Relevant bibliographies by topics / Computer-Aided Tomography

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  1. Journal articles
  2. Dissertations / Theses
  3. Books
  4. Book chapters
  5. Conference papers
  6. Reports

Academic literature on the topic 'Computer-Aided Tomography'

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Published: 25 May 2024

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Journal articles on the topic "Computer-Aided Tomography"

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Juchems, Markus S., Andrea S. Ernst, Hans-Juergen Brambs, and Andrik J. Aschoff. "Computer-aided detection in computer tomography colonography: a review." Expert Opinion on Medical Diagnostics 2, no. 5 (2008): 487–95. http://dx.doi.org/10.1517/17530059.2.5.487.

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van Ginneken, B. "Computer-Aided Diagnosis in Thoracic Computed Tomography." Imaging Decisions MRI 12, no. 3 (2008): 11–22. http://dx.doi.org/10.1111/j.1617-0830.2009.00129.x.

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Woodworth, B. A., A. G. Chiu, N. A. Cohen, D. W. Kennedy, B. W. O'Malley, and J. N. Palmer. "Real-time computed tomography image update for endoscopic skull base surgery." Journal of Laryngology & Otology 122, no. 4 (2007): 361–65. http://dx.doi.org/10.1017/s0022215107000485.

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AbstractIntroduction:The development of computer-aided systems for endoscopic sinus surgery has enabled surgical navigation through diseased or surgically altered sinus anatomy with increased confidence. However, conventional computer-aided systems do not provide intra-operative updated computed tomography imaging. We describe the technical aspects of the xCAT™, a new intra-operative mobile volume computed tomography scanner.Technical report:A patient with a malignant melanoma unwittingly removed at another hospital underwent surgery for removal of the lateral nasal wall and directed biopsies, in an attempt to identify the site of tumour origin. The procedure was performed with the GE InstaTrak 3500 PlusTM computer-aided system, updated with intra-operative computed tomography images. Intra-operative, updated images were integrated successfully into the InstaTrak system, and these images were consistent with the observed endoscopic anatomy.Conclusion:The xCAT intra-operative mobile volume computed tomography scanner is a technological advancement that can assist the endoscopic sinus surgeon when performing complex rhinological and skull base procedures.
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Saba, Luca, Giancarlo Caddeo, and Giorgio Mallarini. "Computer-Aided Detection of Pulmonary Nodules in Computed Tomography." Journal of Computer Assisted Tomography 31, no. 4 (2007): 611–19. http://dx.doi.org/10.1097/rct.0b013e31802e29bf.

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Ziyad, Shabana Rasheed, Venkatachalam Radha, and Thavavel Vayyapuri. "Overview of Computer Aided Detection and Computer Aided Diagnosis Systems for Lung Nodule Detection in Computed Tomography." Current Medical Imaging Formerly Current Medical Imaging Reviews 16, no. 1 (2020): 16–26. http://dx.doi.org/10.2174/1573405615666190206153321.

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Background: Lung cancer has become a major cause of cancer-related deaths. Detection of potentially malignant lung nodules is essential for the early diagnosis and clinical management of lung cancer. In clinical practice, the interpretation of Computed Tomography (CT) images is challenging for radiologists due to a large number of cases. There is a high rate of false positives in the manual findings. Computer aided detection system (CAD) and computer aided diagnosis systems (CADx) enhance the radiologists in accurately delineating the lung nodules. Objectives: The objective is to analyze CAD and CADx systems for lung nodule detection. It is necessary to review the various techniques followed in CAD and CADx systems proposed and implemented by various research persons. This study aims at analyzing the recent application of various concepts in computer science to each stage of CAD and CADx. Methods: This review paper is special in its own kind because it analyses the various techniques proposed by different eminent researchers in noise removal, contrast enhancement, thorax removal, lung segmentation, bone suppression, segmentation of trachea, classification of nodule and nonnodule and final classification of benign and malignant nodules. Results: A comparison of the performance of different techniques implemented by various researchers for the classification of nodule and non-nodule has been tabulated in the paper. Conclusion: The findings of this review paper will definitely prove to be useful to the research community working on automation of lung nodule detection.
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Ribeiro, Luisa, Rui Bernardes, and José Cunha-Vaz. "Computer-aided Analysis of Fundus Photographs." European Ophthalmic Review 05, no. 02 (2011): 104. http://dx.doi.org/10.17925/eor.2011.05.02.104.

