Classification of vessels as arteries verses veins using hybrid features for diagnosis of hypertensive retinopathy

2016 ◽  
Author(s):  
Samra Irshad ◽  
Muhammad Ahmad ◽  
M. Usman Akram ◽  
Asad Waqar Malik ◽  
Sarmad Abbas
Keyword(s):  
Hypertensive Retinopathy ◽  
Hybrid Features

scholarly journals The Classification of Hypertensive Retinopathy using Convolutional Neural Network

2017 ◽  
Vol 116 ◽  
pp. 166-173 ◽  
Author(s):  
Bambang Krismono Triwijoyo ◽  
Widodo Budiharto ◽  
Edi Abdurachman
Keyword(s):  
Neural Network ◽  
Convolutional Neural Network ◽  
Hypertensive Retinopathy

scholarly journals Identification of European and Japanese Larch and Their Interspecific Hybrid with Morphological Markers: Application to Young Seedlings

2006 ◽  
Vol 55 (1-6) ◽  
pp. 123-134 ◽  
Author(s):  
L. E. Pâques ◽  
G. Philippe ◽  
D. Prat
Keyword(s):  
Molecular Markers ◽  
Parental Species ◽  
Correct Classification ◽  
Morphological Markers ◽  
Hybrid Features ◽  
Pure Species ◽  
Seed Orchards ◽  
Linear Discriminant ◽  
Non Destructive

Abstract Open-pollinated hybridisation seed orchards of European and Japanese larches produce mixed progenies combining a highly variable proportion of hybrids along with pure parental species. For several reasons, it is desirable to identify and to sort out hybrids from pure species at the seedling stage. Taxa identification of 1-2 yr-old seedlings was attempted using non-destructive assessment of several traits, including morphology, phenology, growth and architecture parameters. Two sets of progenies originating from 10 open-pollinated hybridisation seed orchards were used, relying in a first step on taxa identification of individual seedlings with diagnostic molecular markers. Based on 21 traits assessed, some clear trends in pure species and hybrid features were apparent but due to the large and overlapping ranges of taxa characteristics, no single parameter allowed unambiguous identification of taxa. Combination of traits through linear discriminant analysis made possible correct classification of 90.2% to 98.6% of individuals depending on the orchard although there were a few problematic orchards. Two traits appeared particularly pertinent for discriminating young plants taxa, namely 1st-yr leaf retention (marcescence) and the bark colour of 2nd-year shoot increments. Results were corroborated using progenies from several orchards and over two experimental periods.

Ensemble classification of colon biopsy images based on information rich hybrid features

2014 ◽  
Vol 47 ◽  
pp. 76-92 ◽  
Author(s):  
Saima Rathore ◽  
Mutawarra Hussain ◽  
Muhammad Aksam Iftikhar ◽  
Abdul Jalil
Keyword(s):  
Ensemble Classification ◽  
Hybrid Features ◽  
Colon Biopsy

scholarly journals Detection and Classification of Early Stage Lesions in Diabetic Retinopathy using Color Fundus Images

2019 ◽  
Vol 8 (3) ◽  
pp. 4476-4480
Keyword(s):  
Diabetic Retinopathy ◽  
Clustering Algorithm ◽  
Early Stage ◽  
High Sensitivity ◽  
Morphological Operations ◽  
Hybrid Features ◽  
Speeded Up Robust Features ◽  
Fuzzy C Means Clustering ◽  
Color Fundus Images

Detection of lesions and classification of Diabetic Retinopathy (DR) play an important role in day-to-day life. In this proposed system, colour fundus image is pre-processed using morphological operations to recover from noises and it is converted into HSV colorspace. Fuzzy C-Means Clustering algorithm (FCMC) is used for segmenting the early stage lesions such as Microaneurysms (Ma), Haemorrhages (HE) and Exudates. Hybrid features such as colour correlogram and speeded up robust features (surf) are extracted to train the classifier. Cascaded Rotation Forest (CRF) classifier is used for classification of diabetic retinopathy. The proposed system increases the accuracy of detection and it has got high sensitivity.

scholarly journals The history of research of the ophthalmic aspects of hypertension

2021 ◽  
Vol 9 (1) ◽  
pp. 14-18
Author(s):  
Aleksandra Krasińska ◽  
Agata Brązert ◽  
Jarosław Kocięcki
Keyword(s):  
Diagnostic Methods ◽  
Hypertensive Retinopathy ◽  
Cotton Wool Spots ◽  
Microvascular Changes ◽  
History Of Research ◽  
Organ Systems ◽  
History Of ◽  
Funduscopic Examination ◽  
Retinal Exudates

Abstract The awareness of the widespread influence of hypertension on various organ systems is ever increasing. Changes associated with this disease can be observed in the heart, brain, kidneys, but also the organ of vision. These usual microvascular changes are defined as hypertensive retinopathy. During a funduscopic examination, abnormalities such as narrowing of arterioles, symptoms of arteriole and vein intersection, cotton wool spots, intra-retinal exudates, retinal haemorrhages, and in severe cases even swelling of the optic disc and macula. This review presents an overview of the changes at the fundus of the eye that may occur in patients with hypertension, as well as problems with the classification of hypertensive retinopathy over the years, and the development of diagnostic methods in ophthalmology and fundoscopic imaging. Running title: The history of hypertensive retinopathy research

scholarly journals Classification the Mammograms Based on Hybrid Features Extraction Techniques Using Multilayer Perceptron Classifier

2020 ◽  
Vol 31 (4) ◽  
pp. 72
Author(s):  
Hayder Adnan AlSudani ◽  
Enaas M. Hussain ◽  
Enam A. Khalil
Keyword(s):  
Multilayer Perceptron ◽  
Region Of Interest ◽  
Texture Features ◽  
Local Binary Patterns ◽  
Features Selection ◽  
Hybrid Features ◽  
Reliable Assessment ◽  
Occurrence Matrix ◽  
Two Stages

Cancer of the breast is one of the world's most prevalent causes of death for women. Early and efficient identification is important for can care choices and reducing mortality. Mammography is the most effective early breast cancer detection process. Radiologists cannot however make a detailed and reliable assessment of mammograms due to fatigue or poor image quality. The main aim of this work is to establish a new approach to help radiologists identify anomalies and improve diagnostic precision. The proposed method has been applied through the implementation of preprocessing then segmentation of the images to get the region of interest that was used to find a texture features that were calculated based on first Order (statistical features), Gray-Level Co-Occurrence Matrix (GLCM), and Local Binary Patterns LBP (LBP). In the features selection phase mutual information (MI) algorithm is applied to choose from the extracted features collection suitable features. Finally, Multilayer Perceptron has been applied in two stages to classify the mammography images first to normal or abnormal, and secondly, classification of abnormal images into benign or malignant images. This method was implemented and gave an accuracy of 92.91 % for the first level and 93.15% for the second level classification.

Classification of benign and malignant lung nodules from CT images based on hybrid features

2019 ◽  
Vol 64 (12) ◽  
pp. 125011 ◽  
Author(s):  
Guobin Zhang ◽  
Zhiyong Yang ◽  
Li Gong ◽  
Shan Jiang ◽  
Lu Wang
Keyword(s):  
Ct Images ◽  
Lung Nodules ◽  
Hybrid Features
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