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Biomedical Engineering and Bioengineering Commons™
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Full-Text Articles in Biomedical Engineering and Bioengineering
Icloudecg: A Mobile Cardiac Telemedicine System, David S. Clifford
Icloudecg: A Mobile Cardiac Telemedicine System, David S. Clifford
Masters Theses
With rising healthcare costs and a substantially growing number of patients 65 or over, the benefits of telemedicine and patient self-monitoring systems are becoming increasingly evident. Patients, physicians, hospitals, and even insurance providers benefit from vigilant, cost-effective patient monitoring systems. This thesis describes the development of a portable, smart-phone connected system for continuous cardiac monitoring. The system is capable of continuously monitoring the conditions of the heart, automated detection of cardiac arrhythmias, and real-time notifying patients and physicians of the detected abnormalities. The system consists of four main subsystems: 1) a Bluetooth capable chest-strap ECG, 2) an Android-enabled mobile device, …
Computer Aided Diagnosis Of Oral Cancer: Using Time-Step Ct Images, Jonathan T. Scott
Computer Aided Diagnosis Of Oral Cancer: Using Time-Step Ct Images, Jonathan T. Scott
Masters Theses
"In medical imaging it is a very common practice to use a technique known as Time-Step imaging in patients who might develop cancer. Time-Step imaging it a very powerful technique, however it can lead to unmanageable amounts of image data. Previously the only way to search all of this data was to manually look through all of the files. This had to be done by trained professionals who knew what to look for within the images and make a judgment about the patient based on the images. This paper discusses the development of an algorithm to have a computer search …
Computer Aided Detection Of Oral Lesions On Ct Images, Shaikat Mahmood Galib
Computer Aided Detection Of Oral Lesions On Ct Images, Shaikat Mahmood Galib
Masters Theses
"Oral lesions are important findings on computed tomography images. They are difficult to detect on CT images because of low contrast, arbitrary orientation of objects, complicated topology and lack of clear lines indicating lesions. In this thesis, a fully automatic method to detect oral lesions from dental CT images is proposed to identify (1) Closed boundary lesions and (2) Bone deformation lesions. Two algorithms were developed to recognize these two types of lesions, which cover most of the lesion types that can be found on CT images. The results were validated using a dataset of 52 patients. Using non training …