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Articles 1 - 14 of 14
Full-Text Articles in Engineering
Sharprazor: Automatic Removal Of Hair And Ruler Marks From Dermoscopy Images, Reda Kasmi, Jason Hagerty, Reagan Harris Young, Norsang Lama, Januka Nepal, Jessica Miinch, William V. Stoecker, R. Joe Stanley
Sharprazor: Automatic Removal Of Hair And Ruler Marks From Dermoscopy Images, Reda Kasmi, Jason Hagerty, Reagan Harris Young, Norsang Lama, Januka Nepal, Jessica Miinch, William V. Stoecker, R. Joe Stanley
Mechanical and Aerospace Engineering Faculty Research & Creative Works
Background: The removal of hair and ruler marks is critical in handcrafted image analysis of dermoscopic skin lesions. No other dermoscopic artifacts cause more problems in segmentation and structure detection. Purpose: The aim of the work is to detect both white and black hair, artifacts and finally inpaint correctly the image. Method: We introduce a new algorithm: SharpRazor, to detect hair and ruler marks and remove them from the image. Our multiple-filter approach detects hairs of varying widths within varying backgrounds, while avoiding detection of vessels and bubbles. The proposed algorithm utilizes grayscale plane modification, hair enhancement, segmentation using tri-directional …
Tooth Position Determination By Automatic Cutting And Marking Of Dental Panoramic X-Ray Film In Medical Image Processing, Yen-Cheng Huang, Chiung-An Chen, Tsung-Yi Chen, He-Sheng Chou, Wei-Chi Lin, Tzu-Chien Li, Jia-Jun Yuan, Szu-Yin Lin, Chun-Wei Li, Shih-Lun Chen, Yi-Cheng Mao, Patricia Angela R. Abu, Wei-Yuan Chiang, Wen-Shen Lo
Tooth Position Determination By Automatic Cutting And Marking Of Dental Panoramic X-Ray Film In Medical Image Processing, Yen-Cheng Huang, Chiung-An Chen, Tsung-Yi Chen, He-Sheng Chou, Wei-Chi Lin, Tzu-Chien Li, Jia-Jun Yuan, Szu-Yin Lin, Chun-Wei Li, Shih-Lun Chen, Yi-Cheng Mao, Patricia Angela R. Abu, Wei-Yuan Chiang, Wen-Shen Lo
Department of Information Systems & Computer Science Faculty Publications
This paper presents a novel method for automatic segmentation of dental X-ray images into single tooth sections and for placing every segmented tooth onto a precise corresponding position table. Moreover, the proposed method automatically determines the tooth’s position in a panoramic X-ray film. The image-processing step incorporates a variety of image-enhancement techniques, including sharpening, histogram equalization, and flat-field correction. Moreover, image processing was implemented iteratively to achieve higher pixel value contrast between the teeth and cavity. The next image-enhancement step is aimed at detecting the teeth cavity and involves determining the segment and points separating the upper and lower jaw, …
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 …
Seeing Eye To Eye: A Machine Learning Approach To Automated Saccade Analysis, Maigh Attre
Seeing Eye To Eye: A Machine Learning Approach To Automated Saccade Analysis, Maigh Attre
Honors Scholar Theses
Abnormal ocular motility is a common manifestation of many underlying pathologies particularly those that are neurological. Dynamics of saccades, when the eye rapidly changes its point of fixation, have been characterized for many neurological disorders including concussions, traumatic brain injuries (TBI), and Parkinson’s disease. However, widespread saccade analysis for diagnostic and research purposes requires the recognition of certain eye movement parameters. Key information such as velocity and duration must be determined from data based on a wide set of patients’ characteristics that may range in eye shapes and iris, hair and skin pigmentation [36]. Previous work on saccade analysis has …
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 …
Spatial Frequency Analysis Of Anisotropic Drug Transport In Tumor Samples, Stewart Russell, Kimberley S. Samkoe, Jason R. Gunn, P Jack Hoopes, Thienan A. Nguyen, Milo J. Russell, Robert R. Alfano, Brian W. Pogue
Spatial Frequency Analysis Of Anisotropic Drug Transport In Tumor Samples, Stewart Russell, Kimberley S. Samkoe, Jason R. Gunn, P Jack Hoopes, Thienan A. Nguyen, Milo J. Russell, Robert R. Alfano, Brian W. Pogue
Dartmouth Scholarship
