Dissertations / Theses: 'T1-weighted'

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Nazarpoor, Mahmood. "Flow measurement with T1-weighted MRI techniques." Thesis, University of Nottingham, 2004. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.403291.

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Teo, Arnold, and Daniel Tsada Yosief. "Influence of T1 and T2 weighted MRI images on automated diagnosis of Alzheimer's disease." Thesis, KTH, Skolan för elektroteknik och datavetenskap (EECS), 2021. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-301735.

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Alzheimer’s Disease (AD) is the most common form of dementia and according to the World Health Organization it contributes to 60-70% of the approximately 50 million total worldwide dementia cases. While AD is easy to diagnose from a patient’s symptoms alone, due to AD atrophying brain tissue, a Magnetic Resonance Imaging (MRI) scan can strengthen the diagnosis. Computer-Aided Diagnosis (CAD) refers to the use of machine learning methods for assistance with diagnosis. The main purpose of CAD is to assist, primarily radiologists, with a second opinion in a diagnosis and reduce the amount of false diagnosis. In some cases CAD can also aid in accurate early detection of AD and therefore allowing the patient the possibility to deploy preventive measures. This study investigates the influence of T1 or T2 weighted MRI images on the automated diagnosis of AD using the VGG-16 Deep Neural Network (DNN). Previous studies have researched classification accuracy of different algorithms or artificial neural networks on MRI images for automated diagnosis of AD. However, the choice of MRI weighting varies in these studies and reasoning for choosing said weightings are not explicitly given. This study thus aims to answer whether choice of MRI weighting can affect the classification accuracy of AD using automated diagnosis, and if so, how significantly? Two of the most common MRI weightings were chosen for the study, T1 and T2. 149 images of each weighting were manually collected from the ADNI database and used for training and validation of the VGG-16 DNN. The resulting difference in classification accuracy was significant, with T1 having an average accuracy of 59.41% and T2 an average of 74.71%. The obtained conclusion was that the selection of T1 or T2 weighted images could have a significant influence on the classification accuracy of a chosen CAD method. More research needs to be done however to see if the results of this study are repeated for other algorithms and/ or for larger datasets. Alzheimers sjukdom (AD) är den vanligaste formen av demens och enligt Världshälsoorganisationen bidrar den till 60-70% av de approximativt 50 miljoner totala globala demensfallen. Medan AD är lätt att diagnostisera enbart utifrån en patients symptom, på grund av att AD atrofierar hjärnvävnad, kan en Magnetisk Resonanstomografisk (MR) undersökning stärka diagnosen. Datorassisterad diagnostisering (CAD) avser användningen av maskininlärningsmetoder för hjälp med diagnostisering. Huvudsyftet med CAD är att hjälpa, främst radiologer, med en andra åsikt vid en diagnos och minska mängden falska diagnoser. I vissa fall kan CAD också hjälpa med tidig upptäckt av AD och därmed ge patienten möjlighet att vidta förebyggande åtgärder. Denna studie undersöker påverkan av T1- eller T2-viktade MR-bilder på automatiska diagnostiseringen av AD med hjälp av Djupa Neurala Nätverket (DNN) VGG-16. Tidigare studier har undersökt klassificeringsnoggrannheten för olika algoritmer eller artificiella neurala nätverk på MR-bilder för automatisk diagnostisering av AD. Valet av MR-viktning varierar i dessa studier och resonemang för valet av viktning ges inte uttryckligen. Denna studie syftar således till att svara på om valet av MR-viktning kan påverka klassificeringsnoggrannheten på AD vid användning av automatiserad diagnos, och i så fall hur betydande? Två av de vanligaste MR-vikterna valdes för studien, T1 och T2. 149 bilder av vardera viktning samlades manuellt från ADNI-databasen och användes för träning och validering av VGG-16 DNN. Den resulterande skillnaden i klassificeringsnoggrannheten var betydlig, där T1 hade en genomsnittlig noggrannhet på 59.41% och T2 ett genomsnitt på 74.71%. Den erhållna slutsatsen var att valet av T1- eller T2-viktade bilder kan ha ett betydande inflytande på klassificeringsnoggrannheten för en vald CAD-metod. Mer forskning behöver dock göras för att se om resultaten av denna studie upprepas för andra algoritmer och/ eller för större datamängder.

