17 research outputs found
Predicting the severity of blood vessel tissue damage in retinal images using support vector machine classifier
No full textA Survey on Deep Learning Architectures and Frameworks for Cancer Detection in Medical Images Analysis
No full textThe various hurdles in machine learning are beaten by deep learning techniques and then the deep learning has gradually become preeminent in artificial intelligence. Deep learning uses neural networks to kindle decisions like humans. Deep learning flourished as an energetic approach and clarity marked its success in various domains. The study includes some dominant deep learning algorithms such as convolution neural network, fully convolutional network, autoencoder, and deep belief network to analyze the medical image and to detect and diagnose of cancer at an early stage. As early as the detection of cancer than to treat the disease is uncomplicated. Early diagnosis was particularly relevant for some cancers such as breast, skin, colon, and rectum, which prohibit the chance to grow and spread. Deep learning contributes to enhanced performance and better prediction in detection of cancer with medical images. The paper presents the study of a few deep learning software frameworks such as tensor flow, theano, caffe, torch, and keras. Tensor Flow provides excellent functionality for deep learning. Keras is a high-level neural network API that operates above on tensor flow or theano. The survey winds up by presenting several future avenues and open challenges that should be addressed by the researcher in the futur
Biomarkers of angiogenesis and their role in the development of VEGF inhibitors
No full textVascular endothelial growth factor (VEGF) has been confirmed as an important therapeutic target in randomised clinical trials in multiple disease settings. However, the extent to which individual patients benefit from VEGF inhibitors is unclear. If we are to optimise the use of these drugs or develop combination regimens that build on this efficacy, it is critical to identify those patients who are likely to benefit, particularly as these agents can be toxic and are expensive. To this end, biomarkers have been evaluated in tissue, in circulation and by imaging. Consistent drug-induced increases in plasma VEGF-A and blood pressure, as well as reductions in soluble VEGF-R2 and dynamic contrast-enhanced MRI parameters have been reported. In some clinical trials, biomarker changes were statistically significant and associated with clinical end points, but there is considerable heterogeneity between studies that are to some extent attributable to methodological issues. On the basis of observations with these biomarkers, it is now appropriate to conduct detailed prospective studies to define a suite of predictive, pharmacodynamic and surrogate response biomarkers that identify those patients most likely to benefit from and monitor their response to this novel class of drugs. © 2010 Cancer Research UK All rights reserved
Intellectually combined face recognition using curvelet based principle component analysis for feature extraction and Bayesian Classifier
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A Novel Ear Recognition Process Using Appearance Shape Model, Fisher Linear Discriminant Analysis and Contourlet Transform
No full textAbstractBiometric authentication using ear images becoming popular nowadays in the field of security surveillance to identify a person. In this paper image processing techniques are used to study about the characteristics of several databases Ear images and to extract the features and data's from that Ear images. Ear is a stable biometric its appearance will not change even for long years. This paper explained about Contourlet transform and Appearance shape model (ASM) for feature extraction and, Fisher linear discriminant analysis (FLDA) is done for classification, ear matching. Here the feature extraction was done by both the Transform and Appearance shape model methods, So that the feature extraction result must be good. The proposed method has been evaluated on IIT Delhi Ear database of 50 Ear images from 10 persons and also tested on our own ear databases that are collected using webcam. The experimental results indicate that contourlet transform improves the overall performance when compared to Principal component analysis. The comparisons between the two feature extraction methods were done and its results were shown
Multimodal Biometric Authentication System Based on Score-Level Fusion of Palmprint and Finger Vein
No full textIntense blooms of Trichodesmium erythraeum (Cyanophyta) in the open waters along east coast of India
No full textTwo blooms of Trichodesmium erythraeum were observed during April 2001, in the open waters of Bay of Bengal and this is the first report from this region. The locations of the bloom were off Karaikkal (10°58′N, 81°50′E) and off south of Calcutta (19° 44′N, 89° 04′), both along east coast of India. Nutrients (nitrate, phosphate, silicate) concentration in the upper 30 m of the water column showed very low values. High-integrated primary production (Bloom 1-2160 mgC m -2 d -1 , Bloom 2-1740 mgC m -2 d -1 ) was obtained in these regions, which indicated the enhancement of primary production in the earlier stages of the bloom. Very low NO 3 -N concentrations, brownish yellow bloom colour, undisturbed patches and high primary production strongly suggested that the blooms were in the growth phase. Low mesozooplankton biomass was found in both locations and was dominated by copepods followed by chaetognaths.
