AM has the potential to get stuck in local minima, we propose a general initialization scheme that enables BCR to start close to a global optimum---this is key for BCR to quickly converge to optimal or near-optimal solutions. We showcase the efficacy of our approach on three applications in computer vision, namely segmentation, co-segmentation, and manifold metric learning. BCR achieves solution quality comparable to state-of-the-art SDP methods with speedups between 4x and 35x.ISSN:0302-9743ISSN:1611-334

Score reproducibility and reliability in differentiating small bowel subepithelial masses from innocent bulges

Aims: The primary aim of this study was to assess the reliability, intra- and inter-observer variation of the SPICE, Mucosal protrusion angle (MPA) and SHYUNG scores in differentiating a subepithelial mass (SEM) from a bulge. Methods: This retrospective multicentre study analysed the 3 scores, radiological studies, enteroscopy and/or surgical findings. Results: 100 patients with a potential SEM (mean age 57.6years) were recruited with 75 patients having pathology. In patients with a SEM the mean SPICE score was 2.04 (95% CI 1.82–2.26) as compared to 1.16 (95% CI 0.81–1.51) without any pathology (AUC 0.74, p<0.001), with a fair intra-observer agreement (Kappa 0.3, p<0.001) and slight inter-observer agreement (Kappa 0.14, p<0.05). SPICE had a 37.3% sensitivity and 92.0% specificity in distinguishing between a SEM and bulge, whereas MPA<90˚ had 58.7% and 76.0% respectively, with poor intra-observer(p = 0.05) and interobserver agreement (p = 0.64). The SHYUNG demonstrated a moderate intra-observer (Kappa 0.44, p<0.001) and slight inter-observer reliability (Kappa 0.18, p<0.001). The sensitivity of an elevated SHYUNG score (≥4) in identifying a SEM was 18.7% with a specificity of 92.0% (AUC 0.71, p = 0.002). Conclusions: Though these scores are easy to use, they have, at best, slight to moderate intra and inter-observer agreement. Their overall diagnostic performances are limited