Unbiased Shape Compactness for Segmentation

We propose to constrain segmentation functionals with a dimensionless, unbiased and position-independent shape compactness prior, which we solve efficiently with an alternating direction method of multipliers (ADMM). Involving a squared sum of pairwise potentials, our prior results in a challenging high-order optimization problem, which involves dense (fully connected) graphs. We split the problem into a sequence of easier sub-problems, each performed efficiently at each iteration: (i) a sparse-matrix inversion based on Woodbury identity, (ii) a closed-form solution of a cubic equation and (iii) a graph-cut update of a sub-modular pairwise sub-problem with a sparse graph. We deploy our prior in an energy minimization, in conjunction with a supervised classifier term based on CNNs and standard regularization constraints. We demonstrate the usefulness of our energy in several medical applications. In particular, we report comprehensive evaluations of our fully automated algorithm over 40 subjects, showing a competitive performance for the challenging task of abdominal aorta segmentation in MRI.Comment: Accepted at MICCAI 201

Thoracoscopic resection of thoracic esophageal duplication cyst containing ectopic pancreatic tissue in adult

Esophageal duplication cyst is a rare congenital anomaly. They can be associated with other congenital anomalies, such as spinal abnormalities, and tracheoesophageal fistulas. In adults, almost of the patients with esophageal duplication cyst is asymptomatic and accidentally diagnosed by chest X-ray or computed tomography. However, cysts may become symptomatic owing to complications such as esophageal stenosis, respiratory system compression, rupture, infarction, or malignancy. Complete surgical resection is the standard treatment even in patients with asymptmatic cysts. Traditional approach for resection is via thoracotomy. But, the thoracoscopic approach makes more indicate for mediastinal diseases, because of minimally invasive for patients. We describe a case with esophageal duplication cyst, which contained the ectopic pancreatic tissue in the solid portion, resected under the thoracoscopic approach in adult

Fractional Sobolev Metrics on Spaces of Immersed Curves

Motivated by applications in the field of shape analysis, we study reparametrization invariant, fractional order Sobolev-type metrics on the space of smooth regular curves Imm(S1 , R ) and on its Sobolev completions ℐ (S1 , R ). We prove local well-posedness of the geodesic equations both on the Banach manifold ℐ (S1 , R ) and on the Fr´echetmanifold Imm(S1 , R ) provided the order of the metric is greater or equal to one. In addition we show that the -metric induces a strong Riemannian metric on the Banach manifold ℐ (S1 , R ) of the same order , provided > 3 2 . These investigations can be also interpreted as a generalization of the analysis for right invariant metrics on the diffeomorphism group

A Fisher-Rao Metric for curves using the information in edges

Two curves which are close together in an image are indistinguishable given a measurement, in that there is no compelling reason to associate the measurement with one curve rather than the other. This observation is made quantitative using the parametric version of the Fisher-Rao metric. A probability density function for a measurement conditional on a curve is constructed. The distance between two curves is then defined to be the Fisher-Rao distance between the two conditional pdfs. A tractable approximation to the Fisher-Rao metric is obtained for the case in which the measurements are compound in that they consist of a point x and an angle α which specifies the direction of an edge at x. If the curves are circles or straight lines, then the approximating metric is generalized to take account of inlying and outlying measurements. An estimate is made of the number of measurements required for the accurate location of a circle in the presence of outliers. A Bayesian algorithm for circle detection is defined. The prior density for the algorithm is obtained from the Fisher-Rao metric. The algorithm is tested on images from the CASIA Iris Interval database

Nucleation reduction strategy of BaNH

Kidney stones consist of various organic, inorganic and semi-organic compounds. Mineral oxalate monohydrate and di-hydrate is the main inorganic constituent of kidney stones. However, the mechanisms for the formation of crystal mineral oxalate are not clearly understood. In this field of study there are many hypothesis including nucleation, crystal growth and or aggregation of formation of AOMH (ammonium oxalate monohydrate) and AODH (ammonium oxalate di-hydrate) crystals. The effect of some urinary species such as ammonium oxalates, calcium, citrate, proteins and trace mineral elements have been previously reported by the author. The kidney stone constituents are grown in the kidney environments, the sodium meta silica gel medium (SMS) provides the necessary growth simulation (in vitro). In the artificial urinary stone growth process, growth parameters within the different chemical environments are identified. The author has reported the growth of urinary crystals such as CHP, SHP, BHP and AHP. In the present study, BaNH4MgHPO4 (barium ammonium magnesium hydrogen phosphate) crystals have been grown in three different growth faces to attain the total nucleation reductions. As an extension of this research, many characterization studies have been carried out and the results are reported

Tracking with Sobolev Active Contours

© 2006 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.DOI: 10.1109/CVPR.2006.314Recently proposed Sobolev active contours introduced a new paradigm for minimizing energies defined on curves by changing the traditional cost of perturbing a curve and thereby redefining their gradients. Sobolev active contours evolve more globally and are less attracted to certain intermediate local minima than traditional active contours. In this paper we analyze Sobolev active contours in the Fourier domain in order to understand their evolution across different scales. This analysis shows an important and useful behavior of Sobolev contours, namely, that they move successively from coarse to increasingly finer scale motions in a continuous manner. Along with other properties, the previous observation reveals that Sobolev active contours are ideally suited for tracking problems that use active contours. Our purpose in this work is to show how a variety of active contour based tracking methods can be significantly improved merely by evolving the active contours according to the Sobolev method