Computerized Medical Imaging and Graphics RSS feed: Articles in Press. The purpose of the journal Computerized Medical Imaging and Graphics is to act as a source for the exchange of information concerning the medical use of new developments in imaging diagnosis, intervention, and follow up. Included in the journal will be articles on new medical scanning techniques, image-guided therapy, computer-aided diagnosis, robotic surgery and imaging, augmented-reality medical visualization, imaging genomics, reports of new advances in imaging modalities, and all other information related to the application of computerized radiology, oncology, and surgery. In addition, information on non-medical modes of imaging that have medical applications such as confocal and multi-photon microscopy, optical microendoscope, photoacoustic imaging, infra-red radiation, and other imaging modalities would be welcomed. The journal is a vehicle for the rapid publication of original research papers and review articles in the field of computerized medical imaging and graphics. Papers published in the journal will be of interest to computer scientists, medical physicists, bioengineers, imaging specialists, medical informaticians, computational biologists, radiologists, oncologists, neurologists, neurosurgeons, surgeons, cardiologists, cardiovascular surgeons, nuclear medicine physicians, pathologists, ophthalmologists, proctologists, nephrologists, gastroenterologists, and internists interested in imaging applications. Please note this Journal accepts neither Case Reports nor preliminary publications. http://www.medicalimagingandgraphics.com//inpress?rss=yesElsevier Inc.en © 2012 Elsevier Ltd. All rights reserved. Computerized Medical Imaging and Graphics0895-61112012-01-30 © 2012 Elsevier Ltd. All rights reserved. healthpermissions@elsevier.comhttp://www.medicalimagingandgraphics.com/article/PIIS0895611112000031/abstract?rss=yesAbstract: In this paper a method which combines iterative computed tomography reconstruction and coronary centerline extraction technique to obtain motion artifact-free reconstructed images of the coronary arteries are proposed and evaluated. The method relies on motion-vector fields derived from a set of coronary centerlines extracted at multiple cardiac phases within the R–R interval. Hereto, start and end points are provided by the user in one time-frame only. Using an elastic image registration, these points are propagated to all the remaining cardiac phases. Consequently, a multi-phase three-dimensional coronary centerline is determined by applying a semi-automatic minimum cost path based extraction method. Corresponding centerline positions are used to determine the relative motion-vector fields from phase to phase. Finally, dense motion-vector fields are achieved by thin-plate-spline interpolation and used to perform a motion-corrected iterative reconstruction of a selected region of interest. The performance of the method is validated on five patients, showing the improved sharpness of cardiac motion-corrected gated iterative reconstructions compared to the results achieved by a classical gated iterative method. The results are also compared to known manual and fully automatic coronary artery motion estimation methods.Cardiac motion-corrected iterative cone-beam CT reconstruction using a semi-automatic minimum cost path-based coronary centerline extraction - Corrected ProofA.A. Isola, C.T. Metz, M. Schaap, S. Klein, M. Grass, W.J. Niessen10.1016/j.compmedimag.2011.12.005Computerized Medical Imaging and Graphics (2012)2012-01-30Computerized Medical Imaging and Graphics2012-01-30http://www.medicalimagingandgraphics.com/article/PIIS0895611111001480/abstract?rss=yesAbstract: We designed a generic method for segmenting the aneurismal sac of an abdominal aortic aneurysm (AAA) both from multi-slice MR and CT-scan examinations. It is a semi-automatic method requiring little human intervention and based on graph cut theory to segment the lumen interface and the aortic wall of AAAs. Our segmentation method works independently on MRI and CT-scan volumes and has been tested on a 44 patient dataset and 10 synthetic images. Segmentation and maximum diameter estimation were compared to manual tracing from 4 experts. An inter-observer study was performed in order to measure the variability range of a human observer. Based on three metrics (the maximum aortic diameter, the volume overlap and the Hausdorff distance) the variability of the results obtained by our method is shown to be similar to that of a human operator, both for the lumen interface and the aortic wall. As will be shown, the average distance obtained with our method is less than one standard deviation away from each expert, both for healthy subjects and for patients with AAA. Our semi-automatic method provides reliable contours of the abdominal aorta from CT-scan or MRI, allowing rapid and reproducible evaluations of AAA.3D segmentation of abdominal aorta from CT-scan and MR images - Corrected ProofAnthony Adam Duquette, Pierre-Marc Jodoin, Olivier Bouchot, Alain