Alexandros Karargyris
National Institutes of Health
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Featured researches published by Alexandros Karargyris.
World Journal of Gastroenterology | 2013
Anastasios Koulaouzidis; Emanuele Rondonotti; Alexandros Karargyris
The introduction of capsule endoscopy (CE) in clinical practice increased the interest for the study of the small-bowel. Consequently, in about 10 years, an impressive quantity of literature on indications, diagnostic yield (DY), safety profile and technical evolution of CE has been published as well as several reviews. At present time, there are 5 small-bowel capsule enteroscopy (SBCE) models in the worldwide market. Head-to-head trials have showed in the great majority of studies comparable results in terms of DY, image quality and completion rate. CE meta-analyses formed the basis of national/international guidelines; these guidelines place CE in a prime position for the diagnostic work-up of patients with obscure gastrointestinal bleeding, known and/or suspected Crohns disease and possible small-bowel neoplasia. A 2-L polyethylene glycol-based purge, administered the day before the procedure, is the most widely practiced preparation regimen. Whether this regimen can be further improved (i.e., by further decreasing its volume, changing the timing of administration, coupling it with prokinetics and/or other factors) or if it can really affect the DY, is still under discussion. Faecal calprotectin has been used in SBCE studies in two settings: in patients taking non-steroidal anti-inflammatory drugs, to evaluate the type and extent of mucosal damage and, more importantly from a clinical point of view, in patients with known or suspected Crohns disease for assessment of inflammation activity. Although there is still a lot of debate around the exact reasons of SBCE poor performance in various small-bowel segments, it is worth to remember that the capsule progress is non-steerable, hence more rapid in the proximal than in lower segments of the small-bowel. Capsule aspiration, a relatively unexpected complication, has been reported with increasing frequency. This is probably related with the increase in the mean age of patients undergoing CE. CE video review is a time-consuming procedure. Therefore, several attempts have been made to develop technical software features, in order to make CE video analysis easier and shorter (without jeopardizing its accuracy). Suspected Blood Indicator, QuickView and Fujinon Intelligent Chromo Endoscopy are some of the software tools that have been checked in various clinical studies to date.
IEEE Transactions on Medical Imaging | 2014
Sema Candemir; Stefan Jaeger; Kannappan Palaniappan; Jonathan P. Musco; Rahul Singh; Zhiyun Xue; Alexandros Karargyris; Sameer K. Antani; George R. Thoma; Clement J. McDonald
The National Library of Medicine (NLM) is developing a digital chest X-ray (CXR) screening system for deployment in resource constrained communities and developing countries worldwide with a focus on early detection of tuberculosis. A critical component in the computer-aided diagnosis of digital CXRs is the automatic detection of the lung regions. In this paper, we present a nonrigid registration-driven robust lung segmentation method using image retrieval-based patient specific adaptive lung models that detects lung boundaries, surpassing state-of-the-art performance. The method consists of three main stages: 1) a content-based image retrieval approach for identifying training images (with masks) most similar to the patient CXR using a partial Radon transform and Bhattacharyya shape similarity measure, 2) creating the initial patient-specific anatomical model of lung shape using SIFT-flow for deformable registration of training masks to the patient CXR, and 3) extracting refined lung boundaries using a graph cuts optimization approach with a customized energy function. Our average accuracy of 95.4% on the public JSRT database is the highest among published results. A similar degree of accuracy of 94.1% and 91.7% on two new CXR datasets from Montgomery County, MD, USA, and India, respectively, demonstrates the robustness of our lung segmentation approach.
IEEE Transactions on Medical Imaging | 2014
Stefan Jaeger; Alexandros Karargyris; Sema Candemir; Les R. Folio; Jenifer Siegelman; Fiona M. Callaghan; Zhiyun Xue; Kannappan Palaniappan; Rahul K. Singh; Sameer K. Antani; George R. Thoma; Yi-Xiang J. Wang; Pu-Xuan Lu; Clement J. McDonald
Tuberculosis is a major health threat in many regions of the world. Opportunistic infections in immunocompromised HIV/AIDS patients and multi-drug-resistant bacterial strains have exacerbated the problem, while diagnosing tuberculosis still remains a challenge. When left undiagnosed and thus untreated, mortality rates of patients with tuberculosis are high. Standard diagnostics still rely on methods developed in the last century. They are slow and often unreliable. In an effort to reduce the burden of the disease, this paper presents our automated approach for detecting tuberculosis in conventional posteroanterior chest radiographs. We first extract the lung region using a graph cut segmentation method. For this lung region, we compute a set of texture and shape features, which enable the X-rays to be classified as normal or abnormal using a binary classifier. We measure the performance of our system on two datasets: a set collected by the tuberculosis control program of our local countys health department in the United States, and a set collected by Shenzhen Hospital, China. The proposed computer-aided diagnostic system for TB screening, which is ready for field deployment, achieves a performance that approaches the performance of human experts. We achieve an area under the ROC curve (AUC) of 87% (78.3% accuracy) for the first set, and an AUC of 90% (84% accuracy) for the second set. For the first set, we compare our system performance with the performance of radiologists. When trying not to miss any positive cases, radiologists achieve an accuracy of about 82% on this set, and their false positive rate is about half of our systems rate.
IEEE Transactions on Biomedical Engineering | 2011
Alexandros Karargyris; Nikolaos G. Bourbakis
Over the last decade, wireless capsule endoscopy (WCE) technology has become a very useful tool for diagnosing diseases within the human digestive tract. Physicians using WCE can examine the digestive tract in a minimally invasive way searching for pathological abnormalities such as bleeding, polyps, ulcers, and Crohns disease. To improve effectiveness of WCE, researchers have developed software methods to automatically detect these diseases at a high rate of success. This paper proposes a novel synergistic methodology for automatically discovering polyps (protrusions) and perforated ulcers in WCE video frames. Finally, results of the methodology are given and statistical comparisons are also presented relevant to other works.
