The Experts below are selected from a list of 9330 Experts worldwide ranked by ideXlab platform
N S Jones - One of the best experts on this subject based on the ideXlab platform.
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paediatric fibro osseous lesions of the nose and Paranasal Sinuses
2006Co-Authors: D Mehta, N Clifton, L Mcclelland, N S JonesAbstract:Summary Objective The term “fibro-osseous lesion” is a generic description for a group of lesions involving the Paranasal Sinuses and anterior skull base. We aim to improve understanding of the clinical and pathological presentation of fibro-osseous lesions in children. Methods and results We report two cases of aggressive “fibro-osseous” lesions arising from Paranasal Sinuses and anterior skull base in childhood that were successfully managed surgically. We compare our case reports with a review of the available literature and evaluate the management of these lesions. Conclusions The clinical behaviour and radiological features of fibro-osseous lesions is variable. Aggressive lesions require a radical surgical approach to ensure complete excision, in spite of an increase in associated morbidity. Incomplete excision of aggressive lesions may result in disease recurrence with severe morbidity or mortality. In contrast a slowly progressive lesion often does not warrant extensive surgical excision. Understanding the nature of fibro-osseous lesions facilitates appropriate clinical management.
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ct of the Paranasal Sinuses a review of the correlation with clinical surgical and histopathological findings
2002Co-Authors: N S JonesAbstract:CT of the Paranasal Sinuses: a review of the correlation with clinical, surgical and histopathological findings Computerized tomography (CT) of the Paranasal Sinuses provides valuable information but this should be interpreted in the context of the history and examination as the prevalence of incidental mucosal changes in an asymptomatic population is approximately 30%. A review of the presence or extent of the various anatomical variations that are found in the Paranasal Sinuses does not differ between a symptomatic and an asymptomatic population. This makes it unlikely that these are very important in either initiating or sustaining Paranasal sinus disease. CT provides an excellent map to help the sinus surgeon operate. CT provides information about the extent of mucosal disease but this correlates poorly with symptoms, surgical findings and histopathology. CT does provide invaluable information to help in the diagnosis of atypical sinus infections, malignancy and in the management of the complications of rhinosinusitis. A normal CT in a patient with facial pain should make the doctor consider another diagnosis. In essence, CT helps to support a clinical diagnosis but it should not be interpreted out of context, and it is therefore vital that doctors communicate the clinical picture to their radiological colleagues, and that they learn to interpret the radiographs.
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the nose and Paranasal Sinuses physiology and anatomy
2001Co-Authors: N S JonesAbstract:The Paranasal Sinuses and nose are much more than two cavities behind a projection on the centre of the face. They humidify, filter, warm, and sense what we breathe. The anatomy and physiology interact forming a dynamic system. The anatomy, airflow, nasal resistance, its turbulence, the nasal cycle - a process by which the turbinates or cushions lining the nose alternatively swell and congest from side to side, can all potentially influence the nasal delivery of drugs. Along with these factors mucus rheology and mucociliary clearance influence the removal of substances delivered to the nose. The health of the nose and its immunological response to what is inhaled, be it pollutants, allergens, drugs or vaccines, all need to be considered. It is a fascinating sensor for the body, not only detecting the potentially harmful substances such as smoke, but its psychosexual aspects have far reaching implications and the olfactory pathway has potential as a pathway for the delivery of drugs.
Max L Goodman - One of the best experts on this subject based on the ideXlab platform.
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solitary fibrous tumor of the nasal cavity and Paranasal Sinuses
1991Co-Authors: Lawrence R Zukerberg, Andrew E Rosenberg, Gregory W Randolph, Ben Z Pilch, Max L GoodmanAbstract:We report two solitary fibrous tumors of the nasal cavity and Paranasal Sinuses that were histologically and immunohistochemically virtually identical to solitary fibrous tumors (fibrous mesotheliomas) of the pleura. One tumor arose in a 48-year-old woman and the other in a 45-year-old woman. Both patients presented with nasal symptoms, and both patients are alive without evidence of disease 6 months and 1 year after excision. The tumors had a disorganized or "patternless" arrangement of spindle cells in a collagenous background and prominent vascular channels of varying size. Immunoperoxidase stains on paraffin sections showed staining of the cells for vimentin only; there was no staining for keratin, S-100 protein, desmin, and actin. Both cases presented some degree of diagnostic difficulty and had to be distinguished from other spindle cell tumors of the nasal cavity and Paranasal Sinuses, such as hemangiopericytoma, angiofibroma, and fibrous histiocytoma.
Kelvin Weng Chiong Foong - One of the best experts on this subject based on the ideXlab platform.
