H. K. Sardana

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Cephalometric analysis has an important role in diagnosis and treatment planning for malocclusions. Most analysis steps are computable and underlying structure may be generated provided landmarks are correctly localized. Due to the complexity of human anatomy sensed in a cephalometric x-ray, the landmarks are localized by human experts. In the last few(More)
Anatomical structure tracing on cephalograms is a significant way to obtain cephalometric analysis. Cephalometric analysis is divided in two categories, manual and automatic approaches. The manual approach is limited in accuracy and repeatability due to differences in inter- and intra-personal marking. In this paper, we have attempted to develop and test a(More)
Hybrid multi-resolution target detection methodology in infrared imagery. Synergic fusion of frame difference background subtraction, FastICA and optical flow. Validation of the methodology using benchmark and experimentally generated data. Quantitative assessment of accuracy in target detection using F-measure. Keywords: Moving target detection Thermal(More)
Cancer is one of the most serious health problems in the world. Lung Computer-Aided Diagnosis (CAD) is a potential method to accomplish a range of quantitative tasks such as early cancer and disease detection, analysis of disease progression. For identifying the lung diseases, computed tomography (CT) scan of the thorax is widely applied in diagnose. DICOM(More)
This paper involves the analysis and experimentation of chest CT scan data for the detection and diagnosis of lung cancer. In lung cancer computer-aided diagnosis (CAD) systems, having an accurate ground truth is critical and time consuming. The contribution of this work include the development of lung nodule database with proven pathology using content(More)
— In this paper, we present a novel approach to find and select texture features of solitary pulmonary nodules (SPNs) detected by computed tomography (CT) and evaluate the performance of grafted decision tree based classifier in differentiating benign from malignant as well as from metastasis SPNs. We compared the results of smallest as well as largest(More)
— This paper presents a novel framework for combining well known shape, texture, size and resolution informatics descriptor of solitary pulmonary nodules (SPNs) detected using CT scan. The proposed methodology evaluates the performance of classifier in differentiating benign, malignant as well as metastasis SPNs with 246 chests CT scan of patients. Both(More)
In this research work a seismic classification system is designed to distinguish between tracked and wheeled vehicle classes. Owing to the extreme non-stationary nature of seismic signals, choosing robust features is an important aspect for the purpose of classification. To obtain a varied feature set different signal processing techniques namely Fast(More)
In lung cancer computer-aided diagnosis (CAD) systems, having an accurate ground truth is critical and time consuming. In this study, we have explored Lung Image Database Consortium (LIDC) database containing pulmonary computed tomography (CT) scans, and we developed content-based image retrieval (CBIR) approach to exploit the limited amount of(More)