Fully Automatic and Real-Time Catheter Segmentation in X-Ray Fluoroscopy

Augmenting X-ray imaging with 3D roadmap to improve guidance is a common strategy. Such approaches benefit from automated analysis of the X-ray images, such as the automatic detection and tracking of instruments. In this paper, we propose a real-time method to segment the catheter and guidewire in 2D X-ray fluoroscopic sequences. The method is based on deep convolutional neural networks. The network takes as input the current image and the three previous ones, and segments the catheter and guidewire in the current image. Subsequently, a centerline model of the catheter is constructed from the segmented image. A small set of annotated data combined with data augmentation is used to train the network. We trained the method on images from 182 X-ray sequences from 23 different interventions. On a testing set with images of 55 X-ray sequences from 5 other interventions, a median centerline distance error of 0.2 mm and a median tip distance error of 0.9 mm was obtained. The segmentation of the instruments in 2D X-ray sequences is performed in a real-time fully-automatic manner.Comment: Accepted to MICCAI 201

Interventional tool tracking using discrete optimization.

This work presents a novel scheme for tracking of motion and deformation of interventional tools such as guide-wires and catheters in fluoroscopic X-ray sequences. Being able to track and thus to estimate the correct positions of these tools is crucial in order to offer guidance enhancement during interventions. The task of estimating the apparent motion is particularly challenging due to the low signal-to-noise ratio (SNR) of fluoroscopic images and due to combined motion components originating from patient breathing and tool interactions performed by the physician. The presented approach is based on modeling interventional tools with B-splines whose optimal configuration of control points is determined through efficient discrete optimization. Each control point corresponds to a discrete random variable in a Markov random field (MRF) formulation where a set of labels represents the deformation space. In this context, the optimal curve corresponds to the maximum a posteriori (MAP) estimate of the MRF energy. The main motivation for employing a discrete approach is the possibility to incorporate a multi-directional search space which is robust to local minima. This is of particular interest for curve tracking under large deformation. This work analyzes feasibility of employing efficient first-order MRFs for tracking. In particular it shows how to achieve a good compromise between energy approximations and computational efficiency. Experimental results suggest to define both the external and internal energy in terms of pairwise potential functions. The method was successfully applied to the tracking of guide-wires in fluoroscopic X-ray sequences of several hundred frames which requires extremely robust techniques. Comparisons with state-of-the-art guide-wire tracking algorithms confirm the effectiveness of the proposed method. © 1982-2012 IEEE

The Lantern Vol. 8, No. 1, December 1939

• Christmas Resurrection • Autumn\u27s Song • Henry Cavendish • The Mystery of Loon Cove • All Hail, Fair Modesty • Mischall • Gift of the Magi • Camera-Phobia • One Envying a Poet • Sonnetshttps://digitalcommons.ursinus.edu/lantern/1019/thumbnail.jp

The Lantern Vol. 7, No. 3, June 1939

• Commencement Sonnet • Largo Appassionato • More Sonnets to Earth • Vladimir • Abe Lincoln in Illinois • Dark Lives • Enter Mr. Smithingham II • A Character is Sketched • Sonnet • Out of the Dawn • Wistaria • Poem Without a Name • You Have Loved the Nighthttps://digitalcommons.ursinus.edu/lantern/1018/thumbnail.jp

The Lantern Vol. 8, No. 3, May 1940

• Sonnet for These Days • Peace Be With You • Creative Citizenship • Tony Solves an Ichthyological Problem • Tippy Tin • A Surgeon Paints • Thoughts • Standing at Ease • Nature\u27s Mistake • Tomorrow • This is Enough • I Built a Shrine to Love • Integer • I Look for Herhttps://digitalcommons.ursinus.edu/lantern/1021/thumbnail.jp

The Lantern Vol. 10, No. 2, April 1942

• Victory • Bobleenatris • Eve, the Apple Polisher • Fame • Rats! • Invasion • Saga of Deeptown • Candide • Wiffenpfooph-Hunting • War • The Conch • Pantomime • Rain • Song of the Little People • The Distant Drums • Advertisementshttps://digitalcommons.ursinus.edu/lantern/1026/thumbnail.jp

The Lantern Vol. 7, No. 2, March 1939

• Editorial • Easter Eggs • Fever • Sonnets to the Planet We Call Earth • Asking Her Father • New Hampshire Ghost Story • Mary • On Approaching Death • On Turning Over a New Leaf • In Defense of Americanism • What is this Love? • Martyrs of Progress • Recurring • Splintershttps://digitalcommons.ursinus.edu/lantern/1013/thumbnail.jp

The Lantern Vol. 7, No. 2, March 1939

• Editorial • Easter Eggs • Fever • Sonnets to the Planet We Call Earth • Asking Her Father • New Hampshire Ghost Story • Mary • On Approaching Death • On Turning Over a New Leaf • In Defense of Americanism • What is this Love? • Martyrs of Progress • Recurring • Splintershttps://digitalcommons.ursinus.edu/lantern/1013/thumbnail.jp

Freshwater ecoregions of the world: A new map of biogeographic units for freshwater biodiversity conservation

We present a new map depicting the first global biogeographic regionalization of Earth's freshwater systems. This map of freshwater ecoregions is based on the distributions and compositions of freshwater fish species and incorporates major ecological and evolutionary patterns. Covering virtually all freshwater habitats on Earth, this ecoregion map, together with associated species data, is a useful tool for underpinning global and regional conservation planning efforts (particularly to identify outstanding and imperiled freshwater systems); for serving as a logical framework for large-scale conservation strategies; and for providing a global-scale knowledge base for increasing freshwater biogeographic literacy. Preliminary data for fish species compiled by ecoregion reveal some previously unrecognized areas of high biodiversity, highlighting the benefit of looking at the world's freshwaters through a new framework.La lista completa de autores que integran el documento puede consultarse en el archivo.Facultad de Ciencias Naturales y Muse