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Petrek, Tomáš. "Zpracování difuzně vážených obrazů." Master's thesis, Vysoké učení technické v Brně. Fakulta elektrotechniky a komunikačních technologií, 2015. http://www.nusl.cz/ntk/nusl-220421.

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Diploma thesis explores the possibility of using diffusion-weighted images in medicine. The paper is a brief physical principle of operation of the magnetic resonance as a tool for non-destructive imaging of the internal structure of substances, the principle of the display contrast as T1, T2 and diffusion weighted images, the course of the sequence for obtaining images with different contrast. Medicine is faced with the problem of classification of pathological tissue in the brain. Contrast diffusion-weighted images does not visually determine the shape of pathological tissue in the form of a tumor or edema. With the T1 and T2 weighted images were calculated mask corresponding tumor and edema, that have been applied to the diffusion-weighted images. Images of the tumor and edema have been subjected diffusivity measurements and statistical evaluation for the purpose of classifying the type of tumor. Investigations were seven findings glioma and metastatic five awards. The research was focused on classifying pathological tissue.

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Brand, Jonathan F., Lars R. Furenlid, Maria I. Altbach, et al. "Task-based optimization of flip angle for fibrosis detection in T1-weighted MRI of liver." SPIE-SOC PHOTO-OPTICAL INSTRUMENTATION ENGINEERS, 2016. http://hdl.handle.net/10150/622346.

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Chronic liver disease is a worldwide health problem, and hepatic fibrosis (HF) is one of the hallmarks of the disease. The current reference standard for diagnosing HF is biopsy followed by pathologist examination; however, this is limited by sampling error and carries a risk of complications. Pathology diagnosis of HF is based on textural change in the liver as a lobular collagen network that develops within portal triads. The scale of collagen lobules is characteristically in the order of 1 to 5 mm, which approximates the resolution limit of in vivo gadolinium-enhanced magnetic resonance imaging in the delayed phase. We use MRI of formalin-fixed human ex vivo liver samples as phantoms that mimic the textural contrast of in vivo Gd-MRI. We have developed a local texture analysis that is applied to phantom images, and the results are used to train model observers to detect HF. The performance of the observer is assessed with the area-under-the-receiver-operator-characteristic curve (AUROC) as the figure-of-merit. To optimize the MRI pulse sequence, phantoms were scanned with multiple times at a range of flip angles. The flip angle that was associated with the highest AUROC was chosen as optimal for the task of detecting HF. (C) The Authors. Published by SPIE under a Creative Commons Attribution 3.0 Unported License. Distribution or reproduction of this work in whole or in part requires full attribution of the original publication, including its DOI.

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Shokouhimehr, Mohammadreza. "Prussian Blue Nanoparticles and its Analogues as New-Generation T1-Weighted MRI Contrast Agents for Cellular Imaging." Kent State University / OhioLINK, 2010. http://rave.ohiolink.edu/etdc/view?acc_num=kent1275612500.

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Kasahara, Seiko. "Hyperintense dentate nucleus on unenhanced T1-weighted MR images is associated with a history of brain irradiation." Kyoto University, 2011. http://hdl.handle.net/2433/151912.

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Chien, Claudia [Verfasser]. "Spinal cord atrophy measured from cerebral T1-weighted MRI: applications in clinical investigations of neuromyelitis optica spectrum disorders / Claudia Chien." Berlin : Medizinische Fakultät Charité - Universitätsmedizin Berlin, 2021. http://d-nb.info/1228860939/34.

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Kašák, Pavel. "Měření difúsního koeficientu membrán dialyzačních filtrů." Master's thesis, Vysoké učení technické v Brně. Fakulta elektrotechniky a komunikačních technologií, 2013. http://www.nusl.cz/ntk/nusl-220057.

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This thesis focuses on the measurement of diffusion coefficient of dialysis membrane. The first part describes possibilities of membrane modelling. Basic models, which allow us to determine the basic characteristics of dialysis membranes like permeability and diffusion coefficient, are described. Next chapter deals with basic types and properties of membranes. The main part focuses on making the experimental installation, which is used to simulate permeance of contrast agent, used in DCE-MRI, through dialysis membrane. The last theoretical chapter describes calculations used to estimate diffusion coefficient. Practical part of this thesis uses a designed experimental installation for estimation of diffusion coefficient for two contrast agents Gadovist® and Multihance®.