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automatic segmentation of the nasal cavity and Paranasal Sinuses from cone beam ct images
2015Co-Authors: Nhat Linh Bui, S H Ong, Kelvin Weng Chiong FoongAbstract:A patient-specific upper airway model is important for clinical, education, and research applications. Cone-beam computed tomography (CBCT) is used for imaging the upper airway but automatic segmentation is limited by noise and the complex anatomy. A multi-step level set segmentation scheme was developed for CBCT volumetric head scans to create a 3D model of the nasal cavity and Paranasal Sinuses. Gaussian mixture model thresholding and morphological operators are first employed to automatically locate the region of interest and to initialize the active contour. Second, the active contour driven by the Kullback–Leibler (K–L) divergence energy in a level set framework to segment the upper airway. The K–L divergence asymmetry is used to directly minimize the K–L divergence energy on the probability density function of the image intensity. Finally, to refine the segmentation result, an anisotropic localized active contour is employed which defines the local area based on shape prior information. The method was tested on ten CBCT data sets. The results were evaluated by the Dice coefficient, the volumetric overlap error (VOE), precision, recall, and $$F$$ -score and compared with expert manual segmentation and existing methods. The nasal cavity and Paranasal Sinuses were segmented in CBCT images with a median accuracy of 95.72 % [93.82–96.72 interquartile range] by Dice, 8.73 % [6.79–12.20] by VOE, 94.69 % [93.80–94.97] by precision, 97.73 % [92.70–98.79] by recall, and 95.72 % [93.82–96.69] by $$F$$ -score. Automated CBCT segmentation of the airway and Paranasal Sinuses was highly accurate in a test sample of clinical scans. The method may be useful in a variety of clinical, education, and research applications.
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automatic segmentation of the nasal cavity and Paranasal Sinuses from cone beam ct images
2015Co-Authors: Nhat Linh Bui, S H Ong, Kelvin Weng Chiong FoongAbstract:Purpose A patient-specific upper airway model is important for clinical, education, and research applications. Cone-beam computed tomography (CBCT) is used for imaging the upper airway but automatic segmentation is limited by noise and the complex anatomy. A multi-step level set segmentation scheme was developed for CBCT volumetric head scans to create a 3D model of the nasal cavity and Paranasal Sinuses.
Lawrence R Zukerberg - One of the best experts on this subject based on the ideXlab platform.
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solitary fibrous tumor of the nasal cavity and Paranasal Sinuses
1991Co-Authors: Lawrence R Zukerberg, Andrew E Rosenberg, Gregory W Randolph, Ben Z Pilch, Max L GoodmanAbstract:We report two solitary fibrous tumors of the nasal cavity and Paranasal Sinuses that were histologically and immunohistochemically virtually identical to solitary fibrous tumors (fibrous mesotheliomas) of the pleura. One tumor arose in a 48-year-old woman and the other in a 45-year-old woman. Both patients presented with nasal symptoms, and both patients are alive without evidence of disease 6 months and 1 year after excision. The tumors had a disorganized or "patternless" arrangement of spindle cells in a collagenous background and prominent vascular channels of varying size. Immunoperoxidase stains on paraffin sections showed staining of the cells for vimentin only; there was no staining for keratin, S-100 protein, desmin, and actin. Both cases presented some degree of diagnostic difficulty and had to be distinguished from other spindle cell tumors of the nasal cavity and Paranasal Sinuses, such as hemangiopericytoma, angiofibroma, and fibrous histiocytoma.
Nhat Linh Bui - One of the best experts on this subject based on the ideXlab platform.
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automatic segmentation of the nasal cavity and Paranasal Sinuses from cone beam ct images
2015Co-Authors: Nhat Linh Bui, S H Ong, Kelvin Weng Chiong FoongAbstract:A patient-specific upper airway model is important for clinical, education, and research applications. Cone-beam computed tomography (CBCT) is used for imaging the upper airway but automatic segmentation is limited by noise and the complex anatomy. A multi-step level set segmentation scheme was developed for CBCT volumetric head scans to create a 3D model of the nasal cavity and Paranasal Sinuses. Gaussian mixture model thresholding and morphological operators are first employed to automatically locate the region of interest and to initialize the active contour. Second, the active contour driven by the Kullback–Leibler (K–L) divergence energy in a level set framework to segment the upper airway. The K–L divergence asymmetry is used to directly minimize the K–L divergence energy on the probability density function of the image intensity. Finally, to refine the segmentation result, an anisotropic localized active contour is employed which defines the local area based on shape prior information. The method was tested on ten CBCT data sets. The results were evaluated by the Dice coefficient, the volumetric overlap error (VOE), precision, recall, and $$F$$ -score and compared with expert manual segmentation and existing methods. The nasal cavity and Paranasal Sinuses were segmented in CBCT images with a median accuracy of 95.72 % [93.82–96.72 interquartile range] by Dice, 8.73 % [6.79–12.20] by VOE, 94.69 % [93.80–94.97] by precision, 97.73 % [92.70–98.79] by recall, and 95.72 % [93.82–96.69] by $$F$$ -score. Automated CBCT segmentation of the airway and Paranasal Sinuses was highly accurate in a test sample of clinical scans. The method may be useful in a variety of clinical, education, and research applications.
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automatic segmentation of the nasal cavity and Paranasal Sinuses from cone beam ct images
2015Co-Authors: Nhat Linh Bui, S H Ong, Kelvin Weng Chiong FoongAbstract:Purpose A patient-specific upper airway model is important for clinical, education, and research applications. Cone-beam computed tomography (CBCT) is used for imaging the upper airway but automatic segmentation is limited by noise and the complex anatomy. A multi-step level set segmentation scheme was developed for CBCT volumetric head scans to create a 3D model of the nasal cavity and Paranasal Sinuses.