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Full-Text Articles in Biomedical Engineering and Bioengineering

Novel Magnetic Resonance Imaging-Compatible Mechatronic Needle Guidance System For Prostate Focal Laser Ablation Therapy, Eric R. Knull Aug 2023

Novel Magnetic Resonance Imaging-Compatible Mechatronic Needle Guidance System For Prostate Focal Laser Ablation Therapy, Eric R. Knull

Electronic Thesis and Dissertation Repository

Advances in prostate cancer (PCa) screening techniques have led to diagnosis of many cases of low-grade and highly localized disease. Conventional whole-gland therapies often result in overtreatment in such cases and debate still surrounds the optimal method of oncologic control. MRI-guided prostate focal laser ablation (FLA) is a minimally invasive treatment option, which has demonstrated potential to destroy localized lesions while sparing healthy prostatic tissue, thereby reducing treatment-related side effects. Many challenges still exist in the development of FLA, including patient selection; tumour localization, visualization, and characterization; needle guidance; and evaluation of treatment efficacy. The objective of this thesis work …


Computer-Assisted Characterization Of Prostate Cancer On Magnetic Resonance Imaging, Derek J. Soetemans Mar 2017

Computer-Assisted Characterization Of Prostate Cancer On Magnetic Resonance Imaging, Derek J. Soetemans

Electronic Thesis and Dissertation Repository

Prostate cancer (PCa) is one of the most prevalent cancers among men. Early diagnosis can improve survival and reduce treatment costs. Current inter-radiologist variability for detection of PCa is high. The use of multi-parametric magnetic resonance imaging (mpMRI) with machine learning algorithms has been investigated both for improving PCa detection and for PCa diagnosis. Widespread clinical implementation of computer-assisted PCa lesion characterization remains elusive; critically needed is a model that is validated against a histologic reference standard that is densely sampled in an unbiased fashion. We address this using our technique for highly accurate fusion of mpMRI with whole-mount …


Prostate Cancer Region Prediction Using Maldi Mass Spectra, Ayyappa Vadlamudi, Shao-Hui Chuang, Xiaoyan Sun, Lisa Cazares, Julius Nyalwidhe, Dean Troyer, O. John Semmes, Jiang Li, Frederic D. Mckenzie Jan 2010

Prostate Cancer Region Prediction Using Maldi Mass Spectra, Ayyappa Vadlamudi, Shao-Hui Chuang, Xiaoyan Sun, Lisa Cazares, Julius Nyalwidhe, Dean Troyer, O. John Semmes, Jiang Li, Frederic D. Mckenzie

Electrical & Computer Engineering Faculty Publications

For the early detection of prostate cancer, the analysis of the Prostate-specific antigen (PSA) in serum is currently the most popular approach. However, previous studies show that 15% of men have prostate cancer even their PSA concentrations are low. MALDI Mass Spectrometry (MS) proves to be a better technology to discover molecular tools for early cancer detection. The molecular tools or peptides are termed as biomarkers. Using MALDI MS data from prostate tissue samples, prostate cancer biomarkers can be identified by searching for molecular or molecular combination that can differentiate cancer tissue regions from normal ones. Cancer tissue regions are …


Adjacent Slice Prostate Cancer Prediction To Inform Maldi Imaging Biomarker Analysis, Shao-Hui Chuang Jul 2009

Adjacent Slice Prostate Cancer Prediction To Inform Maldi Imaging Biomarker Analysis, Shao-Hui Chuang

Electrical & Computer Engineering Theses & Dissertations

Prostate cancer is the second most common type of cancer among men in the U.S. [1]. Traditionally, prostate cancer diagnosis is made by the analysis of prostate-specific antigen (PSA) levels and histopathological images of biopsy samples under microscopes. Proteomic biomarkers can improve upon these methods. MALDI molecular spectra imaging is used to visualize protein/peptide concentrations across biopsy samples to search for biomarker candidates. Unfortunately, traditional processing methods require histopathological examination on one slice of a biopsy sample while the adjacent slice is subjected to the tissue destroying desorption and ionization processes of MALDI. The highest confidence tumor regions gained from …


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 …