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Bioimaging and Biomedical Optics Commons™
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Articles 1 - 5 of 5
Full-Text Articles in Bioimaging and Biomedical Optics
Feasibility Of Using Raman-Based Techniques For Breast Cancer Detection, Sara Mollamohammada
Feasibility Of Using Raman-Based Techniques For Breast Cancer Detection, Sara Mollamohammada
Department of Civil and Environmental Engineering: Dissertations, Theses, and Student Research
Breast cancer is one of the common types of cancer among women all over the world. Early diagnosis is an effective way that improve the treatment process and gives the patients a better chance of survival. Many of the patients infected by breast cancer choose breast conservation surgery (BCS). However, some of those will be subjected to mastectomy, and many will have tumor recurrence as there is no precise technique to show the tumor margins. Raman-based methods are powerful techniques with potential to rapidly differentiate normal from tumor tissues and provides a solution to detect tumor margin. This is because …
Calibration And Optimization Of 3d Digital Breast Tomosynthesis Guided Near Infrared Spectral Tomography, Kelly E. Michaelsen, Venkataramanan Krishnaswamy, Linxi Shi, Srinivasan Vedantham, Steven Poplack, Andrew Karellas, Brian Pogue, Keith Paulsen
Calibration And Optimization Of 3d Digital Breast Tomosynthesis Guided Near Infrared Spectral Tomography, Kelly E. Michaelsen, Venkataramanan Krishnaswamy, Linxi Shi, Srinivasan Vedantham, Steven Poplack, Andrew Karellas, Brian Pogue, Keith Paulsen
Dartmouth Scholarship
Calibration of a three-dimensional multimodal digital breast tomosynthesis (DBT) x-ray and non-fiber based near infrared spectral tomography (NIRST) system is challenging but essential for clinical studies. Phantom imaging results yielded linear contrast recovery of total hemoglobin (HbT) concentration for cylindrical inclusions of 15 mm, 10 mm and 7 mm with a 3.5% decrease in the HbT estimate for each 1 cm increase in inclusion depth. A clinical exam of a patient's breast containing both benign and malignant lesions was successfully imaged, with greater HbT was found in the malignancy relative to the benign abnormality and fibroglandular regions (11 μM vs. …
Characterization Of Low Density Intracranial Lesions Using Dual-Energy Computed Tomography, Jessica L. Nute
Characterization Of Low Density Intracranial Lesions Using Dual-Energy Computed Tomography, Jessica L. Nute
Dissertations & Theses (Open Access)
Calcific and hemorrhagic foci of susceptibility are frequently encountered on routine brain MR studies. Both etiologies cause variations in local magnetic field strength, leading to dark regions on the MR images that cannot be classified. Single-energy CT (SECT) can be used to identify lesions with attenuation over 100 HU as calcific, however lesions with lower attenuation cannot be reliably identified. While calcific lesions are unlikely to cause harm, hemorrhagic lesions carry a risk of subsequent intracranial bleeding; as such, identification of hemorrhage is vital in preventing the inappropriate use of anticoagulant medications in patients with hemorrhagic lesions.
Given there currently …
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 …