Lalande10.1016/j.compmedimag.2011.12.001Computerized Medical Imaging and Graphics (2012)2012-01-18Computerized Medical Imaging and Graphics2012-01-18http://www.medicalimagingandgraphics.com/article/PIIS0895611111001492/abstract?rss=yesAbstract: In this work, we present modeling and visualization techniques for virtual stenting of aneurysms and stenoses. In particular, contributions to support the computer-aided treatment of artery diseases – artery enlargement (aneurysm) and artery contraction (stenosis) – are made. If an intervention takes place, there are two different treatment alternatives for this kind of artery diseases: open surgery and minimally invasive (endovascular) treatment. Computer-assisted optimization of endovascular treatments is the main focus of our work. In addition to stent simulation techniques, we also present a computer-aided simulation of endoluminal catheters to support the therapy-planning phase. The stent simulation is based on a three-dimensional Active Contour Method and is applicable to both non-bifurcated (I-stents) and bifurcated stents (Y-stents). All methods are introduced in detail and are evaluated with phantom datasets as well as with real patient data from the clinical routine. Additionally, the clinical prototype that is based upon these methods is described.Modeling and visualization techniques for virtual stenting of aneurysms and stenoses - Corrected ProofJan Egger, Stefan Grosskopf, Christopher Nimsky, Tina Kapur, Bernd Freisleben10.1016/j.compmedimag.2011.12.002Computerized Medical Imaging and Graphics (2012)2012-01-09Computerized Medical Imaging and Graphics2012-01-09http://www.medicalimagingandgraphics.com/article/PIIS0895611111001248/abstract?rss=yesAbstract: A novel imaging technique can now provide microscopic images of the distal lung in vivo, for which quantitative analysis tools need to be developed. In this paper, we present an image classification system that is able to discriminate between normal and pathological images. Different feature spaces for discrimination are investigated and evaluated using a support vector machine. Best classification rates reach up to 90% and 95% on non-smoker and smoker groups, respectively. A feature selection process is also implemented, that allows us to gain some insight about these images. Whereas further tests on extended databases are needed, these first results indicate that efficient computer based automated classification of normal vs. pathological images of the distal lung is feasible.An SVM-based distal lung image classification using texture descriptors - Corrected ProofChesner Désir, Caroline Petitjean, Laurent Heutte, Luc Thiberville, Mathieu Salaün10.1016/j.compmedimag.2011.11.001Computerized Medical Imaging and Graphics (2011)2011-12-19Computerized Medical Imaging and Graphics2011-12-19http://www.medicalimagingandgraphics.com/article/PIIS0895611111001236/abstract?rss=yesAbstract: In modern epidemiological population-based studies a huge amount of magnetic resonance imaging (MRI) data is analysed. This requires reliable automatic methods for organ extraction. In the current paper, we propose a fast and accurate automatic method for lung segmentation and volumetry. Our approach follows a “coarse-to-fine” segmentation strategy. First, we extract the lungs and trachea excluding the main pulmonary vessels. This step is executed very fast and allows for measuring the volume of both structures. Thereafter, we start a refinement procedure that consists of three main stages: trachea extraction, lung separation, and filling the cavities on the final lung masks. After the trachea extraction step the volumes of both lungs without the main vessels can be measured. The final segmentation step results in the volumes of the left and right lungs including the vessels. The method has been tested by processing MR datasets from ten healthy participants. We compare our results with manually produced masks and obtain high agreement between the expert reading and our method: the True Positive Volume Fraction is more than 95%. The proposed automatic approach is fast and accurate enough to be applied in clinical routine for processing of thousands of participants.A fast and accurate automatic lung segmentation and volumetry method for MR data used in epidemiological studies - Corrected ProofTetyana Ivanovska, Katrin Hegenscheid, Rene Laqua, Jens-P. Kühn, Sven Gläser, Ralf Ewert, Norbert Hosten, Ralf Puls, Henry Völzke10.1016/j.compmedimag.2011.10.001Computerized Medical Imaging and Graphics (2011)2011-11-14Computerized Medical Imaging and Graphics2011-11-14http://www.medicalimagingandgraphics.com/article/PIIS0895611111001212/abstract?rss=yesAbstract: Fluorescent proteins (FPs) have been widely adopted in cell research for protein trafficking and reporter gene expression studies, as well as to study other biological processes. However, biological tissue has high light scattering and high absorption coefficients of visible light; hence, using FPs in small animal imaging remains a challenge, especially when the FPs are located deep in the tissue. In small animals, fluorescence