Directional Fourier spatial frequency analysis was used on standard histological sections to identify salient directional bias in the spatial frequencies of stromal and epithelial patterns within tumor tissue. This directional bias is shown to be correlated to the pathway of reduced fluorescent tracer transport. Optical images of tumor specimens contain a complex distribution of randomly oriented aperiodic features used for neoplastic grading that varies with tumor type, size, and morphology. The internal organization of these patterns in frequency space is shown to provide a precise fingerprint of the extracellular matrix complexity, which is well known to be related to the …
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 …
Dual-Tracer Background Subtraction Approach For Fluorescent Molecular Tomography, Kenneth M. Tichauer, Robert W. Holt, Fadi El-Ghussein, Scott C. Davis, Kimberly S. Samkoe, Jason R. Gunn, Frederic Leblond, Brian W. Pogue
Dual-Tracer Background Subtraction Approach For Fluorescent Molecular Tomography, Kenneth M. Tichauer, Robert W. Holt, Fadi El-Ghussein, Scott C. Davis, Kimberly S. Samkoe, Jason R. Gunn, Frederic Leblond, Brian W. Pogue
Dartmouth Scholarship
Diffuse fluorescence tomography requires high contrast-to-background ratios to accurately reconstruct inclusions of interest. This is a problem when imaging the uptake of fluorescently labeled molecularly targeted tracers in tissue, which can result in high levels of heterogeneously distributed background uptake. We present a dual-tracer background subtraction approach, wherein signal from the uptake of an untargeted tracer is subtracted from targeted tracer signal prior to image reconstruction, resulting in maps of targeted tracer binding. The approach is demonstrated in simulations, a phantom study, and in a mouse glioma imaging study, demonstrating substantial improvement over conventional and homogenous background subtraction image reconstruction …
Improved Tumor Contrast Achieved By Single Time Point Dual-Reporter Fluorescence Imaging, Kenneth M. Tichauer, Kimberley S. Samkoe, Kristian J. Sexton, Jason R. Gunn, Tayyaba Hasan, Brian W. Pogue
Improved Tumor Contrast Achieved By Single Time Point Dual-Reporter Fluorescence Imaging, Kenneth M. Tichauer, Kimberley S. Samkoe, Kristian J. Sexton, Jason R. Gunn, Tayyaba Hasan, Brian W. Pogue
Dartmouth Scholarship
In this study, we demonstrate a method to quantify biomarker expression that uses an exogenous dual-reporter imaging approach to improve tumor signal detection. The uptake of two fluorophores, one nonspecific and one targeted to the epidermal growth factor receptor (EGFR), were imaged at 1 h in three types of xenograft tumors spanning a range of EGFR expression levels (n = 6 in each group). Using this dual-reporter imaging methodology, tumor contrast-to-noise ratio was amplified by >6 times at 1 h postinjection and >2 times at 24 h. Furthermore, by as early as 20 min postinjection, the dual-reporter imaging signal …
Comparing Implementations Of Magnetic-Resonance-Guided Fluorescence Molecular Tomography For Diagnostic Classification Of Brain Tumors, Scott C. Davis, Kimberley S. Samkoe, Julia A. O’Hara, Summer L. Gibbs-Strauss, Keith D. Paulsen, Brian W. Pogue
Comparing Implementations Of Magnetic-Resonance-Guided Fluorescence Molecular Tomography For Diagnostic Classification Of Brain Tumors, Scott C. Davis, Kimberley S. Samkoe, Julia A. O’Hara, Summer L. Gibbs-Strauss, Keith D. Paulsen, Brian W. Pogue
Dartmouth Scholarship
Fluorescence molecular tomography (FMT) systems coupled to conventional imaging modalities such as magnetic resonance imaging (MRI) and computed tomography provide unique opportunities to combine data sets and improve image quality and content. Yet, the ideal approach to combine these complementary data is still not obvious. This preclinical study compares several methods for incorporating MRI spatial prior information into FMT imaging algorithms in the context of in vivo tissue diagnosis. Populations of mice inoculated with brain tumors that expressed either high or low levels of epidermal growth factor receptor (EGFR) were imaged using an EGF-bound near-infrared dye and a spectrometer-based MRI-FMT …
Automated Identification Of Tumor Microscopic Morphology Based On Macroscopically Measured Scatter Signatures, Pilar Beatriz Garcia-Allende, Venkataramanan Krishnaswamy, P Jack Hoopes, Kimberley S. Samkoe, Olga M. Conde, Brian W. Pogue
