Medicine and Health Sciences Commons^™

A Multi-Institutional Meningioma Mri Dataset For Automated Multi-Sequence Image Segmentation, Dominic Labella, Omaditya Khanna, Shan Mcburney-Lin, Ryan Mclean, Pierre Nedelec, Arif Rashid, Nourel Hoda Tahon, Talissa Altes, Ujjwal Baid, Radhika Bhalerao, Yaseen Dhemesh, Scott Floyd, Devon Godfrey, Fathi Hilal, Anastasia Janas, Anahita Kazerooni, Collin Kent, John Kirkpatrick, Florian Kofler, Kevin Leu, Nazanin Maleki, Bjoern Menze, Maxence Pajot, Zachary Reitman, Jeffrey Rudie, Rachit Saluja, Yury Velichko, Chunhao Wang, Pranav Warman, Nico Sollmann, David Diffley, Khanak Nandolia, Daniel Warren, Ali Hussain, John Pascal Fehringer, Yulia Bronstein, Lisa Deptula, Evan Stein, Mahsa Taherzadeh, Eduardo Portela De Oliveira, Aoife Haughey, Marinos Kontzialis, Luca Saba, Benjamin Turner, Melanie Brüßeler, Shehbaz Ansari, Athanasios Gkampenis, David Maximilian Weiss, Aya Mansour, Islam Shawali, Nikolay Yordanov, Joel Stein, Roula Hourani, Mohammed Yahya Moshebah, Ahmed Magdy Abouelatta, Tanvir Rizvi, Klara Willms, Dann Martin, Abdullah Okar, Gennaro D'Anna, Ahmed Taha, Yasaman Sharifi, Shahriar Faghani, Dominic Kite, Marco Pinho, Muhammad Ammar Haider, Michelle Alonso-Basanta, Javier Villanueva-Meyer, Andreas Rauschecker, Ayman Nada, Mariam Aboian, Adam Flanders, Spyridon Bakas, Evan Calabrese

Department of Radiology Faculty Papers

Meningiomas are the most common primary intracranial tumors and can be associated with significant morbidity and mortality. Radiologists, neurosurgeons, neuro-oncologists, and radiation oncologists rely on brain MRI for diagnosis, treatment planning, and longitudinal treatment monitoring. However, automated, objective, and quantitative tools for non-invasive assessment of meningiomas on multi-sequence MR images are not available. Here we present the BraTS Pre-operative Meningioma Dataset, as the largest multi-institutional expert annotated multilabel meningioma multi-sequence MR image dataset to date. This dataset includes 1,141 multi-sequence MR images from six sites, each with four structural MRI sequences (T2-, T2/FLAIR-, pre-contrast T1-, and post-contrast T1-weighted) accompanied by …

Efficient Thorax Disease Classification And Localization Using Dcnn And Chest X-Ray Images, Zeeshan Ahmad, Ahmad Kamran Malik, Nafees Qamar, Saif Ul Islam

Psychology Department Faculty Journal Articles

Thorax disease is a life-threatening disease caused by bacterial infections that occur in the lungs. It could be deadly if not treated at the right time, so early diagnosis of thoracic diseases is vital. The suggested study can assist radiologists in more swiftly diagnosing thorax disorders and in the rapid airport screening of patients with a thorax disease, such as pneumonia. This paper focuses on automatically detecting and localizing thorax disease using chest X-ray images. It provides accurate detection and localization using DenseNet-121 which is foundation of our proposed framework, called Z-Net. The proposed framework utilizes the weighted cross-entropy loss …

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 …

Prediction Of Rapid Early Progression And Survival Risk With Pre-Radiation Mri In Who Grade 4 Glioma Patients, Walia Farzana, Mustafa M. Basree, Norou Diawara, Zeina Shboul, Sagel Dubey, Marie M. Lockheart, Mohamed Hamza, Joshua D. Palmer, Khan Iftekharuddin

