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Full-Text Articles in Biomedical Engineering and Bioengineering

Towards Supervised Autonomous Task Completion Using An In Vivo Surgical Robot, Jason J. Dumpert Oct 2009

Towards Supervised Autonomous Task Completion Using An In Vivo Surgical Robot, Jason J. Dumpert

Department of Mechanical and Materials Engineering: Dissertations, Theses, and Student Research

Laparoscopy is a minimally invasive alternative to traditional abdominal surgery. Unlike traditional surgery, a laparoscopic procedure can be completed using small incisions. The use of these small incision results in reduced pain to the patient, shorter recovery times, and less trauma to skin, muscle and other tissues. However, these benefits to the patient are offset by the increased difficulty to the surgeon performing the procedure. These difficulties include reduced dexterity, reduced perception, and longer procedure times. The use of small in vivo robotic devices in minimally invasive surgery is one possible solution to these problems. The movement of these devices …


Time-Frequency Analysis Of Intracardiac Electrogram, Erik Brockman Jun 2009

Time-Frequency Analysis Of Intracardiac Electrogram, Erik Brockman

Master's Theses

The Cardiac Rhythm Management Division of St. Jude Medical specializes in the development of implantable cardioverter defibrillators that improve the quality of life for patients diagnosed with a variety of cardiac arrhythmias, especially for patients prone to sudden cardiac death. With the goal to improve detection of cardiac arrhythmias, this study explored the value in time-frequency analysis of intracardiac electrogram in four steps. The first two steps characterized, in the frequency domain, the waveforms that construct the cardiac cycle. The third step developed a new algorithm that putatively provides the least computationally expensive way to identifying cardiac waveforms in the …


Automatic Diagnosis For Prostate Cancer Using Run-Length Matrix Method, Xiaoyan Sun, Shao-Hui Chuang, Jiang Li, Frederic Mckenzie, Nico Karssemeijer (Ed.), Maryellen L. Giger (Ed.) Jan 2009

Automatic Diagnosis For Prostate Cancer Using Run-Length Matrix Method, Xiaoyan Sun, Shao-Hui Chuang, Jiang Li, Frederic Mckenzie, Nico Karssemeijer (Ed.), Maryellen L. Giger (Ed.)

Electrical & Computer Engineering Faculty Publications

Prostate cancer is the most common type of cancer and the second leading cause of cancer death among men in US1. Quantitative assessment of prostate histology provides potential automatic classification of prostate lesions and prediction of response to therapy. Traditionally, prostate cancer diagnosis is made by the analysis of prostate-specific antigen (PSA) levels and histopathological images of biopsy samples under microscopes. In this application, we utilize a texture analysis method based on the run-length matrix for identifying tissue abnormalities in prostate histology. A tissue sample was collected from a radical prostatectomy, H&E fixed, and assessed by a pathologist …


Optimizing Computer-Aided Colonic Polyp Detection For Ct Colonography By Evolving The Pareto Front, Jiang Li, Adam Huang, Jack Tao, Jiamin Liu, Robert L. Van Uitert, Nicholas Petrick, Ronald Summers Jan 2009

Optimizing Computer-Aided Colonic Polyp Detection For Ct Colonography By Evolving The Pareto Front, Jiang Li, Adam Huang, Jack Tao, Jiamin Liu, Robert L. Van Uitert, Nicholas Petrick, Ronald Summers

Electrical & Computer Engineering Faculty Publications

A multiobjective genetic algorithm is designed to optimize a computer-aided detection (CAD) system for identifying colonic polyps. Colonic polyps appear as elliptical protrusions on the inner surface of the colon. Curvature-based features for colonic polyp detection have proved to be successful in several CT colonography (CTC) CAD systems. Our CTC CAD program uses a sequential classifier to form initial polyp detections on the colon surface. The classifier utilizes a set of thresholds on curvature-based features to cluster suspicious colon surface regions into polyp candidates. The thresholds were previously chosen experimentally by using feature histograms. The chosen thresholds were effective for …


Parameter Optimization For Image Denoising Based On Block Matching And 3d Collaborative Filtering, Ramu Pedada, Emin Kugu, Jiang Li, Zhanfeng Yue, Yuzhong Shen, Josien P.W. Pluim (Ed.), Benoit M. Dawant (Ed.) Jan 2009

Parameter Optimization For Image Denoising Based On Block Matching And 3d Collaborative Filtering, Ramu Pedada, Emin Kugu, Jiang Li, Zhanfeng Yue, Yuzhong Shen, Josien P.W. Pluim (Ed.), Benoit M. Dawant (Ed.)

Electrical & Computer Engineering Faculty Publications

Clinical MRI images are generally corrupted by random noise during acquisition with blurred subtle structure features. Many denoising methods have been proposed to remove noise from corrupted images at the expense of distorted structure features. Therefore, there is always compromise between removing noise and preserving structure information for denoising methods. For a specific denoising method, it is crucial to tune it so that the best tradeoff can be obtained. In this paper, we define several cost functions to assess the quality of noise removal and that of structure information preserved in the denoised image. Strength Pareto Evolutionary Algorithm 2 (SPEA2) …