molecular imaging could potentially address this difficulty. We constructed fluorescence molecular imaging systems that have two modes: a planner mode (projection imaging) and a multimodality mode (fluorescence molecular tomography and micro-CT). The planner mode can provide projection images of a fluorophore in the whole body of a small animal, whereas three-dimensional information can be offered by multimodality mode. The planner imaging system works in the reflection mode and is designed to provide fast imaging. The multimodality imaging system is designed to allow quantification and three-dimensional localization of fluorophores. A nude mouse with a tumour targeted with a far-red FP, which is appropriate for in vivo imaging, was adopted to validate the two systems. The results indicate that the planner imaging system is probably suitable for high throughput molecular imaging, whereas the multimodality imaging system is fit for quantitative research.Molecular imaging of small animals with fluorescent proteins: From projection to multimodality - Corrected ProofXiaoquan Yang, Hui Gong, Jianwei Fu, Guotao Quan, Chuan Huang, Qingming Luo10.1016/j.compmedimag.2011.09.002Computerized Medical Imaging and Graphics (2011)2011-10-26Computerized Medical Imaging and Graphics2011-10-26http://www.medicalimagingandgraphics.com/article/PIIS0895611111001182/abstract?rss=yesAbstract: Stereoscopic MRA acquires a pair of blood vessel projections at two different viewing angles. Previously, we have developed two algorithms to reconstruct 3-D blood vessels from stereoscopic MRA. The assumption we made was that blood vessels were tilting circular tubes and the shape of the vessel on every cross-section was an ellipse. Since an ellipse can be represented in either algebraic form or parametric form, our previous algorithms reconstructed the ellipses by representing them in these two forms. In this paper, we further improved the accuracy of our previous algorithms by an order through two enhancements. The first improvement we made was a better method to estimate the rotation angle of the major axis of an ellipse. Instead of using the center of two adjacent ellipses to estimate the rotation angle as in our previous method, the new method used the projection lengths of the two views to estimate the angle. The second improvement we made was the equation to describe the relationship between the major/minor axes and the projection lengths. In our experiments, the average estimation error for the parametric algorithm was improved from 0.471 pixels to 0.066 pixels. The average error for the algebraic algorithm was improved from 0.101 pixels to 0.014 pixels.Three-dimensional elliptical reconstruction for stereoscopic magnetic resonance angiography - Corrected ProofJan-Ray Liao, Shye-Chorng Kuo10.1016/j.compmedimag.2011.08.003Computerized Medical Imaging and Graphics (2011)2011-09-07Computerized Medical Imaging and Graphics2011-09-07http://www.medicalimagingandgraphics.com/article/PIIS0895611111001170/abstract?rss=yesAbstract: Multi-photon fluorescence microscopy (MFM) captures high-resolution fluorescence image sequences and can be used for the intact brain imaging of small animals. Recently, it has been extended from anesthetized and head-stabilized mice to awake and head-restrained ones for in vivo neurological study. In these applications, motion correction is an important pre-processing step since brain pulsation and body movement can cause motion artifact and prevent stable serial image acquisition at such high spatial resolution. This paper proposes a speed embedded Hidden Markov model (SEHMM) for motion correction in MFM imaging of awake head-restrained mice. The algorithm extends the traditional Hidden Markov model (HMM) method by embedding a motion prediction model to better estimate the state transition probability. The novelty of the method lies in using adaptive probability to estimate the linear motion, while the state-of-the-art method assumes that the highest probability is assigned to the case with no motion. In experiments we demonstrated that SEHMM is more accurate than the traditional HMM using both simulated and real MFM image sequences.Motion correction for cellular-resolution multi-photon fluorescence microscopy imaging of awake head-restrained mice using speed embedded HMM - Corrected ProofTaoyi Chen, Zhong Xue, Changhong Wang, Zhenshen Qu, Kelvin K. Wong, Stephen T.C. Wong10.1016/j.compmedimag.2011.08.002Computerized Medical Imaging and Graphics (2011)2011-09-05Computerized Medical Imaging and Graphics2011-09-05http://www.medicalimagingandgraphics.com/article/PIIS0895611111001054/abstract?rss=yesAbstract: Perfusion analysis computes blood flow parameters (blood volume, blood flow, and mean transit time) from the observed flow of a contrast agent passing through the patient's vascular system. Perfusion deconvolution has been widely accepted as the principal numerical tool for perfusion analysis, and is used routinely in clinical applications. The extensive use of perfusion in clinical decision-making makes numerical stability and robustness