Sanjay Talbar

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This paper presents a novel approach for Automatic Image Stitching of spinal cord MRI Images by exploring the effectiveness of Scale Invariant Feature Transform(SIFT) for feature matching. Because of limitations of MRI machine, when a patient undergoes scan of spinal cord, three different images of cervical, thoracic and lumbar parts with some vertebral(More)
There is an increase in need of video surveillance applications. Intelligent video surveillance (IVS) includes public safety and security applications, including authenticity control, crowd flow direction and crowd analysis, human behaviour detection and analysis etc. The critical part of IVS system is proper foreground estimation using background(More)
Obtaining accurate and automated lung field segmentation is a challenging step in the development of Computer-Aided Diagnosis (CAD) system. In this paper, fully automatic lung field segmentation is proposed. Initially, novel features are extracted by considering spatial interaction of the neighbouring pixels. Then constrained non-negative matrix(More)
Object recognition and tracking are important and challenging tasks in many computer vision applications. Difficulties in object recognition arise due to occlusion, clutter and geometric transformations present between pair of images or frames. Challenges in tracking include ability to deal with abrupt object motion, nonrigid object structures, change in(More)
Knee Osteoarthritis (OA) is a most prevalent joint disease that can be diagnosed by measuring physiology and morphology of knee joint organs using Magnetic Resonance Imaging (MRI). Measurement of morphological changes in the knee joint organs is a highly challenging task as it requires interpretation and analysis from MR images acquired using different MR(More)
Over a decade, automatic segmentation of brain tumor in Magnetic Resonance Imaging (MRI) is a challenging task for researchers. Large amount of data is produced by MRI and the task of marking the tumor slice by slice is a very tedious and time consuming process for radiologists and hence accurate and reliable segmentation methods are gaining more attention(More)
Knee osteoarthritis (OA) progression can be monitored by measuring changes in the subchondral bone structure such as area and shape from MR images as an imaging biomarker. However, measurements of these minute changes are highly dependent on the accurate segmentation of bone tissue from MR images and it is challenging task due to the complex tissue(More)
Most medical images suffer from inadequate contrast and brightness, which leads to blurred or weak edges (low contrast) between adjacent tissues resulting in poor segmentation and errors in classification of tissues. Thus, contrast enhancement to improve visual information is extremely important in the development of computational approaches for obtaining(More)
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