Spatial Bayesian modeling of GLCM with application to malignant lesion characterization
Sign Up to like & getrecommendations! Published in 2018 at "Journal of Applied Statistics"
DOI: 10.1080/02664763.2018.1473348
Abstract: ABSTRACT The emerging field of cancer radiomics endeavors to characterize intrinsic patterns of tumor phenotypes and surrogate markers of response by transforming medical images into objects that yield quantifiable summary statistics to which regression and… read more here.
Keywords: modeling; bayesian modeling; spatial bayesian; application ... See more keywords
Evaluation of MRI-based radiomic features in heart morphologic variations as a consequence of autoimmune thyroid disorders
Sign Up to like & getrecommendations! Published in 2022 at "Medicine"
DOI: 10.1097/md.0000000000030197
Abstract: Radiomics (RC) was initially developed using computed tomography (CT) for oncological imaging. However, it can be applied to various scientific and clinical radiology fields regardless of the modalities involved. The purpose of this survey was… read more here.
Keywords: glcm; gray level; heart; autoimmune thyroid ... See more keywords
Development of a Gray-Level Co-Occurrence Matrix-Based Texture Orientation Estimation Method and Its Application in Sea Surface Wind Direction Retrieval From SAR Imagery
Sign Up to like & getrecommendations! Published in 2018 at "IEEE Transactions on Geoscience and Remote Sensing"
DOI: 10.1109/tgrs.2018.2812778
Abstract: A gray-level co-occurrence matrix (GLCM)-based method was developed for better texture orientation estimation in remote sensing imagery. A GLCM is essentially the joint probability distribution of gray levels at the position pairs satisfying a specific… read more here.
Keywords: orientation; method; texture orientation; orientation estimation ... See more keywords
Gray level co-occurrence matrix (GLCM) texture based crop classification using low altitude remote sensing platforms
Sign Up to like & getrecommendations! Published in 2021 at "PeerJ Computer Science"
DOI: 10.7717/peerj-cs.536
Abstract: Crop classification in early phenological stages has been a difficult task due to spectrum similarity of different crops. For this purpose, low altitude platforms such as drones have great potential to provide high resolution optical… read more here.
Keywords: crop classification; low altitude; gray level; glcm ... See more keywords