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Indirect immunofluorescence (IIF) imaging is a method used for detection of antinuclear auto-antibodies (ANA) for the diagnosis of autoimmune diseases. We present a feature extraction and classification scheme to classify the fluorescence staining patterns of HEp-2 cells in IIF images. We propose a set of complementary features that are sensitive to staining pattern variations among classes. Our feature...
Morphological attribute filters modify images based on properties or attributes of connected components. Usually, attribute filtering is based on a scalar property which has relatively little discriminating power. Vector-attribute filtering allow better description of characteristic features for 2D images. In this paper, we extend vector attribute filtering by incorporating unsupervised pattern recognition,...
The presence of involuntary muscle twitches is a diagnostic indicator of neurodegenerative diseases, such as motor neurone disease (MND), but current methods of twitch detection are invasive and pose potential risks to patients. We present a method by which standard B-mode ultrasound can be used to automatically identify muscle twitches similar to those found in patients with MND. The results of initial...
Accurate vessel segmentation is the first step in retinal image analysis for medical diagnosis. In this paper we propose a novel method to segment vessel network in fundus image. Vessel centerlines are first extracted by using a set of directional line detectors. Next an Iterative Geodesic Time Transform (ItGTT) is designed to segment the entire vessel network. The idea of the ItGTT is to use centerline...
We introduce a semi-automatic tracking method that can be utilized for the analysis of facial markers in the medical condition of facial palsy. Tracking of markers will help medical physicians in evaluating this medical condition quantitatively. We use particle filtering to track markers towards measuring distances needed to evaluate the degree of facial palsy. We show that by employing tracking methods,...
Breast cancer is the most commonly diagnosed form of cancer in women. Thermography, which uses cameras with sensitivities in the thermal infrared, has been shown to provide an interesting modality for detecting breast cancer as it is able to detect small tumors and hence can lead to earlier diagnosis. In this paper, we present an effective approach to breast thermogram analysis that utilises features...
Optic cup is the primary image indicator clinically used for identifying glaucoma. To automatically localize the optic cup in fundus images, an effective and efficient superpixel classification based approach is proposed in this work, which maintains both advantages of existing pixel and window based approaches. This method provides three major contributions. First, it proposes processing of the fundus...
Although atlas-based methods simplify the segmentation process by making it more automated, such methods are often very sensitive to the computationally expensive image registration step. Also, existing methods based on a parametric deformation model may fail when the transformation between the atlas and target images can not be properly described with this model. This paper presents a novel and efficient...
As a new biometric for person authentication, hand-dorsa vein has attracted increasing attention in recent years. This paper proposes a novel approach for hand-dorsa vein recognition, which makes use of multi-level keypoint detection and SIFT feature based local matching. In order to overcome the difficulty in finding local features on NIR images of hand dorsa, a multi-level keypoint detection approach,...
This paper presents a new approach to image-thresholding-based segmentation. It considerably improves existing methods by efficiently modeling non-Gaussian and multi-modal class-conditional distributions. The proposed approach seamlessly: 1) extends the Otsu's method to arbitrary numbers of thresholds and 2) extends the Kittler and Illingworth minimum error thresholding to non-Gaussian and multi-modal...
With the increase in age and diabetes-related eye diseases, there is a rising demand for systems which can efficiently screen and locate abnormalities in retinal images. In this paper, we propose a framework that utilizes a variant of the Maximally Stable Extremal Region method, termed C-MSER, to systematically detect various retinopathy pathologies such as microaneurysms, haemorrhages, hard exudates...
Volume registration is an essential technology for comparing medical volume data acquired in different days and for combining different types of volume data from various imaging devices. For accurate comparison, it is necessary to correct non-rigid deformation between volume data, since the complex deformation between medical volume data is observed even if they are taken from the same regions of...
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