Results 1 to 10 of about 578,151 (295)
Multi Texture Analysis of Colorectal Cancer Continuum Using Multispectral Imagery. [PDF]
PLoS ONE, 2016 PURPOSE:This paper proposes to characterize the continuum of colorectal cancer (CRC) using multiple texture features extracted from multispectral optical microscopy images.
Ahmad Chaddad +5 more
doaj +7 more sources
Predicting head and neck cancer treatment outcomes with pre-treatment quantitative ultrasound texture features and optimising machine learning classifiers with texture-of-texture features [PDF]
Frontiers in Oncology, 2023 AimCancer treatments with radiation present a challenging physical toll for patients, which can be justified by the potential reduction in cancerous tissue with treatment.
Aryan Safakish +17 more
doaj +2 more sources
Estimating rice yield-related traits using machine learning models integrating hyperspectral and texture features [PDF]
Frontiers in Plant ScienceBackgroundRapidly estimating multiple trait indicators simultaneously, nondestructively, and with high precision is an important means of accurate diagnosis in modern phenomics.
Yufen Zhang +17 more
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Rotationally invariant texture based features [PDF]
Proceedings 2001 International Conference on Image Processing (Cat. No.01CH37205), 2001 Content-based retrieval is ultimately dependent on the features used for the annotation of data and its efficiency is dependent on the invariance and robust properties of these features.
Bull, DR, Canagarajah, CN, Hill, PR
core +4 more sources
Journal of the American Heart Association: Cardiovascular and Cerebrovascular Disease, 2019 Background We hypothesized that measures of common carotid artery echolucency and grayscale texture features were associated with cardiovascular disease (CVD) risk factors and could predict CVD events.
Carol C. Mitchell +9 more
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T1K+: A Database for Benchmarking Color Texture Classification and Retrieval Methods
Sensors, 2021 In this paper we present T1K+, a very large, heterogeneous database of high-quality texture images acquired under variable conditions. T1K+ contains 1129 classes of textures ranging from natural subjects to food, textile samples, construction materials ...
Claudio Cusano +2 more
doaj +1 more source
Wood recognition using image texture features. [PDF]
PLoS ONE, 2013 Inspired by theories of higher local order autocorrelation (HLAC), this paper presents a simple, novel, yet very powerful approach for wood recognition. The method is suitable for wood database applications, which are of great importance in wood related ...
Hang-jun Wang +2 more
doaj +1 more source
Scientific Reports, 2021 The purpose of this study was to examine differences in texture features between olfactory neuroblastoma (ONB) and sinonasal squamous cell carcinoma (SCC) on contrast-enhanced CT (CECT) images, and to evaluate the predictive accuracy of texture analysis ...
Masaki Ogawa +9 more
doaj +1 more source
Texture features for object salience [PDF]
Image and Vision Computing, 2017 Although texture is important for many vision-related tasks, it is not used in most salience models. As a consequence, there are images where all existing salience algorithms fail.
Kasim Terzic +2 more
openaire +4 more sources