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Colour fundus photography is the most frequently used imaging modality because it is non-invasive, well accepted by patients and above all, because it allows documentation and automated analysis of the ophthalmoscopic examination. Colour fundus photography is considered crucial for diabetic retinopathy management to identify disease and its progression in clinical practice. This article focuses on automated computer-aided analysis of fundus digital photographs with special emphasis on microaneurysm dynamics. Together with optical coherence tomography measurements of extracellular space and retinal thickness, both based on non-invasive procedures, this technique allows close follow-up of the main changes in the diabetic retina. Determination of the activity of the retinal disease and individual risk profiles using these non-invasive procedures contribute to personalised management of diabetic retinopathy by identifying eyes at risk from vision-threatening complications, such as macular oedema and proliferative retinopathy.
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Ahmed, Mamdouhh, Mariam Kamel Salah, and Nesrine Khairy. "Computer-Aided Design/Computer-Aided Manufacturing Cutting Guides for Odontectomy of Deeply Impacted Mandibular Third Molars." Open Access Macedonian Journal of Medical Sciences 6, no. 12 (2018): 2395–401. http://dx.doi.org/10.3889/oamjms.2018.371.

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AIM: To evaluate a new technique for surgical removal of deeply impacted mandibular third molars (DIMTM), using computer-guided cutting guide to maintain inferior alveolar nerve (IAN) integrity and the covering buccal bone.
 PATIENTS AND METHODS: Eighteen cases indicated for removal of DIMTM. Cone-beam Computed Tomography (CBCTs) used to determine the tooth’s relation to the IAN. Computer-guided software used for fabrication of surgical cutting guide stent to expose the impacted tooth and repositioning of bone after odontectomy without fixation. Clinical assessment included a neurosensory deficit of IAN, pain using a visual analogue scale (VAS), facial swelling, and maximal mouth opening (MMO). CBCTs were taken immediately and six months postoperatively to evaluate position and healing of bone.
 RESULTS: None of the patients showed a permanent neurological deficit of IAN while all patients showed normal parameters of pain, facial swelling and MMO.
 CONCLUSION: this technique has shown the accurate determination of the bony window cuts with subsequent preservation of IAN and external oblique ridge.
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Wyber, Ron J., and Brian G. Ferguson. "Interferometry and computer‐aided tomography as an acoustic analysis tool." Journal of the Acoustical Society of America 115, no. 5 (2004): 2547. http://dx.doi.org/10.1121/1.4783706.

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Liu, Jiamin, Sanket Pattanaik, Jianhua Yao, et al. "Computer aided detection of epidural masses on computed tomography scans." Computerized Medical Imaging and Graphics 38, no. 7 (2014): 606–12. http://dx.doi.org/10.1016/j.compmedimag.2014.04.007.

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Marom, Shlomo A., and Martin J. Linden. "Computer aided stress analysis of long bones utilizing computed tomography." Journal of Biomechanics 23, no. 5 (1990): 399–404. http://dx.doi.org/10.1016/0021-9290(90)90294-d.

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Dissertations / Theses on the topic "Computer-Aided Tomography"

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Fayed, Karam Ali. "Computational Methods for Image Rotation and Computer Aided Tomography Volume I: Theoretical Basi. Volume II: Computer Software." Thesis, Cranfield University, 1993. http://dspace.lib.cranfield.ac.uk/handle/1826/12145.