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Ohno, Tsuyoshi. "Usefulness of breath-hold inversion recovery-prepared T1-weighted two-dimensional gradient echo sequence for detection of hepatocellular carcinoma in Gd-EOB-DTPA-enhanced MR imaging." Kyoto University, 2017. http://hdl.handle.net/2433/218009.

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Minsterová, Alžběta. "Srovnání preklinických DCE-MRI perfusních technik." Master's thesis, Vysoké učení technické v Brně. Fakulta elektrotechniky a komunikačních technologií, 2016. http://www.nusl.cz/ntk/nusl-242190.

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This diploma thesis deals with DCE-MRI (Dynamic Contrast-Enhanced Magnetic Resonance Imaging) thus one of the contrast magnetic resonance imaging methods. It describes the principle of conventional continuous DCE-MRI, which uses single bolus of contrast agent and further it focuses on the dual bolus contrast agent techniques, especially the interleaved acquisition. The graphical interface for processing Bruker systems data was made. Synthetic data were used to evaluate the influence of this method on the perfusion parameters estimation. Simulations proved that the further the second bolus is from the first one, the better results are. Simulations of acquisition interruption did not lead to the clear result. However, two statements, which are expected to lead to as good estimation of perfusion parameters as possible, were formulated

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Bains, Lauren Jean. "Assessing the effects of water exchange on quantitative dynamic contrast enhanced MRI." Thesis, University of Manchester, 2011. https://www.research.manchester.ac.uk/portal/en/theses/assessing-the-effects-of-water-exchange-on-quantitative-dynamic-contrast-enhanced-mri(e04de84b-45e2-429f-9fc4-4a76b8f018ec).html.

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Applying mathematical models to dynamic contrast enhanced MRI (DCE MRI) data to perform quantitative tracer kinetic analysis enables the estimation of tissue characteristics such as vascular permeability and the fractional volume of plasma in a tissue. However, it is unclear to what extent modeling assumptions, particularly regarding water exchange between tissue compartments, impacts parameter estimates derived from clinical DCE MRI data. In this work, a new model is developed which includes water exchange effects, termed the water exchange modified two compartment exchange model (WX-2CXM). Two boundaries of this model (the fast and no exchange limits) were used to analyse a clinical DCE MRI bladder cancer dataset. Comparisons with DCE CT, which is not affected by water exchange, suggested that water exchange may have affected estimates of vp, the fractional volume of plasma. Further investigation and simulations led to the development of a DCE MRI protocol which was sensitised to water exchange, in order to further evaluate the water exchange effects found in the bladder cancer dataset. This protocol was tested by imaging the parotid glands in eight healthy volunteers, and confirmed evidence of water exchange effects on vp, as well as flow Fp and the fractional volume of extravascular extracellular space ve. This protocol also enabled preliminary estimates of the water residence times in parotid tissue, however, these estimates had a large variability and require further validation. The work presented in this thesis suggests that, although water exchange effects do not have a large effect on clinical data, the effect is measurable, and may lead to the ability to estimate of tissue water residence times. Results do not support a change in the current practise of neglecting water exchange effects in clinical DCEMRI acquisitions.

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Waghorn, Benjamin J. "Monitoring dynamic calcium homeostasis alterations by T₁-weighted and T₁-mapping cardiac manganese enhanced MRI (MEMRI) in a murine myocardial infarction model." Thesis, Atlanta, Ga. : Georgia Institute of Technology, 2009. http://hdl.handle.net/1853/28237.

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Thesis (M. S.)--Mechanical Engineering, Georgia Institute of Technology, 2009. Committee Chair: Hu, Tom; Committee Co-Chair: Rahnema, Farzad; Committee Member: Wang, Chris; Committee Member: Yanasak, Nathan.

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Chen, Kuan-Han, and 陳寬翰. "Vertebrae Segmentation on T1-Weighted MRI Spine Image." Thesis, 2019. http://ndltd.ncl.edu.tw/cgi-bin/gs32/gsweb.cgi/login?o=dnclcdr&s=id=%22107NCHU5396039%22.&searchmode=basic.

