Journal ArticleDOI
Breast tumor classification in ultrasound images using texture analysis and super-resolution methods
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TLDR
It is shown that the super-resolution-based approach improves the performance of the evaluated texture methods and thus outperforms the state of the art in benign/malignant tumor classification.About:
This article is published in Engineering Applications of Artificial Intelligence.The article was published on 2017-03-01. It has received 89 citations till now. The article focuses on the topics: Local binary patterns & Phase congruency.read more
Citations
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Book ChapterDOI
Amniotic Fluids Classification Using Combination of Rules-Based and Random Forest Algorithm
TL;DR: In this paper, the authors proposed a model for the classification of amniotic fluid by combining the rule-based of the Single Deep Pocket (SDP) method and the Random Forest algorithm, which showed an average increase in accuracy performance of 9.12%, precision of 14.92%, and recall of 0.51%.
Journal ArticleDOI
A novel incomplete sparse least square optimized regression model for abdominal mass detection in ultrasound images
TL;DR: This paper intends to propose a novel model for abdominal masses detection with US images, where the coefficient matrix is optimally tuned using a new hybrid Lion and Whale Optimization algorithm.
Journal ArticleDOI
Pre-Trained Deep Neural Network-Based Computer-Aided Breast Tumor Diagnosis Using ROI Structures
TL;DR: In this paper , a novel ensemble pre-trained DNN-based CABTD method using global and local-ROI-structures of B-mode ultrasound images was proposed.
Journal ArticleDOI
Unsupervised Mitral Valve Tracking for Disease Detection in Echocardiogram Videos
TL;DR: A novel algorithmic scheme is developed that processes echocardiogram videos, and tracks the movement of the mitral valve leaflets, and thereby estimates whether the movement is symptomatic of a healthy or diseased heart.
Proceedings ArticleDOI
Hybrid Regional Feature Cutting Network for Thyroid Ultrasound Images Classification
TL;DR: This paper proposes hybrid cutting network (HCN) based on regional feature cutting method for feature extraction and classification of thyroid ultrasound images based on N-first voting method to construct a hybrid classification voting network with three branches for final classification prediction.
References
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Journal ArticleDOI
Random Forests
TL;DR: Internal estimates monitor error, strength, and correlation and these are used to show the response to increasing the number of features used in the forest, and are also applicable to regression.
Proceedings ArticleDOI
Histograms of oriented gradients for human detection
Navneet Dalal,Bill Triggs +1 more
TL;DR: It is shown experimentally that grids of histograms of oriented gradient (HOG) descriptors significantly outperform existing feature sets for human detection, and the influence of each stage of the computation on performance is studied.
Journal ArticleDOI
Textural Features for Image Classification
TL;DR: These results indicate that the easily computable textural features based on gray-tone spatial dependancies probably have a general applicability for a wide variety of image-classification applications.
Journal ArticleDOI
Multiresolution gray-scale and rotation invariant texture classification with local binary patterns
TL;DR: A generalized gray-scale and rotation invariant operator presentation that allows for detecting the "uniform" patterns for any quantization of the angular space and for any spatial resolution and presents a method for combining multiple operators for multiresolution analysis.
Journal ArticleDOI
The Fractal Geometry of Nature
TL;DR: A blend of erudition (fascinating and sometimes obscure historical minutiae abound), popularization (mathematical rigor is relegated to appendices) and exposition (the reader need have little knowledge of the fields involved) is presented in this article.