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This thesis, describes work whose principal goal has been to research and iden- tify an optimum algorithm for computing the Radon transform - optimum in the sense of minimum CPU time for maximum image fidelity. This transform is the basis for a wide range of applications which are either directly or indirectly associ- ated with Computer Aided Tomography. It has therefore been important to try and identify an optimum computational technique for the evaluation of this transform. A central theme to the computational techniques reported in this thesis has been the digital image rotation for which a new algorithm has been designed based en- tirely on integer arithmetic. This algorithm has been used for the evaluation of the forward and inverse Radon transforms (in particular, forward and back-projection). The relationship between the interpolation methods used for image rotation and the filtering techniques required to compute the inverse Radon transform has been stud- ied in detail. The result of this study has been to identify a specific data processing path which provides an algorithm whose 'computational energy' is approximately half that of previously published algorithms. With an optimum algorithm identified, research has been undertaken into the use of the Radon transform for two-dimensional array processing. It is shown that the Radon transform can be used to reduce the dimensionality of a problem from two-dimensions to a one-dimensional problem. By applying signal processors to the set of projections obtained by taking the Radon transform of an image, the inverse Radon transform can be used to reconstruct the processed image. The value of this approach lies in the fact that some useful one-dimensional signal processing algorithms do not have a two-dimensional extension or else the implementation of the two-dimensional algorithm is computationally intensive. An example of the latter case is reported.
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Mazinani, Mahdi. "Computer aided detection and measurement of coronary artery disease from computed tomography angiography images." Thesis, Kingston University, 2012. http://eprints.kingston.ac.uk/24527/.

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Coronary artery disease is one of the most pernicious diseases around the world and early identification of vascular disease can help to reduce morbidity and mortality. Assessment of the degree of vascular obstruction, or stenosis, is critical for classifying the risks of the future vascular events. Automatic detection and quantification of stenosis are important in assessing coronary artery disease from medical imagery, especially for disease progression. Important factors affecting the reproducability and robustness of accuarate quantification arise from the partial volume effect and other noise sources. The main goal of this study is to present a fully automatic approach for detection and quantification of the stenosis in the coronary arteries. The proposed approach begins by building a 3D reconstruction of the coronary arterial system and then making accurate measurement of the vessel diameter from a robust estimate of the vessel cross-section. The proposed algorithm models the partial volume effect using a Markovian fuzzy clustering method in the process of accurate quantification of the degree of stenosis. To evaluate the accuracy and reproducibility of the measurement, the method was applied to a vascular phantom that was scanned using different protocols. The algorithm was applied to 20 CTA patient datasets containing a total of 85 stenoses, which were all successfully detected, with an average false positive rate of 0.7 per scan.
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Qi, Xin. "COMPUTER-AIDED DIAGNOSIS OF EARLY CANCERS IN THE GASTROINTESTINAL TRACT USING OPTICAL COHERENCE TOMOGRAPHY." Case Western Reserve University School of Graduate Studies / OhioLINK, 2008. http://rave.ohiolink.edu/etdc/view?acc_num=case1207245243.

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Zhang, Ning. "Quantification of the proliferation of soil fungi in three dimensions using micro-computer aided tomography." Thesis, The University of Sydney, 2015. http://hdl.handle.net/2123/13691.

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Good soil structure is important for sustaining agricultural production and preserving functions of the soil ecosystem. Soil aggregation is a critically important component of soil structure. Stable aggregates enable water infiltration, gas exchange for biological activities of plant roots and microorganisms, living space and surfaces for soil microbes, and contribute to stabilization of organic matter and storage of organic carbon (OC) in soil. Soil aggregation process involves fine roots, organic matter and fungal hyphae. Hyphal proliferation is essential for soil aggregation, and sequestration of OC in soil. Organic materials and available phosphorus are two of the major factors that influence fungi in soil. Organic materials are a source of energy for saprotrophic microbes and fungal hyphae may increase in the presence of organic matter. Phosphorus is an important element usually found depleted in soil ecosystems. The low availability of phosphorus may limit the biological activity of microbes. Arbuscular mycorrhizal fungi (AM) benefit plants by delivering phosphorus to the root system. However, the density and the length of hyphae of AM fungi do not appear to be increased by available phosphorus. We do not yet have a mechanism to directly quantify the density of hyphae in soil. A number of indirect methods have been used to visualize distribution of fungi in soil. Reliable analyses of soil are limited because of the use of destructive harvests to gain information. Soils are fragile, and fragility limits opportunity for non-destructive analysis. The soil ecosystem is also complex. Soil particles are dense and the density obscures the visualization of fungal hyphae. Fungal hyphae are relatively fine and information at the small scale (<250 µm) is key to understanding how fungi respond to environmental stimuli. The experiments conducted here developed a new method for the observation of fungi and quantification of hyphae in three dimensions. The methods were first tested using a melanised saprotrophic fungus, 222A. The response of two AM fungi, Glomus mosseae and Glomus pellucidum, growing together to common environmental factors was then quantified. Hyphae were quantified in an artificial soil matrix over 6 week’s incubation using micro-computer aided tomography (microCT). MicroCT provides three dimensional images of mycelia within electron lucent materials and enables the visualization and quantification of hyphae. Starch stimulated proliferation of 222A after 2 weeks. Starch, and starch and K2HPO4, stimulated proliferation of hyphae of AM fungi after 3 and 6 weeks. K2HPO4 stimulated hyphal proliferation only after 3 weeks. The images also indicate that fungal hyphae grew appressed to the surfaces of the particles rather than through the spaces between the particles. The capacity to quantify hyphae in three-dimensional space allows a wide range of questions to now be addressed. Apart from studying mechanisms of carbon turnover, more complex processes may now be considered. Soil is commonly thought of as a black box. That black box potentially is now a shade of grey.
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Mazeyev, Yuri. "Direction estimation on 3D-tomography images of jawbones." Thesis, Halmstad University, School of Information Science, Computer and Electrical Engineering (IDE), 2008. http://urn.kb.se/resolve?urn=urn:nbn:se:hh:diva-1661.