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碩士 國立中興大學 資訊管理學系所 107 The spine is the foundation of health, and it is also the source of all diseases. If this important tool that bears the weight of the human body has diseases, various diseases of the body will come one after another, and if it is serious, it will affect the normal operation of the main nervous system, causing the pain of tissues such as muscles, ligaments, bonesand blood vessels. Magnetic resonance imaging (MRI) is an imaging technique that uses signals generated by changes in the external magnetic field of hydrogen atoms in water molecules in the human body and then calculates the images obtained by computer. MRI technology is widely used in the diagnosis of motion-related injuries. It provides clear images of bones and soft tissues near and around bones and bones, including ligaments and muscles, and is therefore extremely meticulous in terms of spine and joint problems. This study proposes a cutting algorithm for MRI vertebral images and develops an automated system that roughly cuts out the correct spinal region, which can assist doctors in their diagnosis and treatment. This method adjusted the image size first, and the contrast is adjusted and the noise is removed. Then the Otsu algorithm is used to find the most suitable threshold and then make binarization, then the cutting is performed by Opening-Operation and Closing-Operation so that the image of the spine becomes smoother and more completed. Then, the Eight Connected-Component are used to determine whether the shape is the spine, and then use distinctive feature such as major axis length, perimeter, area to filter the correct spine section, and finally fill the gap, and then the image cutting of the entire spine is completed. After completing the image cutting of the spine, use four index such as similarity, sensitivity, specificity, accuracy as standard evaluation to evaluate the quality of cutting sample. The experimental results show that the system can cut out the correct spine region, and its cutting quality is nearly 80%, its similarity, sensitivity, specificity and accuracy are up to 99%, and the performance is excellent.

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Tsai, Ming-Gen, and 蔡明艮. "Switchable T1 / T2-weighted Contrast Agent Applied on Cancer Theranostic." Thesis, 2016. http://ndltd.ncl.edu.tw/handle/21662672035227189470.

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碩士 國立中興大學 化學系所 104 To reach the accurate cancer treatment, the ‘‘theranostic nanoparticle’’ become popular. The word“theranostic”means that the nanoparticles can diagnose the situation at first and then carry out the therapy. As the result, it can not only decrease the drug dose and the side effect, but also it can achieve more accurate efficiency of treatment for the nanoparticles which can control drug release by stimulate. However, it is difficult to know whether the drug is released completely by stimulate or not. As we know, there do not appear any platform which can evaluate the efficiency of treatment immediately among studies nowadays. The NIR-activated nanoparticles are synthesize in this study, and the core of it can transform NIR to heat. According the extinction coefficient, photothermal conversion efficiency and good photothermal stability, the experimental results reveal that the nanoparticles applied in this study are outstanding photothermal agent. After irradiated the laser to raise the temperature, the heat will stimulate the nanoparticles to transform structure to induce its MRI contrast ability to change. In our study, the T1 relaxivity will increase after heating. We can use this change to determine whether the stimulation is triggered on by NIR laser. Meanwhile, the product also can detect the drug release efficiency by measuring the T1 relaxivity, when it is intercalated the DOX (anti-cancer drug) into nanoparticles. Besides, it can solve the drug resistance of MCF-7/ADR cell line by co-therapy of photothermal therapy and chemotherapy. In summary, the product not only have property of normal theranostic nanoparticle but also can get real-time information of therapy. We believe that this technology can be effectively applied on cancer theranostic.

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Shen, Yu-Han, and 沈于涵. "Construction of Brain Templates using T1-weighted and DT MRI Data." Thesis, 2012. http://ndltd.ncl.edu.tw/handle/6x695a.