Electrical & Computer Engineering Faculty Publications

Rapid early progression (REP) has been defined as increased nodular enhancement at the border of the resection cavity, the appearance of new lesions outside the resection cavity, or increased enhancement of the residual disease after surgery and before radiation. Patients with REP have worse survival compared to patients without REP (non-REP). Therefore, a reliable method for differentiating REP from non-REP is hypothesized to assist in personlized treatment planning. A potential approach is to use the radiomics and fractal texture features extracted from brain tumors to characterize morphological and physiological properties. We propose a random sampling-based ensemble classification model. The proposed …

The Use Of Vesgen For Analysis Of Retinal Vasculature In Pulmonary Arterial Hypertension, Mariana Desiree Dupont

All ETDs from UAB

Pulmonary artery hypertension is a chronic and progressive disease leading to right heart failure and, ultimately, death if untreated. The goal of the studies in this dissertation was to determine if fluorescein angiography (FA), and color fundus angiography (CF) imaging could be used to garner critical information about retinal changes in individuals with pulmonary artery hypertension (PAH). VESsel GENerational Analysis (VESGEN) is a noninvasive computer program that assigns branching generation to large and small vessels. VESGEN was utilized to investigate vascular alterations in FA, and CF imaging investigating disease progression in PAH. This dissertation demonstrated that PAH patients had aberrant …

Extended Functional Connectivity Of Convergent Structural Alterations Among Individuals With Ptsd: A Neuroimaging Meta-Analysis, Brianna S. Pankey, Michael C. Riedel, Isis Cowan, Jessica E. Bartley, Rosario Pintos Lobo, Lauren D. Hill-Bowen, Taylor Sato, Erica D. Musser, Matthew T. Sutherland, Angela R. Laird

Psychology Faculty Publications

Background: Post-traumatic stress disorder (PTSD) is a debilitating disorder defined by the onset of intrusive, avoidant, negative cognitive or affective, and/or hyperarousal symptoms after witnessing or experiencing a traumatic event. Previous voxel-based morphometry studies have provided insight into structural brain alterations associated with PTSD with notable heterogeneity across these studies. Furthermore, how structural alterations may be associated with brain function, as measured by task-free and task-based functional connectivity, remains to be elucidated.

Methods: Using emergent meta-analytic techniques, we sought to first identify a consensus of structural alterations in PTSD using the anatomical likelihood estimation (ALE) approach. Next, we generated functional …

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, …

Triangulation And Finite Element Method For A Variational Problem Inspired By Medical Imaging, Tim Komperda, Enrico Au-Yeung

DePaul Discoveries

We implement the finite element method to solve a variational problem that is inspired by medical imaging. In our application, the domain of the image does not need to be a rectangle and can contain a cavity in the middle. The standard approach to solve a variational problem involves formulating the problem as a partial differential equation. Instead, we solve the variational problem directly, using only techniques available to anyone familiar with vector calculus. As part of the computation, we also explore how triangulation is a useful tool in the process.

Removing The Noise From X-Ray Image Using Image Processing Technology: A Bibliometric Survey And Future Research Directions, Ayushi Kamboj, Mrinal Bachute

Library Philosophy and Practice (e-journal)

The retrieval of superior-quality photographs with a minimal exposure is an interesting subject in radiography. Pre-processing is a key phase in signal and image processing such as healthcare, telecommunications, and satellite, and it focuses on reducing or eliminating the extent of noise in the image. Denoising aids in the recovery of finer data and relevant material. Medical images including ECG, Ultrasound, CT-scan, and X-ray provide incredibly fine data that has to be precise and noise-free in order for the knowledge and aspects of interest to be retained during diagnosis. Various noise reduction technologies for medical images, such as wavelet transform, …

Machine Learning Applications To Neuroimaging For Glioma Detection And Classification: An Artificial Intelligence Augmented Systematic Review, Quinlan D. Buchlak, Nazanin Esmaili, Jean-Christophe Leveque, Christine Bennett, Farrokh Farrokhi, Massimo Piccardi