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<p>The present work expose a technique of estimation of optimal direction for placing dental implant. A volumetric computed tomography (CT) scan is used as a help of the following searches. The work offers criteria of the optimal implant placement direction and methods of evaluation on direction’s significance. The technique utilizes structure tensor to find a normal to the jawbone surface. Direction of that normal is then used as initial direction for search of optimal direction.</p><p>The technique described in the present work aimed to support doctor’s decisions during dental implantation treatment.</p>
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Sprague, Matthew J. "A Genetic Algorithm Approach to Feature Selection for Computer Aided Detection of Lung Nodules." University of Dayton / OhioLINK, 2016. http://rave.ohiolink.edu/etdc/view?acc_num=dayton1480465837455442.

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Wu, Bangxian, and 吴邦限. "Clinical applications of imaging informatics: computer aided diagnosis of nasopharyngeal carcinoma based on PET-CTand multimedia electronic patient record system for neurosurgery." Thesis, The University of Hong Kong (Pokfulam, Hong Kong), 2012. http://hub.hku.hk/bib/B48521917.

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Medical imaging informatics is one of the important research areas in radiology that studies how information available on medical images is retrieved, analyzed, and enhanced. Recent development in medical imaging informatics has resulted in improvement of diagnostic accuracy based on imaging examinations, as well as efficiency in clinical workflow. Computer aided diagnosis (CAD) and electronic patient record system (ePR) are both topics in medical imaging informatics that have matured from research concepts into commercially available computerized systems in clinical environment. The current challenges are to further broaden their scope of applications. In this thesis project, I developed a CAD system for interpreting PET/CT examinations and an ePR system for patient data integration in neurosurgery suites. Specifically, the CAD system in this project was designed to automatically diagnose nasopharyngeal carcinoma (NPC) on Positron emission tomography/computed tomography (PET/CT) examinations, which aimed to detect and classify both the primary NPC and its nodal metastasis. The regions of interests (ROIs) were segmented from the PET images and registered onto the CT in order to combine the imaging features from both modalities and the a priori anatomical knowledge of the suspicious lesion. These combined features were then classified by a support vector machine (SVM) to generate the final diagnosis result. The system was validated with 25 PET/CT examinations from 10 patients suffering from NPC, and the result produced by the system was compared to the gold standard of lesions manually contoured by experienced radiologists. The results confirmed that the system successfully distinguished all 53 genuine lesions from the mimickers due to normal physiological uptake and artifacts that also produced potentially confusing signals. The second part of the project involved development of an electronic patient record system (ePR) that integrated all the myriad of images and different types of clinical information before, during, and after neurosurgery operations, in order to enhance efficiency of work flow in this unique clinical environment. The system comprises of pre-, intra-, and post-operation modules which correspond to the different stages of the neurosurgery. The pre-op module was developed to store and categorize all images and data before the procedure to assist the surgeons in planning operation. The intra-op module integrates all the input signals, waveforms, images and videos that are produced by different imaging and physiological monitoring devices in the operation room during the surgery, and displays all the relevant information in a single large screen in real time to ease monitoring of the procedure. The post-op module helps surgeons to review all the data acquired from all the prior stages for follow-up of the treatment outcome. One-tumor case was utilized to test the pre-op module, and the signals and waveforms simulators were used to evaluate the performance of the intra-op module. In summary, two different medical informatics systems, a CAD and an ePR system were developed. Both showed promising results in laboratory tests. Future work would involve performance enhancement and feedback of the systems, and ultimately evaluation of these systems in the clinical environment.<br>published_or_final_version<br>Diagnostic Radiology<br>Master<br>Master of Philosophy
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El, Azami Meriem. "Computer aided diagnosis of epilepsy lesions based on multivariate and multimodality data analysis." Thesis, Lyon, 2016. http://www.theses.fr/2016LYSEI087/document.