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碩士 國立交通大學 生醫工程研究所 101 This study aims at the development of a construction algorithm for brain templates using T1-weighted and diffusion tensor (DT) magnetic resonance imaging (MRI) data. Recently, several brain templates developed in the ICBM-152 stereotactic space, such as ICBM452, ICBM DTI-81 atlas, and IIT DT brain template. In addition to inter-subject variation, however, the brain structures vary with races, genders, ages, and diseases. Hence, a construction algorithm of the stereotactic space for a specific study group can facilitate the structure analysis of the brains. Moreover, we improved the accuracy of registration procedure to reduce the image distortion during the template construction procedure. First, a symmetric and diffeomorphic non-rigid registration algorithm was used to provide both forward and inverse deformation fields. Also, we proposed an objective function which simultaneously utilized both T1-weighted and DT data to improve the accuracy of registration. The DT image is estimated from noise-sensitive diffusion-weighted images (DWIs). All details of DT-MRI processing procedure were carefully considered in this study. First, DT images were estimated from DWIs by the MedINRIA tensor estimation tool, which can tolerate the low signal-to-noise ratio (SNR) in clinical MRI and ensure the positive definiteness of all tensors. For preserving the good property of estimated tensors, Log-Euclidean metrics was used to avoid the problems of the tensor swelling effect and non-positive eigenvalues. In this study, 64 normal subjects were recruited for MRI scanning and template construction. First, we rigidly registered the MRI image to baseline DWI image for each subject to align both modalities of images in the same stereotactic space. Second, a representative subject was chosen as the one having the smallest deformation magnitude when registering to other subject images. Third, each subject image was registered to the temporary template, which was initialized as the image of the representative subject. The average of the obtained inverse deformation fields was applied to the image of the representative subject to update the temporary template. Iteratively applying the third step until the template image converges. Finally, we constructed a representative template and an average template in this converged space. In this study, two criteria were used to evaluate the constructed template images and the registration accuracy, including the DTI differences and overlaps between each subject and the template. The evaluation results showed that the accuracy of non-rigid registration was improved by simultaneously utilizing both T1-weighted and DT data. Furthermore, the results displayed a high correlation between the proposed template and registered subject images. Consequently, the proposed brain template construction could provide a stereotactic space for a specific subject group.

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Huang, Chin-Jan, and 黃群然. "Skull Stripping Based on a Cluster-Constraint Watershed Method for MR T1-Weighted Image." Thesis, 2011. http://ndltd.ncl.edu.tw/handle/87206207958444014060.

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碩士 國立陽明大學 醫學工程研究所 99 The purpose of skull-stripping is to remove non-brain tissue from a head image and retain brain tissue only. It has played an important role in neuroimage analyses because it’s a basic preliminary step in many clinical applications. There are also many applications benefit from the ability to accurately segment brain from non-brain tissue, such as registration, cortical flattening algorithm and brain atrophy estimation. But skull-stripping has been a tricky and challenging problem all along due to the complexity of human brain structure, variety of individual characteristics and variable parameters of MR scanners. This study proposes a semi-automatic method to perform skull-stripping in T1-weighted magnetic resonance（MR）head images. We first apply a series of pre-processing steps combining bilateral filtering and fuzzy possibilistic c-means to smooth noise and cluster images. Then we apply watershed algorithm to segment clustered images into several regions. Finally, a post-merging step merges brain-like regions, and then a morphology processing refines the brain region to a final result. Experimental results suggest that our algorithm is potentially accurate, robust, and fast for automatically skull-stripping MR head image volumes.

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Namkung, Sook [Verfasser]. "Superparamagnetic iron oxide (SPIO)-enhanced liver MR imaging with ferucarbotran : efficacy for characterization of focal liver lesions with T2-weighted FSE and T2*-weighted GRE and early dynamic T1-weighted GRE sequences / vorgelegt von Sook Namkung." 2006. http://d-nb.info/98196723X/34.

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Brandão, Fernanda Sofia Quintela da Silva. "Segmentation of deep grey matter structures by using magnetic resonance high-resolution T1- weighted images acquired at 3 Tesla : a technical approach." Master's thesis, 2010. https://repositorio-aberto.up.pt/handle/10216/102402.

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Brandão, Fernanda Sofia Quintela da Silva. "Segmentation of deep grey matter structures by using magnetic resonance high-resolution T1- weighted images acquired at 3 Tesla : a technical approach." Dissertação, 2010. https://repositorio-aberto.up.pt/handle/10216/102402.

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Meddour, Miriam. "MR-tomographische Darstellung intracerebraler Blutungen mit und ohne Therapie." Doctoral thesis, 2011. http://hdl.handle.net/11858/00-1735-0000-0006-B180-D.

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Dissertations / Theses on the topic 'T1-weighted'

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