Papers by Vijayalaxmi Mekali
Among five main type of cancer lung cancer is one of causing health hazards in both men and women... more Among five main type of cancer lung cancer is one of causing health hazards in both men and women all over the world. Advanced techniques of Computed Tomography and medical images play an important role in clinically detection of lung cancer tumors in all TNM stages. Efficient Computer Aided Detection (CADe) systems help the radiologist in early detection and diagnosis of lung cancer. The objective of this paper is to develop efficient CADe system using iterative thresholding method for segmentation and freeman chain code algorithm to repair the boundary of separated lung regions. Region growing algorithm is used to extract tumor region from lung regions. Tumor shape, size, whole tumor volume and solid part tumor volume are important factors. These factors are computed in this research work to determine prognosis of tumor. Developed CADe system is evaluated using CT thoracic lung images from Lung Image Database Consortium and Reference Image (LIDC) and Reference Image Database to Evaluate Response (RIDER).
Mortality rate of lung cancer is increasing very day all over the world. Early stage lung nodules... more Mortality rate of lung cancer is increasing very day all over the world. Early stage lung nodules detection and proper treatment is solution to reduce the deaths due to lung cancer. In this research work proposed integrated CADe/CADx system segments and classifies lung nodules into benign or malignant. CADe phase segments Well Circumscribed Nodules (WCN), Juxta Vascular Nodules (JVN) and Juxta Pleural Nodules (JPN) of different size in diameter. This part uses algorithms proposed in our previous WCN, JVN and JPN lung nodules segmentation work. CADx performance classification of segmented WCNs, JVNs and JPNs nodules into benign or malignant. In first part of CADx system hybrid features of segmented lung nodules are extracted and features dimension vector is reduced with Linear Discrimination Analysis. Finally, Probabilistic Neural Network uses reduced hybrid features of segmented nodules to classify segmented nodules as benign or malignant. Proposed integrated system achieved high cl...
The main aim of this paper is to remove difficulties faced by completely paralyzed patients suffe... more The main aim of this paper is to remove difficulties faced by completely paralyzed patients suffering from Motor Neuron Disease (MND) and Locked-in Syndrome (LIS). Paralyzed patients cannot communicate as they suffer from speech disorder, the only part that remains unaffected is eyes and communication is possible only through their eye movements. The proposed system is based on a Video-Oculography (VOG) technique which is efficient when compared to other existing techniques. In this system methods like face detection, eye blink detection and image processing are employed to communicate the needs of patients to the concerned person through a text and an audio message using twilio application.
Proceedings of the International Conference on ISMAC in Computational Vision and Bio-Engineering 2018 (ISMAC-CVB), 2019
Lung cancer health care community depends on lung cancer Computer Aided Detection system to draw ... more Lung cancer health care community depends on lung cancer Computer Aided Detection system to draw useful lung cancer details from Computed Tomography lung images. Nodules growth rate indicates the severity of the disease, which can be periodically radiologist analyzed by nodule segmentation and classification. Main challenges in analyzing nodules growth rate are lung nodules of different type requires special methods for segmentation, their irregular shape, and boundary. In this paper, automatic three-phase framework for lung nodules and nodules of ground glass opacity detection followed by classification is proposed. In this work, nodule segmentation framework uses proposed automatic region growing algorithm that selects set of black pixels as seed points automatically from output binary image for lung parenchyma segmentation followed by artifacts removal to reduce disease search space. Nodules are segmented based on nodule candidates center pixels identification and intensity featu...
Early detection of all kinds of lung nodules with different characters in patient’s medical modal... more Early detection of all kinds of lung nodules with different characters in patient’s medical modality images is the best acceptable remedy to save the life of lung cancer sufferers. Even though day by day the prominence of Computer-Aided Detection/Diagnosis (CADe/x) systems have been increasing as a part of medical routine in detection of different types of lung nodules, but detection rate performance depends on accuracy of lung parenchyma and nodule segmentation procedures. Segmentation of Juxta-Vascular nodules attached very complex. In this paper new fully automated CAD system is developed to detect and classify Juxta-Vascular nodules. In proposed methodology, lung parenchyma is segmented using iterative thresholding algorithm and lung nodules are segmented using proposed modified region growing algorithm. Since in vascular nodules, separation of blood vessel from nodule is difficult as intensity feature of attached blood vessel and nodule is same. Two new methods nodule segmentat...
International Journal of Healthcare Information Systems and Informatics
Early detection of all types of lung nodules with different characters in medical modality images... more Early detection of all types of lung nodules with different characters in medical modality images using computer-aided detection is the best acceptable remedy to save the lives of lung cancer sufferers. But accuracy of different types of nodule detection rates is based on chosen segmented procedures for parenchyma and nodules. Separation of pleural from juxta-pleural nodules (JPNs) is difficult as intensity of pleural and attached nodule is similar. This research paper proposes a fully automated method to detect and segment JPNs. In the proposed method, lung parenchyma is segmented using iterative thresholding algorithm. To improve the nodules detection rate separation of connected lung lobes, an algorithm is proposed to separate connected left and right lung lobes. The new method segments JPNs based on lung boundary pixels extraction, concave points extraction, and separation of attached pleural from nodule. Validation of the proposed method was performed on LIDC-CT images. The exp...
International Journal of Engineering Applied Sciences and Technology
The main aim of this paper is to remove difficulties faced by completely paralyzed patients suffe... more The main aim of this paper is to remove difficulties faced by completely paralyzed patients suffering from Motor Neuron Disease MND) and Locked-in Syndrome (LIS). Paralyzed patients cannot communicate as they suffer from speech disorder, the only part that remains unaffected is eyes and communication is possible only through their eye movements. The proposed system is based on a Video-Oculography (VOG) technique which is efficient when compared to other existing techniques. In this system methods like face detection, eye blink detection and image processing are employed to communicate the needs of patients to the concerned person through a text and an audio message.
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Papers by Vijayalaxmi Mekali