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Recently, in vivo visualization of the cochlea and the smaller structures inside of it has been achieved by optical coherence tomography (OCT). This makes it possible to use OCT imaging for diagnosis of diseases such as Meniere's disease through measuring the degree of endolymphatic hydrops. To this end, we present a novel method for 3D segmentation of these cochlear OCT images that is based on superpixels...
Optical Coherence Tomography (OCT) has emerged as a major diagnostic modality for retinal imaging. Although OCT generates gross volumetric data, manual analysis of the images for locating or quantifying retinal cysts is a time consuming process. Recently semi- and fully-automatic methods for locating and segmenting retinal cysts have been proposed in the literature. Our paper proposes a fully automatic...
A new algorithm for apple disease image segmentation is proposed. A fuzzy factor for weighted balance is introduced in the algorithm to describe the coefficient of spatial constraints between pixels in neighborhood. For enhancing the integrality of neighbor information, the space distance constraints and the spatial gray constraints are considered. The fuzzy factor in the neighborhood is used to keep...
The patterns of Human Epithelial type 2 (HEp-2) cell provide useful information for the diagnosis of systemic autoimmune diseases. However, the recognition of cell patterns requires manual annotation by experienced physicians, which is subject to inter-observer variability. Therefore, an automatic diagnosis system is desirable. As the crucial pre-processing step for cell pattern recognition, the performance...
In this work, the core objective is to implement an automatic and reliable system for the classification of plants into two plant categories named as monocotyledonous and dicotyledonous using the microscopic images of plant stem cross sections. The system can be used for the classification of plants when a large number of new plant species are discovered and it can be applied in plant disease detection...
The measure of blood cells are more important for the doctor to diagnose various diseases such as anaemia, leukaemia etc. Similarly observation and classification of these cells grant for the estimation and detecting of a vast number of sickness. By evaluating white blood cells (WBCs) allows the leukaemia detection (Acute Lympho blastic leukaemia (ALL), Acute Myloid leukaemia),be cancer which affected...
About 3.2 million people suffer from sickle-cell disease. Aim of this paper is to detect sickle cell anaemia and thalassaemia. The proposed method involves acquisition of the thin blood smear microscopic images, pre-processing by applying median filter, segmentation of overlapping erythrocytes using marker-controlled watershed segmentation, applying morphological operations to enhance the image, extraction...
Computer aided diagnosis (CAD) systems are important in obtaining precision medicine and patient driven solutions for various diseases. One of the main brain tumor is the Glioblastoma multiforme (GBM) and histopathological tissue images can provide unique insights into identifying and grading disease stages. In this work, we consider feature extraction and disease stage classification for brain tumor...
A detecting way based on Android platform was proposed in order to detect greenhouse tomato disease degree in real time. This way employed the camera in mobile phone to acquire tomato disease leaf image in the greenhouse. Firstly, the detection system was built by the Eclipse based on the Android development environment. The iterative threshold segmentation algorithm was used to separate the tomato...
Coronary artery diseases are the most common type of heart disease. Early detection and quantification of coronary plaques is therefore of high interest. CTA has rapidly emerged, and is nowadays widely used in clinical practice. A calcification detection and quantification method is proposed, which can detect the calcium plaque and quantify the stenosis of coronary artery in CT images. Firstly, the...
Agricultural Images are defined for different fruits, crops, vegetables and flowers to identify the agricultural product type or the associated disease identification. These diseases are specific to the product component which can be leaf, root, seed etc. This automation is helpful to provide the identification of disease from remote lab. This paper is defined specifically for leaf disease identification...
Brain magnetic resonance imaging (MRI) in patients with Multiple Sclerosis (MS) shows regions of signal abnormalities, named plaques or lesions. The spatial lesion distribution plays a major role for MS diagnosis. In this paper we present a 3D MS-lesion segmentation method based on an adaptive geometric brain model. We model the topological properties of the lesions and brain tissues in order to constrain...
The emergence and development of plant diseases and pest outbreaks have become more common nowadays due to the unsettled climate and environmental conditions. Actions controlling diseases or remedial measures can be undertaken if the symptoms are identified at an early stage. This would help the farmer in detecting and controlling plant diseases, thereby controlling the financial losses. We present...
Grape constitutes one of the most widely grown fruit crops in the India. Productivity of grape decreases due to infections caused by various types of diseases on its fruit, stem and leaf. Leaf diseases are mainly caused by bacteria, fungi, virus etc. Diseases are a major factor limiting fruit production and diseases are often difficult to control. Without accurate disease diagnosis, proper control...
Multiple sclerosis (MS) is a disease of the central nervous system (CNS), it is inflammation or decay in a myelin's substance (Demyelination). The causes of the disease is unknown yet, but it is believed to be caused by a combination of many genetic and environmental factors including: geographical distribution (i e less spread closer to the equator), and hereditary reasons. Currently, the diagnosis...
The disease Glaucoma is detected whenever there is change in the retinal inside eye structure, which is the change in the characteristics of the cup and disc area of nerve head and it is also called as undying loss of the vision capacity. In this model, Advance thresholding algorithm is used for cup and disc segmentation. This algorithm is based on spatial variations in the illumination. This system...
With the Agriculture Sector being the backbone of not only a large number of industries but also society as a whole, there is a rising need to grow good quality crops which in turn will give a high yield. For this to happen, it is crucial to monitor the crops throughout their growth period. In this paper, Image processing is used to detect and classify sunflower crop diseases based on the image of...
The applications based on image processing for plant disease recognition and classification is the wide area of research these days. These applications are useful for timely recognition of plant disease. The disease like fungal, bacterial and virus are the destructive disease for any plant. In the study, five types of tomato diseases i.e. tomato late blight, Septoria spot, bacterial spot, bacterial...
Nowadays, abroad trade has expanded definitely in numerous nations. Plenty fruit products are foreign from alternate countries, for example, oranges, apples and so forth. Manual distinguishing proof of infected fruit is extremely tedious. The utilization of image processing procedures is of outstanding implication for the analysis of agro based applications. In any case, detection of infections in...
The Liver is a largest gland in the body. Distinct diseases affected on the liver. Liver diseases is one of the most serious health problem worldwide. For detecting the liver diseases the Segmentation Technique is essential. Segmentation is used for the classification of liver diseases. The liver diseases are focal or diffused is easily understood by the physician using segmentation. We use CT scan...
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