Medical Papers and Journal Articles

Glioma is the most common primary intraparenchymal tumor of the brain and the 5-year survival rate of high-grade glioma is poor. Magnetic resonance imaging (MRI) is essential for detecting, characterizing and monitoring brain tumors but definitive diagnosis still relies on surgical pathology. Machine learning has been applied to the analysis of MRI data in glioma research and has the potential to change clinical practice and improve patient outcomes. This systematic review synthesizes and analyzes the current state of machine learning applications to glioma MRI data and explores the use of machine learning for systematic review automation. Various datapoints were extracted …

Electrical Identification Of Innate Immune Cells, Rasha Ayman Nasser

Theses

This thesis is concerned with the electrical characterization of the key players of the innate immune cells. Innate immunity is basically the nonspecific immune response that is triggered by any foreign body that attacks the human system. The key players of the innate immune system are mainly dendritic cells and macrophages. Accurately classifying these cell types helps us understand the mechanism of the immune system thereby enabling the development of models to improve new prospects for therapeutics and diagnostics. The characterization described in this thesis is based on extracting the capacitance for each biological cell using I-V curves. The main …

Alcohol Ablation Of Cardiac Tissues Quantified And Evaluated Using Cielab Euclidean Distances, Ashley Rook, Mathews M John, Allison Post, Mehdi Razavi

The Texas Heart Institute Journal

Ethanol solubilizes cell membranes, making it useful for various ablation applications. We examined the effect of time and alcohol type on the extent of ablation, quantified as Euclidean distances between color coordinates. We obtained biopsy punch samples (diameter, 6 mm) of left atrial appendage, atrial, ventricular, and septal tissue from porcine hearts and placed them in transwell plates filled with ethanol or methanol for 10, 20, 30, 40, 50, or 60 min. Control samples were taken for each time point. At each time point, samples were collected, cut transversely, and photographed. With use of a custom MATLAB program, all images …

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

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 …

Prognostic Performance Of Prospective Versus Retrospective Electrocardiographic Gating In Coronary Computed Tomographic Angiography, Pradnya Velankar, Kongkiat Chaikriangkrai, Ninad Dewal, Sayf Khaleel Bala, Belqis Elferjani, Sama Alchalabi, Su Min Chang

The Texas Heart Institute Journal

Coronary computed tomographic angiography (CCTA) with prospective electrocardiographic gating reduces radiation exposure, but its prognostic power for predicting cardiovascular risk in patients with suspected CAD has not been fully validated. To determine whether prospective gating performs as well as retrospective gating in this population, we compared these scan modes in patients undergoing 64-slice CCTA.

From January 2009 through September 2011, 1,407 patients underwent CCTA; of these, 915 (mean age, 57.8 ± 13.5 yr; 54% male) had suspected coronary artery disease at the time of CCTA and were included in the study. Prospective gating was used in 195 (21%) and retrospective …

Methods For The Investigation Of Microvascular Control Of Oxygen Distribution, Richard Sove

Electronic Thesis and Dissertation Repository

The purpose of this thesis was to develop tools for studying oxygen-dependent regulation of red blood cell (RBC) flow distribution in the microcirculation. At the microvascular level, arterioles dictate the distribution of oxygen (O₂) carrying RBCs to downstream capillaries, a process which needs to be tightly regulated and coupled to O₂ off loading from capillaries to the tissue. To investigate potential regulatory mechanisms, an O₂ exchange platform was developed to manipulate the RBC hemoglobin O₂ saturation (SO₂) at the muscle surface while limiting the changes in SO₂ to only a single capillary …

Development Of A Pulmonary Imaging Biomarker Pipeline For Phenotyping Of Chronic Lung Disease, Fumin Guo, Dante Capaldi, Miranda Kirby, Khadija Sheikh, Sarah Svenningsen, David G Mccormack, Aaron Fenster, Grace Parraga

Medical Biophysics Publications

We designed and generated pulmonary imaging biomarker pipelines to facilitate high-throughput research and point-of-care use in patients with chronic lung disease. Image processing modules and algorithm pipelines were embedded within a graphical user interface (based on the .NET framework) for pulmonary magnetic resonance imaging (MRI) and x-ray computed-tomography (CT) datasets. The software pipelines were generated using C++ and included: (1) inhaled