IEEE Engineering in Medicine and Biology Magazine | 2010
Alexandros Karargyris; Nikolaos G. Bourbakis
The purpose of this study was to serve as a reference for further research improvements and to address the current level of maturity of each methodology from its maximum capabilities. This paper discussed the following: automatic detection of intestinal juices in wireless capsule video endoscopy; neural networks-based approach; model of deformable rings for aiding the WCE video interpretation and reporting; digestive organ automatic image classification; WCE blood detection using expectation maximization clustering; discriminate tissues color distributions; color- and texture-based GI tissue discrimination; topographic segmentation and transit time estimation for endoscopic capsule exams; automated tissue classification; colonoscopic diagnosis using online learning and differential evolution; computer-aided tumor detection using color wavelet features; versatile coLD detection system for colorectal lesions; images sequences; blood-based abnormalities detection; and other related topics.
IEEE Transactions on Medical Imaging | 2011
Alexandros Karargyris; Nikolaos G. Bourbakis
Wireless capsule endoscopy is a revolutionary technology that allows physicians to examine the digestive tract of a human body in the minimum invasive way. Physicians can detect diseases such as blood-based abnormalities, polyps, ulcers, and Crohns disease. Although this technology is really a marvel of our modern times, currently it suffers from two serious drawbacks: 1) frame rate is low (3 frames/s) and 2) no 3-D representation of the objects is captured from the camera of the capsule. In this paper we offer solutions (methodologies) that deal with each of the above issues improving the current technology without forcing hardware upgrades. These methodologies work synergistically to create smooth and visually friendly interpolated images from consecutive frames, while preserving the structure of the observed objects. They also extract and represent the texture of the surface of the digestive tract in 3-D. Thus the purpose of our methodology is not to reduce the time that the gastroenterologists need to spend to examine the video. On the contrary, the purpose is to enhance the video and therefore improve the viewing of the digestive tract leading to a more qualitative and efficient examination. The proposed work introduces 3-D capsule endoscopy textured results that have been welcomed by Digestive Specialists, Inc., Dayton, OH. Finally, illustrative results are given at the end of the paper.
Quantitative imaging in medicine and surgery | 2013
Stefan Jaeger; Alexandros Karargyris; Sema Candemir; Jenifer Siegelman; Les R. Folio; Sameer K. Antani; George R. Thoma
Tuberculosis (TB) is a major global health threat. An estimated one-third of the worlds population has a history of TB infection, and millions of new infections are occurring every year. The advent of new powerful hardware and software techniques has triggered attempts to develop computer-aided diagnostic systems for TB detection in support of inexpensive mass screening in developing countries. In this paper, we describe the medical background of TB detection in chest X-rays and present a survey of the recent approaches using computer-aided detection. After a thorough research of the computer science literature for such systems or related methods, we were able to identify 16 papers, including our own, written between 1996 and early 2013. These papers show that TB screening is a challenging task and an open research problem. We report on the progress to date and describe experimental screening systems that have been developed.
international conference of the ieee engineering in medicine and biology society | 2012
Stefan Jaeger; Alexandros Karargyris; Sameer K. Antani; George R. Thoma
Tuberculosis (TB) is a major health threat in many regions of the world, while diagnosing tuberculosis still remains a challenge. Mortality rates of patients with undiagnosed TB are high. Modern diagnostic techniques are often too slow or too expensive for highly-populated developing countries that bear the brunt of the disease. In an effort to reduce the burden of the disease, this paper presents an automated approach for detecting TB on conventional posteroanterior chest radiographs. The idea is to provide developing countries, which have limited access to radiological services and radiological expertise, with an inexpensive detection system that allows screening of large parts of the population in rural areas. In this paper, we present results produced by our TB screening system. We combine a lung shape model, a segmentation mask, and a simple intensity model to achieve a better segmentation mask for the lung. With the improved masks, we achieve an area under the ROC curve of more than 83%, measured on data compiled within a tuberculosis control program.
World Journal of Gastroenterology | 2015
Anastasios Koulaouzidis; Dimitris K. Iakovidis; Alexandros Karargyris; Emanuele Rondonotti
Currently, the major problem of all existing commercial capsule devices is the lack of control of movement. In the future, with an interface application, the clinician will be able to stop and direct the device into points of interest for detailed inspection/diagnosis, and therapy delivery. This editorial presents current commercially-available new designs, European projects and delivery capsule and gives an overview of the progress required and progress that will be achieved -according to the opinion of the authors- in the next 5 year leading to 2020.
ieee/nih life science systems and applications workshop | 2009
Alexandros Karargyris; Nikolaos G. Bourbakis
Wireless Capsule Endoscopy (WCE) is a very useful technology that enables gastroenterologists to examine the human digestive tract and more particularly, the small bowel, searching for various abnormalities like blood-based abnormalities, ulcers and polyps. Each WCE video consists of approximately 50,000 frames making its examination a very tedious task. In this paper a methodology is proposed for the automatic detection of polyps. It utilizes the very promising Log Gabor filters as a segmentation scheme, in conjunction with the powerful SUSAN edge detector. After segmentation process, geometric information of the resulted segments is extracted to identify polyp candidates. Furthermore, certain rules apply to limit the number of false positive detections. Illustrative and statistical results of the methodology are also given in this paper.