Corina Barbalata | University of Michigan (original) (raw)
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Papers by Corina Barbalata
OCEANS 2021: San Diego – Porto, 2021
—The development of the narrow-band imaging (NBI) has been increasing the interest of medical spe... more —The development of the narrow-band imaging (NBI) has been increasing the interest of medical specialists in the study of laryngeal microvascular network to establish diagnosis without biopsy and pathological examination. A possible solution to this challenging problem is presented in this paper, which proposes an automatic method based on anisotropic filtering and matched filter to extract the lesion area and segment blood vessels. Lesion classification is then performed based on a statistical analysis of the blood vessels' characteristics, such as thickness, tortuosity, and density. Here, the presented algorithm is applied to 50 NBI en-doscopic images of laryngeal diseases and the segmentation and classification accuracies are investigated. The experimental results show the proposed algorithm provides reliable results, reaching an overall classification accuracy rating of 84.3%. This is a highly motivating preliminary result that proves the feasibility of the new method and supports the investment in further research and development to translate this study into clinical practice. Furthermore , to our best knowledge, this is the first time image processing is used to automatically classify laryngeal tumors in endoscopic videos based on tumor vascularization characteristics. Therefore, the introduced system represents an innovation in biomedical and health informatics.
—The development of the narrow-band imaging (NBI) has been increasing the interest of medical spe... more —The development of the narrow-band imaging (NBI) has been increasing the interest of medical specialists in the study of laryngeal microvascular network to establish diagnosis without biopsy and pathological examination. A possible solution to this challenging problem is presented in this paper, which proposes an automatic method based on anisotropic filtering and matched filter to extract the lesion area and segment blood vessels. Lesion classification is then performed based on a statistical analysis of the blood vessels' characteristics, such as thickness, tortuosity, and density. Here, the presented algorithm is applied to 50 NBI en-doscopic images of laryngeal diseases and the segmentation and classification accuracies are investigated. The experimental results show the proposed algorithm provides reliable results, reaching an overall classification accuracy rating of 84.3%. This is a highly motivating preliminary result that proves the feasibility of the new method and supports the investment in further research and development to translate this study into clinical practice. Furthermore , to our best knowledge, this is the first time image processing is used to automatically classify laryngeal tumors in endoscopic videos based on tumor vascularization characteristics. Therefore, the introduced system represents an innovation in biomedical and health informatics.
— This paper introduces an adaptive tuning method for the controllers of a 4 degrees-of-freedom a... more — This paper introduces an adaptive tuning method for the controllers of a 4 degrees-of-freedom autonomous underwater vehicle. The proposed scheme consists of two control loops, one for position control and an inner one for velocity control. The gains of the controller are determined on-line, according to the position/velocity errors. Using the proposed adaptive architecture, the uncertainties in the parameters of the system are addressed and the system is able to operate when hydrodynamic disturbances are present. The complexity of the fixed gain tuning procedure is also greatly decreased for underwater vehicles when the algorithm suggested here is used. Experimental results with the Nessie VII AUV show that the adaptive controller is beneficial for underwater vehicles. Finally it is shown that the current approach reduces the energy consumption of the system.
—This paper presents a study of the interaction effects between a lightweight underwater vehicle ... more —This paper presents a study of the interaction effects between a lightweight underwater vehicle and the attached manipulator. Based on a tree representation of the system, the dynamic and hydrodynamic model of the UVMS is computed and the coupling effects are analysed. Simulations show that having a manipulator with considerable mass compared with the vehicle significantly influences the stability of the system. Gaining a clear understanding of the coupling effects is important for designing the control laws. Moreover, it is possible that incorporating these disturbances in the control methods can improve the performance of the UVMS.
—The first requisite of a robot to succeed in social interactions is accurate human localisation,... more —The first requisite of a robot to succeed in social interactions is accurate human localisation, i.e. subject detection and tracking. Later, it is estimated whether an interaction partner seeks attention, for example by interpreting the position and orientation of the body. In computer vision, these cues usually are obtained in colour images, whose qualities are degraded in ill illuminated social scenes. In these scenarios depth sensors offer a richer representation. Therefore, it is important to combine colour and depth information. The second aspect that plays a fundamental role in the acceptance of social robots is their real-time-ability. Processing colour and depth images is computationally demanding. To overcome this we propose a parallelisation strategy of face detection and tracking based on two different architectures: message passing and shared memory. Our results demonstrate high accuracy in low computational time, processing nine times more number of frames in a parallel implementation. This provides a real-time social robot interaction.