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Environ 150.000 personnes souffrent en France d'une épilepsie partielle réfractaire à tous les médicaments. La chirurgie, qui constitue aujourd’hui le meilleur recours thérapeutique nécessite un bilan préopératoire complexe. L'analyse de données d'imagerie telles que l’imagerie par résonance magnétique (IRM) anatomique et la tomographie d’émission de positons (TEP) au FDG (fluorodéoxyglucose) tend à prendre une place croissante dans ce protocole, et pourrait à terme limiter de recourir à l’électroencéphalographie intracérébrale (SEEG), procédure très invasive mais qui constitue encore la technique de référence. Pour assister les cliniciens dans leur tâche diagnostique, nous avons développé un système d'aide au diagnostic (CAD) reposant sur l'analyse multivariée de données d'imagerie. Compte tenu de la difficulté relative à la constitution de bases de données annotées et équilibrées entre classes, notre première contribution a été de placer l'étude dans le cadre méthodologique de la détection du changement. L'algorithme du séparateur à vaste marge adapté à ce cadre là (OC-SVM) a été utilisé pour apprendre, à partir de cartes multi-paramétriques extraites d'IRM T1 de sujets normaux, un modèle prédictif caractérisant la normalité à l'échelle du voxel. Le modèle permet ensuite de faire ressortir, dans les images de patients, les zones cérébrales suspectes s'écartant de cette normalité. Les performances du système ont été évaluées sur des lésions simulées ainsi que sur une base de données de patients. Trois extensions ont ensuite été proposées. D'abord un nouveau schéma de détection plus robuste à la présence de bruit d'étiquetage dans la base de données d'apprentissage. Ensuite, une stratégie de fusion optimale permettant la combinaison de plusieurs classifieurs OC-SVM associés chacun à une séquence IRM. Enfin, une généralisation de l'algorithme de détection d'anomalies permettant la conversion de la sortie du CAD en probabilité, offrant ainsi une meilleure interprétation de la sortie du système et son intégration dans le bilan pré-opératoire global<br>One third of patients suffering from epilepsy are resistant to medication. For these patients, surgical removal of the epileptogenic zone offers the possibility of a cure. Surgery success relies heavily on the accurate localization of the epileptogenic zone. The analysis of neuroimaging data such as magnetic resonance imaging (MRI) and positron emission tomography (PET) is increasingly used in the pre-surgical work-up of patients and may offer an alternative to the invasive reference of Stereo-electro-encephalo -graphy (SEEG) monitoring. To assist clinicians in screening these lesions, we developed a computer aided diagnosis system (CAD) based on a multivariate data analysis approach. Our first contribution was to formulate the problem of epileptogenic lesion detection as an outlier detection problem. The main motivation for this formulation was to avoid the dependence on labelled data and the class imbalance inherent to this detection task. The proposed system builds upon the one class support vector machines (OC-SVM) classifier. OC-SVM was trained using features extracted from MRI scans of healthy control subjects, allowing a voxelwise assessment of the deviation of a test subject pattern from the learned patterns. System performance was evaluated using realistic simulations of challenging detection tasks as well as clinical data of patients with intractable epilepsy. The outlier detection framework was further extended to take into account the specificities of neuroimaging data and the detection task at hand. We first proposed a reformulation of the support vector data description (SVDD) method to deal with the presence of uncertain observations in the training data. Second, to handle the multi-parametric nature of neuroimaging data, we proposed an optimal fusion approach for combining multiple base one-class classifiers. Finally, to help with score interpretation, threshold selection and score combination, we proposed to transform the score outputs of the outlier detection algorithm into well calibrated probabilities
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Narayanan, Barath Narayanan. "New Classifier Architecture and Training Methodologies for Lung Nodule Detection in Chest Radiographs and Computed Tomography." University of Dayton / OhioLINK, 2017. http://rave.ohiolink.edu/etdc/view?acc_num=dayton1508237793168873.