Automated Identification Of Tumor Microscopic Morphology Based On Macroscopically Measured Scatter Signatures, Pilar Beatriz Garcia-Allende, Venkataramanan Krishnaswamy, P Jack Hoopes, Kimberley S. Samkoe, Olga M. Conde, Brian W. Pogue
Dartmouth Scholarship
An automated algorithm and methodology is presented to identify tumor-tissue morphologies based on broadband scatter data measured by raster scan imaging of the samples. A quasi-confocal reflectance imaging system was used to directly measure the tissue scatter reflectance in situ, and the spectrum was used to identify the scattering power, amplitude, and total wavelength-integrated intensity. Pancreatic tumor and normal samples were characterized using the instrument, and subtle changes in the scatter signal were encountered within regions of each sample. Discrimination between normal versus tumor tissue was readily performed using a K-nearest neighbor classifier algorithm. A similar approach worked …
Methodology Development For Three-Dimensional Mr-Guided Near Infrared Spectroscopy Of Breast Tumors, Colin M. Carpenter, Subhadra Srinivasan, Brian W. Pogue, Keith D. Paulsen
Methodology Development For Three-Dimensional Mr-Guided Near Infrared Spectroscopy Of Breast Tumors, Colin M. Carpenter, Subhadra Srinivasan, Brian W. Pogue, Keith D. Paulsen
Dartmouth Scholarship
Combined Magnetic Resonance (MR) and Near Infrared Spectroscopy (NIRS) has been proposed as a unique method to quantify hemodynamics, water content, and cellular size and packing density of breast tumors, as these tissue constituents can be quantified with increased resolution and overlaid on the structural features identified by the MR. However, the choices in how to reconstruct and visualize this information can have a dramatic impact on the feasibility of implementing this modality in the clinic. This is especially true in 3 dimensions, as there is often limited optical sampling of the breast tissue, and methods need to accurately reflect …
Imaging Breast Adipose And Fibroglandular Tissue Molecular Signatures By Using Hybrid Mri-Guided Near-Infrared Spectral Tomography, Ben Brooksby, Brian W. Pogue, Shudong Jiang, Hamid Dehghani, Subhadra Srinivasan, Christine Kogel, Tor D. Tosteson, John Weaver, Steven P. Poplack, Keith D. Paulsen
Imaging Breast Adipose And Fibroglandular Tissue Molecular Signatures By Using Hybrid Mri-Guided Near-Infrared Spectral Tomography, Ben Brooksby, Brian W. Pogue, Shudong Jiang, Hamid Dehghani, Subhadra Srinivasan, Christine Kogel, Tor D. Tosteson, John Weaver, Steven P. Poplack, Keith D. Paulsen
Dartmouth Scholarship
Magnetic resonance (MR)-guided near-infrared spectral tomography was developed and used to image adipose and fibroglandular breast tissue of 11 normal female subjects, recruited under an institutional review board-approved protocol. Images of hemoglobin, oxygen saturation, water fraction, and subcellular scattering were reconstructed and show that fibroglandular fractions of both blood and water are higher than in adipose tissue. Variation in adipose and fibroglandular tissue composition between individuals was not significantly different across the scattered and dense breast categories. Combined MR and near-infrared tomography provides fundamental molecular information about these tissue types with resolution governed by MR T1 images.
Contrast Enhancement Of Medical Images Using Multiscale Edge Representation, Jian Lu, Dennis M. Healy Jr., John B. Weaver
Contrast Enhancement Of Medical Images Using Multiscale Edge Representation, Jian Lu, Dennis M. Healy Jr., John B. Weaver
Dartmouth Scholarship
Experience suggests the existence of a connection between the contrast of a gray-scale image and the gradient magnitude of intensity edges in the neighborhood where the contrast is measured. This observation motivates the development of edge-based contrast enhancement techniques. We present a simple and effective method for image contrast enhancement based on the multiscale edge representation of images. The contrast of an image can be enhanced simply by stretching or upscaling the multiscale gradient maxima of the image. This method offers flexibility to selectively enhance features of different sizes and ability to control noise magnification. We present some experimental results …