OCEANS 2021: San Diego – Porto, 2021
—The development of the narrow-band imaging (NBI) has been increasing the interest of medical spe... more —The development of the narrow-band imaging (NBI) has been increasing the interest of medical specialists in the study of laryngeal microvascular network to establish diagnosis without biopsy and pathological examination. A possible solution to this challenging problem is presented in this paper, which proposes an automatic method based on anisotropic filtering and matched filter to extract the lesion area and segment blood vessels. Lesion classification is then performed based on a statistical analysis of the blood vessels' characteristics, such as thickness, tortuosity, and density. Here, the presented algorithm is applied to 50 NBI en-doscopic images of laryngeal diseases and the segmentation and classification accuracies are investigated. The experimental results show the proposed algorithm provides reliable results, reaching an overall classification accuracy rating of 84.3%. This is a highly motivating preliminary result that proves the feasibility of the new method and supports the investment in further research and development to translate this study into clinical practice. Furthermore , to our best knowledge, this is the first time image processing is used to automatically classify laryngeal tumors in endoscopic videos based on tumor vascularization characteristics. Therefore, the introduced system represents an innovation in biomedical and health informatics.
—The development of the narrow-band imaging (NBI) has been increasing the interest of medical spe... more —The development of the narrow-band imaging (NBI) has been increasing the interest of medical specialists in the study of laryngeal microvascular network to establish diagnosis without biopsy and pathological examination. A possible solution to this challenging problem is presented in this paper, which proposes an automatic method based on anisotropic filtering and matched filter to extract the lesion area and segment blood vessels. Lesion classification is then performed based on a statistical analysis of the blood vessels' characteristics, such as thickness, tortuosity, and density. Here, the presented algorithm is applied to 50 NBI en-doscopic images of laryngeal diseases and the segmentation and classification accuracies are investigated. The experimental results show the proposed algorithm provides reliable results, reaching an overall classification accuracy rating of 84.3%. This is a highly motivating preliminary result that proves the feasibility of the new method and supports the investment in further research and development to translate this study into clinical practice. Furthermore , to our best knowledge, this is the first time image processing is used to automatically classify laryngeal tumors in endoscopic videos based on tumor vascularization characteristics. Therefore, the introduced system represents an innovation in biomedical and health informatics.
— This paper introduces an adaptive tuning method for the controllers of a 4 degrees-of-freedom a... more — This paper introduces an adaptive tuning method for the controllers of a 4 degrees-of-freedom autonomous underwater vehicle. The proposed scheme consists of two control loops, one for position control and an inner one for velocity control. The gains of the controller are determined on-line, according to the position/velocity errors. Using the proposed adaptive architecture, the uncertainties in the parameters of the system are addressed and the system is able to operate when hydrodynamic disturbances are present. The complexity of the fixed gain tuning procedure is also greatly decreased for underwater vehicles when the algorithm suggested here is used. Experimental results with the Nessie VII AUV show that the adaptive controller is beneficial for underwater vehicles. Finally it is shown that the current approach reduces the energy consumption of the system.
—This paper presents a study of the interaction effects between a lightweight underwater vehicle ... more —This paper presents a study of the interaction effects between a lightweight underwater vehicle and the attached manipulator. Based on a tree representation of the system, the dynamic and hydrodynamic model of the UVMS is computed and the coupling effects are analysed. Simulations show that having a manipulator with considerable mass compared with the vehicle significantly influences the stability of the system. Gaining a clear understanding of the coupling effects is important for designing the control laws. Moreover, it is possible that incorporating these disturbances in the control methods can improve the performance of the UVMS.
—The first requisite of a robot to succeed in social interactions is accurate human localisation,... more —The first requisite of a robot to succeed in social interactions is accurate human localisation, i.e. subject detection and tracking. Later, it is estimated whether an interaction partner seeks attention, for example by interpreting the position and orientation of the body. In computer vision, these cues usually are obtained in colour images, whose qualities are degraded in ill illuminated social scenes. In these scenarios depth sensors offer a richer representation. Therefore, it is important to combine colour and depth information. The second aspect that plays a fundamental role in the acceptance of social robots is their real-time-ability. Processing colour and depth images is computationally demanding. To overcome this we propose a parallelisation strategy of face detection and tracking based on two different architectures: message passing and shared memory. Our results demonstrate high accuracy in low computational time, processing nine times more number of frames in a parallel implementation. This provides a real-time social robot interaction.