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Quatrehomme, Auréline. "Caractérisation des lésions hépatiques focales sur des acquisitions scanner multiphasiques." Thesis, Montpellier 2, 2013. http://www.theses.fr/2013MON20207/document.

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L'évolution des techniques d'acquisition des imageries médicales et leur importance de plus en plus grande dans la prise en charge du patient (diagnostic, préparation d'intervention, suivi, etc.), font émerger de nouveaux besoins autour du traitement informatique des images. La reconnaissance du type de lésions hépatiques est un grand enjeu, notamment car le cancer du foie, létal et très répandu, est souvent diagnostiqué trop tard pour sauver le patient. C'est dans ce cadre qu'est né le projet de recherche de ce manuscrit, fruit d'une collaboration entre la société IMAIOS et le Laboratoire d'Informatique, de Robotique et de Microélectronique de Montpellier (LIRMM).Cette thèse présente un système complet et automatique permettant, à partir d'images de lésions au format médical DICOM, d'extraire des descripteurs visuels de divers nodules hépatiques puis de les différencier à l'aide de ces derniers. Les contributions décrites s'articulent autour de divers axes : normalisation des niveaux de gris des images de lésions par rapport au foie sain, proposition, analyse et tests de descripteurs visuels (s'appuyant notamment sur les informations temporelles ou de densité des tissus), caractérisations diverses des différents types de lésions grâce à ces descripteurs et à un algorithme de classification. Les données sur lesquelles ces travaux ont été effectués sont des examens scanner multiphasiques<br>Medical imaging acquisition has taken benefits from recent advances and is becoming more and more important in the patient care process. New needs raise, which are related to image processing. Hepatic lesion recognition is a hot topic, especially because liver cancer is wide-spread and leads to death, most of the time because of the diagnosis which is made too late. In this context is born this manuscrit research project, a collaboration between IMAIOS company and the Laboratory of Informatics, Robotics and Micro-electronics ofMontpellier (LIRMM).This thesis presents a complete and automated system that extracts visual features from lesion images in the medical format DICOM, then differenciate them on these features.The various described contributions are: intensity normalization using healthy liver values, analysis and experimentations around new visual features, which use temporal information or tissue density, different kind of caracterisation of the lesions. This work has been done on multi-phase Computed Tomography acquisitions
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Books on the topic "Computer-Aided Tomography"

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Industrial Computerized Tomography Topical (1989 Seattle, Wash.). Industrial computerized tomography: Topical proceedings, July 25-27, 1989, Seattle, WA. The Society, 1989.

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Seminar Computertomografie (2nd : 1991 : Munich, Germany), ed. Computertomografie: Vorträge des 2. Seminars, 11.-12. März 1991. Deutsche Gesellschaft für Zerstörungsfreie Prüfung, 1991.

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International Symposium on Computerized Tomography for Industrial Applications (3rd 1994 Berlin). International Symposium on Computerized Tomography for Industrial Applications =: Internationales Symposium über Computertomografie für die Industrielle Anwendung : 8.-10. Juni 1994, Bundesministerium des Innern, Berlin. Deutsche Gesellschaft für Zerstörungsfreie Prüfung, 1995.

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Drago, Carl. Implant Restorations: A Step-By-Step Guide. Wiley & Sons, Incorporated, John, 2008.

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Drago, Carl. Implant Restorations: A Step-By-Step Guide. Wiley & Sons, Incorporated, John, 2019.

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Implant Restorations: A Step-By-Step Guide. Wiley & Sons, Limited, John, 2020.

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Drago, Carl. Implant Restorations: A Step-By-Step Guide. Wiley & Sons, Limited, John, 2019.

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Drago, Carl. Implant Restorations: A Step-By-Step Guide. Wiley & Sons, Incorporated, John, 2019.

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Drago, Carl. Implant Restorations: A Step-By-Step Guide. Wiley & Sons, Incorporated, John, 2014.

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Drago, Carl. Implant Restorations: A Step-by-Step Guide. Wiley-Interscience, 2014.

