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Full-Text Articles in Engineering
Experimental And Computational Tools For Single Cell Analysis In Cancer Diagnostics, Manibarathi Vaithiyanathan
Experimental And Computational Tools For Single Cell Analysis In Cancer Diagnostics, Manibarathi Vaithiyanathan
LSU Doctoral Dissertations
Substantial evidence shows that cellular heterogeneity commonly exists within an isogenic or clonal population. Whether in isolation or caused through a combination of the above events, cellular heterogeneity can dramatically influence cellular decision making and cell fate, however, this can be masked by the average response from a population. One approach to solve this issue is to analyze a population at the individual cell level. The goal of this work is to develop high-throughput experimental and computational platforms to screen and quantify single cancer cells for specific intracellular enzyme activities. An interdisciplinary approach was taken to 1) better understand the …
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 …
Cervical Cancer Histology Image Feature Extraction And Classification, Peng Guo
Cervical Cancer Histology Image Feature Extraction And Classification, Peng Guo
Masters Theses
"Cervical cancer, the second most common cancer affecting women worldwide and the most common in developing countries can be cured if detected early and treated. Expert pathologists routinely visually examine histology slides for cervix tissue abnormality assessment. In previous research, an automated, localized, fusion-based approach was investigated for classifying squamous epithelium into Normal, CIN1, CIN2, and CIN3 grades of cervical intraepithelial neoplasia (CIN) based on image analysis of 62 digitized histology images obtained through the National Library of Medicine. In this research, CIN grade assessments from two pathologists are analyzed and are used to facilitate atypical cell concentration feature development …