of perfusion computations vital for accurate diagnostics and patient safety.The main goal of this paper is to propose a novel approach for validating numerical properties of perfusion algorithms. The approach is based on the Perfusion Linearity Property (PLP), which is fundamental to virtually all perfusion data processing. PLP allows one to study perfusion values as weighted averages of the original imaging data. This, in turn, uncovers hidden problems with the existing perfusion techniques, and may be used to suggest more reliable computational approaches and methodology.Perfusion linearity and its applications in perfusion algorithm analysis - Corrected ProofOleg S. Pianykh10.1016/j.compmedimag.2011.08.001Computerized Medical Imaging and Graphics (2011)2011-08-26Computerized Medical Imaging and Graphics2011-08-26http://www.medicalimagingandgraphics.com/article/PIIS0895611111001017/abstract?rss=yesAbstract: This paper describes the methodology used to create a multimedia collection of cases with interstitial lung diseases (ILDs) at the University Hospitals of Geneva. The dataset contains high-resolution computed tomography (HRCT) image series with three-dimensional annotated regions of pathological lung tissue along with clinical parameters from patients with pathologically proven diagnoses of ILDs. The motivations for this work is to palliate the lack of publicly available collections of ILD cases to serve as a basis for the development and evaluation of image-based computerized diagnostic aid. After 38 months of data collection, the library contains 128 patients affected with one of the 13 histological diagnoses of ILDs, 108 image series with more than 41l of annotated lung tissue patterns as well as a comprehensive set of 99 clinical parameters related to ILDs. The database is available for research on request and after signature of a license agreement.Building a reference multimedia database for interstitial lung diseases - Corrected ProofAdrien Depeursinge, Alejandro Vargas, Alexandra Platon, Antoine Geissbuhler, Pierre-Alexandre Poletti, Henning Müller10.1016/j.compmedimag.2011.07.003Computerized Medical Imaging and Graphics (2011)2011-08-01Computerized Medical Imaging and Graphics2011-08-01http://www.medicalimagingandgraphics.com/article/PIIS0895611111000851/abstract?rss=yesAbstract: Common carotid artery intima–media thickness (IMT), which is usually measured upon ultrasound images, is an important indicator to cardiovascular diseases. This paper proposes a snake model based segmentation method to automatically detect the boundary of intima–media for IMT measurement. In the proposed method, two contours are initialized from line segments generated by Hough transform and then evolved simultaneously by dual snake model for boundary detection. Experimental results show that the proposed method has strong robustness against ultrasound artifacts, gives better results than traditional snake model and dynamic programming based methods, and achieves similar clinical parameters to ground truth data.Ultrasound intima–media segmentation using Hough transform and dual snake model - Corrected ProofXiangyang Xu, Yuan Zhou, Xinyao Cheng, Enmin Song, Guokuan Li10.1016/j.compmedimag.2011.06.007Computerized Medical Imaging and Graphics (2011)2011-07-08Computerized Medical Imaging and Graphics2011-07-08http://www.medicalimagingandgraphics.com/article/PIIS0895611111000656/abstract?rss=yesAbstract: The structure of an early fetal heart provides vital information for the diagnosis of fetus defects. However, early fetal hearts are difficult to detect due to their relatively small size and the low signal-to-noise ratio of ultrasound images. In this paper, a novel method is proposed for automatic detection of early fetal cardiac structure from ultrasound images. The proposed method consists of two major parts which are the preprocessing phase and the active cardiac model: (1) The preprocessing phase consists of two sub-steps. (a) The region of interest is first automatically selected based on an accumulated motion image, which is able to represent the motion information of the fetal heart more accurately. (b) Then by combining Rayleigh-trimmed filter and anisotropic diffusion in 3-dimensional space, a despeckling method is developed to suppress the speckle noise and emphasize the motion information for subsequent cardiac structure detection. (2) The active cardiac model is proposed for the detection of fetal heart structure, which is a key contribution of this paper. It takes into account both the structure and motion information of fetal hearts simultaneously. Both learning and inference of the active cardiac model are described in the paper. Experiments on seven ultrasound sequences demonstrate the effectiveness of the proposed method.Active cardiac model and its application on structure detection from early fetal ultrasound sequences - Corrected ProofYinhui Deng, Yuanyuan Wang, Yuzhong Shen, Ping Chen10.1016/j.compmedimag.2011.04.002Computerized Medical Imaging and Graphics (2011)2011-05-30Computerized Medical Imaging and Graphics2011-05-30