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Book chapters on the topic "Computer-Aided Tomography"

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Peixoto, Hugo, and Victor Alves. "Computer-Aided Diagnosis in Brain Computed Tomography Screening." In Advances in Data Mining. Applications and Theoretical Aspects. Springer Berlin Heidelberg, 2009. http://dx.doi.org/10.1007/978-3-642-03067-3_7.

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de Moura, Joaquim, Gabriela Samagaio, Jorge Novo, et al. "Automatic Identification of Diabetic Macular Edema Biomarkers Using Optical Coherence Tomography Scans." In Computer Aided Systems Theory – EUROCAST 2019. Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-45096-0_31.

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Vidal, Plácido, Joaquim de Moura, Jorge Novo, Manuel G. Penedo, and Marcos Ortega. "Intuitive and Coherent Intraretinal Cystoid Map Representation in Optical Coherence Tomography Images." In Computer Aided Systems Theory – EUROCAST 2019. Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-45096-0_34.

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Alemán-Flores, Miguel, Patricia Alemán-Flores, and Rafael Fuentes-Pavón. "Analysis of Global and Local Intensity Distributions for the Segmentation of Computed Tomography Images." In Computer Aided Systems Theory – EUROCAST 2015. Springer International Publishing, 2015. http://dx.doi.org/10.1007/978-3-319-27340-2_62.

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Budiño, Alejandro, Lucía Ramos, Joaquim de Moura, Jorge Novo, Manuel G. Penedo, and Marcos Ortega. "Robust Deep Learning-Based Approach for Retinal Layer Segmentation in Optical Coherence Tomography Images." In Computer Aided Systems Theory – EUROCAST 2022. Springer Nature Switzerland, 2022. http://dx.doi.org/10.1007/978-3-031-25312-6_50.

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Laznovsky, Jakub, Adam Brinek, Tomas Zikmund, and Jozef Kaiser. "Ex-vivo Evaluation of Newly Formed Bone After Lumbar Interbody Fusion Surgery Using X-ray Micro Computed Tomography." In Medical Imaging and Computer-Aided Diagnosis. Springer Nature Singapore, 2023. http://dx.doi.org/10.1007/978-981-16-6775-6_9.

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Priyanka, P., V. Norris Juliet, and S. Shenbaga Devi. "Detection of Glaucoma Using Anterior Segment Optical Coherence Tomography Images." In Computer Aided Intervention and Diagnostics in Clinical and Medical Images. Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-030-04061-1_30.

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Arakeri, Megha P., and Ram Mohana Reddy G. "Recent Advances and Future Potential of Computer Aided Diagnosis of Liver Cancer on Computed Tomography Images." In Communications in Computer and Information Science. Springer Berlin Heidelberg, 2011. http://dx.doi.org/10.1007/978-3-642-22786-8_31.

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Chen, Michael M. "Computer-Aided Tomographic Thermography." In Heat Transfer in Medicine and Biology. Springer US, 1985. http://dx.doi.org/10.1007/978-1-4684-8285-0_11.

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Suzuki, Kenji, and Abraham H. Dachman. "Computer-Aided Diagnosis in Computed Tomographic Colonography." In Atlas of Virtual Colonoscopy. Springer New York, 2010. http://dx.doi.org/10.1007/978-1-4419-5852-5_12.

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Conference papers on the topic "Computer-Aided Tomography"

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Ladas, Kostas T., George A. Tsihrintzis, and Mohammad Maleki. "Contour reconstruction in computer-aided holography." In OSA Annual Meeting. Optica Publishing Group, 1990. http://dx.doi.org/10.1364/oam.1990.mff3.

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Abstract:
In this presentation we generate images of the directional derivative and the Laplacian of the complex index of refraction of a weakly inhomogeneous scattering object. The object is embedded in a known background medium and is probed with coherent plane optical wavefields. The intensity distribution of the wavefields diffracted by the object is then recorded over lines perpendicular to the direction of propagation of the incident waves and is used as input data to a diffraction-tomographic procedure that generates estimates (reconstructions) of the directional derivative and the Laplacian of the index of refraction of the scatterer. The reconstruction algorithm is of the usual filtered-back-propagation type of diffraction tomography,1 in which appropriate modification of the tomographic filter is required. The success of the procedure, even when only intensity data are available (as is the case in the usual optical scattering experiments),2 is discussed briefly and is verified through a number of examples that use both synthetic and experimental data.
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Juarez Chambi, Ronald Miguel, Carmen Kut, Jesus Rico-Jimenez, et al. "Detection of brain tumor margins using optical coherence tomography." In Computer-Aided Diagnosis, edited by Kensaku Mori and Nicholas Petrick. SPIE, 2018. http://dx.doi.org/10.1117/12.2293599.