Algorithm Development For Intrafraction Radiotherapy Beam Edge Verification From Cherenkov Imaging., Clare Snyder, Brian W. Pogue, Michael Jermyn, Irwin Tendler

Dartmouth Scholarship

Imaging of Cherenkov light emission from patient tissue during fractionated radiotherapy has been shown to be a possible way to visualize beam delivery in real time. If this tool is advanced as a delivery verification methodology, then a sequence of image processing steps must be established to maximize accurate recovery of beam edges. This was analyzed and developed here, focusing on the noise characteristics and representative images from both phantoms and patients undergoing whole breast radiotherapy. The processing included temporally integrating video data into a single, composite summary image at each control point. Each image stack was also median filtered …

Accurate Cytogenetic Biodosimetry Through Automated Dicentric Chromosome Curation And Metaphase Cell Selection, Jin Liu, Yanxin Li, Ruth Wilkins, Canadian Nuclear Laboratories, Joan H. Knoll, Peter Rogan

Biochemistry Publications

Accurate digital image analysis of abnormal microscopic structures relies on high quality images and on minimizing the rates of false positive (FP) and negative objects in images. Cytogenetic biodosimetry detects dicentric chromosomes (DCs) that arise from exposure to ionizing radiation, and determines radiation dose received based on DC frequency. Improvements in automated DC recognition increase the accuracy of dose estimates by reclassifying FP DCs as monocentric chromosomes or chromosome fragments. We also present image segmentation methods to rank high quality digital metaphase images and eliminate suboptimal metaphase cells. A set of chromosome morphology segmentation methods selectively filtered out FP DCs …

Mammographic Density Assessed On Paired Raw And Processed Digital Images And On Paired Screen-Film And Digital Images Across Three Mammography Systems, Anya Burton, Graham Byrnes, Jennifer Stone, Rulla M. Tamimi, John Heine, Celine Vachon, Vahit Ozmen, Ana Pereira, Maria Luisa Garmendia, Christopher Scott, John H. Hipwell, Caroline Dickens, Joachim Schüz, Mustafa Erkin Aribal, Kimberly Bertrand, Ava Kwong, Graham G. Giles, John Hopper, Beatriz Pérez Gómez, Marina Pollán, Soo-Hwang Teo, Shivaani Mariapun, Nur Aishah Mohd Taib, Martín Lajous, Ruy Lopez-Riduara, Megan Rice, Isabelle Romieu, Anath Arzee Flugelman, Giske Ursin, Samera Qureshi, Huiyan Ma, Eunjung Lee, Reza Sirous, Mehri Sirous, Jong Won Lee, Jisun Kim, Dorria Salem, Rasha Kamal, Mikael Hartman, Hui Miao, Kee-Seng Chia, Chisato Nagata, Sudhir Vinayak, Rose Ndumia, Carla H. Van Gils, Johanna O. P. Wanders, Beata Peplonska, Agnieszka Bukowska, Steve Allen, Sarah Vinnicombe, Sue Moss, Anna M. Chiarelli, Linda Linton, Gertraud Maskarinec, Martin J. Yaffe, Norman F. Boyd, Isabel Dos-Santos-Silva, Valerie A. Mccormack

Imaging & Diagnostic Radiology, East Africa

Background: Inter-women and intra-women comparisons of mammographic density (MD) are needed in research, clinical and screening applications; however, MD measurements are influenced by mammography modality (screen film/ digital) and digital image format (raw/processed). We aimed to examine differences in MD assessed on these image types.

Methods: We obtained 1294 pairs of images saved in both raw and processed formats from Hologic and General Electric (GE) direct digital systems and a Fuji computed radiography (CR) system, and 128 screen-film and processed CR-digital pairs from consecutive screening rounds. Four readers performed Cumulus-based MD measurements (n = 3441), with each image pair read …

Framework For Hyperspectral Image Processing And Quantification For Cancer Detection During Animal Tumor Surgery, Guolan Lu, Dongsheng Wang, Xulei Qin, Luma Halig, Susan Muller, Hongzheng Zhang, Amy Chen, Brian W. Pogue, Zhuo G. Chen

