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This paper presents image and video analysis based schemes to automate the process of adductors angle measurement which is carried out on infants as a part of Hammersmith Infant Neurological Examination (HINE). Image segmentation, thinning and feature point based object tracking are used for automating the analysis. Segmentation outputs are processed with a novel region merging algorithm. It is found...
Ventriculomegaly is one of the most sensitive markers for abnormal development of the fetal central nervous system. So assessment of the size of lateral ventricles has become an important part of routine neurological assessment in neonates. We have proposed a method for measuring the width of lateral ventricles in term and preterm neonates from the coronal view of their brain ultrasound images. Based...
The tomato (Lycopersicon esculentum) is an herbaceous, usually sprawling plant which belong to Solanaceae or nightshade family. Genetic evidence shows that the progenitors of tomatoes were herbaceous green plants with small green fruit. There are a great many (around 7500) tomato varieties grown for various purposes. Their identifications had been studied using various laboratory methods. The morphological...
Image clustering and categorization is a means for high-level description of image content. In the field of content-based image retrieval (CBIR), the analysis of gray scale images has got very much importance because of its immense application starting from satellite images to medical images. But the analysis of an image with such number of gray shades becomes very complex, so, for simplicity we cluster...
A novel algorithm is introduced to track multiple circular objects present in video using Helmholtz perception principle. First, segmentation of circular objects in the video frame is performed using the perception principle and then same perception principle is applied to track the circular objects. For each circular object present in video, we have taken an assessment of the meaningfulness of the...
Visualization of the patient-specific fractured bone in three dimensions (3D) plays an important role in image guided orthopedic surgery. Existing research often focuses on intra-operative registration of the patientspsila anatomy with pre-operatively obtained 3D volumetric data (e.g. CT scans) utilizing fiduciary markers. This expensive and invasive approach is not routinely available for diagnostics,...
Three dimensional (3D) visualization of anatomy plays an important role in image guided orthopedic surgery and ultimately motivates minimally invasive procedures. However, direct 3D imaging modalities such as computed tomography (CT) are restricted to a minority of complex orthopedic procedures. Thus the diagnostics and planning of many interventions still rely on two dimensional (2D) radiographic...
We propose algorithms to extract groups of meaningful image level lines using Helmholtz perception principle. In this paper, the meaningfulness refers to the segmentation of circular and rectangular shapes in an image. We propose an objective assessment of meaningfulness of an image level line when the level line takes the shape of circle or rectangular segment. We have shown that a logical threshold...
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