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Guo, Bang Jun, Xiuxiu He, Tonghe Wang, et al. "Benign and malignant thyroid classification using computed tomography radiomics." In Computer-Aided Diagnosis, edited by Horst K. Hahn and Maciej A. Mazurowski. SPIE, 2020. http://dx.doi.org/10.1117/12.2549087.

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Mortazi, Aliasghar, Jayaram K. Udupa, Yubing Tong, and Drew A. Torigian. "A post-acquisition standardization method for positron emission tomography images." In Computer-Aided Diagnosis, edited by Horst K. Hahn and Maciej A. Mazurowski. SPIE, 2020. http://dx.doi.org/10.1117/12.2550423.

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Bulygin, Theodor V., E. Y. Ovodkova, and Michael S. Umansky. "Correction of aberrations in interferometric systems with computer-aided phase reconstuction." In Analytical Methods for Optical Tomography, edited by Gennady G. Levin. SPIE, 1992. http://dx.doi.org/10.1117/12.131886.

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He, Xiuxiu, Bang Jun Guo, Tonghe Wang, et al. "Classification of lesion specific myocardial ischemia using cardiac computed tomography radiomics." In Computer-Aided Diagnosis, edited by Horst K. Hahn and Maciej A. Mazurowski. SPIE, 2020. http://dx.doi.org/10.1117/12.2548471.

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Faryna, Khrystyna, Fakrul I. Tushar, Vincent M. D’Anniballe, Rui Hou, Geoffrey D. Rubin, and Joseph Y. Lo. "Attention-guided classification of abnormalities in semi-structured computed tomography reports." In Computer-Aided Diagnosis, edited by Horst K. Hahn and Maciej A. Mazurowski. SPIE, 2020. http://dx.doi.org/10.1117/12.2551370.

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Hu, Mingzhe, Jing Wang, Jacob Wynne, Tian Liu, and Xiaofeng Yang. "A vision-GNN framework for retinopathy classification using optical coherence tomography." In Computer-Aided Diagnosis, edited by Khan M. Iftekharuddin and Weijie Chen. SPIE, 2023. http://dx.doi.org/10.1117/12.2653615.

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Singhal, Vanika, Sidharth Abrol, Daphne Mulot, et al. "Low does calcium scoring in cardiac computer tomography using deep learning." In Computer-Aided Diagnosis, edited by Susan M. Astley and Weijie Chen. SPIE, 2024. http://dx.doi.org/10.1117/12.3005114.

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Macedo, Maysa M. G., and Dario A. B. Oliveira. "Exploring features towards semantic characterization of lung nodules in computed tomography images." In Computer-Aided Diagnosis, edited by Horst K. Hahn and Kensaku Mori. SPIE, 2019. http://dx.doi.org/10.1117/12.2512661.

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Reports on the topic "Computer-Aided Tomography"

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Xia, Jessie Q. Image Processing and Computer Aided Diagnosis in Computed Tomography of the Breast. Defense Technical Information Center, 2007. http://dx.doi.org/10.21236/ada488205.

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Yu, Xiaoli. Improving Detection of Axillary Lymph Nodes by Computer-Aided Kinetic Feature Identification in Positron Emission Tomography. Defense Technical Information Center, 2002. http://dx.doi.org/10.21236/ada412153.

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Yu, Xiaoli. Improving Detection of Axillary Lymph Nodes by Computer-Aided Kinetic Feature Identification in Positron Emission Tomography. Defense Technical Information Center, 2003. http://dx.doi.org/10.21236/ada423474.

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Yu, Xiaoli. Improving Detection of Axillary Lymph Nodes by Computer-Aided Kinetic Feature Identification in Positron Emission Tomography. Defense Technical Information Center, 2000. http://dx.doi.org/10.21236/ada390707.

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