Dartmouth Scholarship

Hyperspectral imaging (HSI) is an imaging modality that holds strong potential for rapid cancer detection during image-guided surgery. But the data from HSI often needs to be processed appropriately in order to extract the maximum useful information that differentiates cancer from normal tissue. We proposed a framework for hyperspectral image processing and quantification, which includes a set of steps including image preprocessing, glare removal, feature extraction, and ultimately image classification. The framework has been tested on images from mice with head and neck cancer, using spectra from 450- to 900-nm wavelength. The image analysis computed Fourier coefficients, normalized reflectance, mean, …

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

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 …

Contourlet Textual Features: Improving The Diagnosis Of Solitary Pulmonary Nodules In Two Dimensional Ct Images, Jingjing Wang, Tao Sun, Ni Gao, Desmond D. Menon, Yanxia Luo, Qi Gao, Xia Li, Wei Wang, Huiping Zhu, Pingxin Lv, Zhigang Liang, Lixin Tao, Xiangtong Liu, Xiuhua Guo

Research outputs 2014 to 2021

Materials and Methods: A total of 6,299 CT images were acquired from 336 patients, with 1,454 benign pulmonary nodule images from 84 patients (50 male, 34 female) and 4,845 malignant from 252 patients (150 male, 102 female). Further to this, nineteen patient information categories, which included seven demographic parameters and twelve morphological features, were also collected. A contourlet was used to extract fourteen types of textural features. These were then used to establish three support vector machine models. One comprised a database constructed of nineteen collected patient information categories, another included contourlet textural features and the third one contained both …

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 …

Microwave Imaging For Neoadjuvant Chemotherapy Monitoring: Initial Clinical Experience, Paul M. Meaney, Peter A. Kaufman, Lori S. Muffly, Michael Click, Stephen P. Poplack, Wendy A. Wells, Gary N. Schwartz, Roberta M. Di Florio-Alexander, Tor Tosteson, Zhongze Li, Shireen D. Geimer, Margaret W. Fanning, Tian Zhou, Neil R. Epstein, Keith D. Paulsen

Dartmouth Scholarship

Introduction:

Microwave tomography recovers images of tissue dielectric properties, which appear to be specific for breast cancer, with low-cost technology that does not present an exposure risk, suggesting the modality may be a good candidate for monitoring neoadjuvant chemotherapy.

Methods:

Eight patients undergoing neoadjuvant chemotherapy for locally advanced breast cancer were imaged longitudinally five to eight times during the course of treatment. At the start of therapy, regions of interest (ROIs) were identified from contrast-enhanced magnetic resonance imaging studies. During subsequent microwave examinations, subjects were positioned with their breasts pendant in a coupling fluid and surrounded by an immersed antenna …

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 …

Impact Of Varied Low Resolution Phantoms On Intensity Modulated Proton Therapy Dose Distributions, Aarohi Shyam Padhye

Theses Digitization Project

The primary purpose of this thesis is to discuss the usefulness of image segmentation techniques in creating accurate proton dose distribution plans. The calculation of the proton dose distribution has to take into account the material (tissue, bone, brain) in the treatment area of the patients body.

Mcnamara 20120831fri-20120904tue Cosmic Ray Particles By Ccd Imaging, George Mcnamara

George McNamara

McNamara 20120831Fri-20120904Tue Cosmic Ray Particles by CCD imaging.zip contains image files in support of a Microscopy Today article - please see

http://www.microscopy-today.com/

Cosmic Ray Particles Images With Orca-Ii Erg, George Mcnamara

George McNamara

Cosmic ray particles image series acquired using a Hamamatsu ORCA-II ERG scientific grade CCD camera, cooled to -60 C. Each image is a consecutive 600 second (10 minute) exposure time with no light to the camera.

While processing the data, I discoverd that the background changed around planes 25 and 227 (see Excel file and jpeg screenshots), so I also processed only planes 025-227 (203 planes total, 2030 minutes, 33.83 hours). the CCD industry "rule of thumb" for a "typical" CCD sensor (i.e. 1/3" CCD) is that one cosmic ray particle strikes a sensor approximately every 30 seconds (assuming not …