Results 161 to 170 of about 22,865 (233)

An auxiliary diagnosis model for the pathological classification of cervical cancer based on radiomics biomarkers. [PDF]

Front Genet
Wang M, Cao Y, Zhu M, Zhao P, Zhou Q, Lan H, Liu J, Lei J.   +7 more
europepmc   +1 more source

Preventing spread of the invasive spotted lanternfly via texture-based automated egg detection. [PDF]

Front Insect Sci
Negrete K, Butler R, Wallis E, Magnani E, Mcglynn MB, McDonald M, Alvarez NJ, Tang M.   +7 more
europepmc   +1 more source

Preliminary exploration of radiomic mammographic analysis in triple negative breast cancer related to BRCA profile. [PDF]

Sci Rep
Pecchi A, Sessa G, Nocetti L, Beretta C, Bozzola C, Balboni E, Besutti G, Toss A, Cortesi L, Guidi G, Dominici M, Torricelli P.   +11 more
europepmc   +1 more source

Graph-enhanced multimodal fusion of vascular biomarkers and deep features for diabetic retinopathy detection. [PDF]

Front Artif Intell
Deepsahith KV, Shashank B, Kumar B, Alphonse S, Subburaj B, Subramanian G.   +5 more
europepmc   +1 more source

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MM-GLCM-CNN: A multi-scale and multi-level based GLCM-CNN for polyp classification

Computerized Medical Imaging and Graphics, 2023
Distinguishing malignant from benign lesions has significant clinical impacts on both early detection and optimal management of those early detections. Convolutional neural network (CNN) has shown great potential in medical imaging applications due to its powerful feature learning capability.
Shu Zhang 0006, Jinru Wu, Enze Shi, Sigang Yu, Yongfeng Gao, Lihong Li 0002, Licheng Ryan Kuo, Marc Jason Pomeroy, Jerome Zhengrong Liang   +8 more
openaire   +3 more sources

Vegetation Mapping with Random Forest Using Sentinel 2 and GLCM Texture Feature—A Case Study for Lousã Region, Portugal

Remote Sensing, 2022
Vegetation mapping requires accurate information to allow its use in applications such as sustainable forest management against the effects of climate change and the threat of wildfires.
Pegah Mohammadpour
exaly   +2 more sources

Object-Oriented LULC Classification in Google Earth Engine Combining SNIC, GLCM, and Machine Learning Algorithms

Remote Sensing, 2020
Google Earth Engine (GEE) is a versatile cloud platform in which pixel-based (PB) and object-oriented (OO) Land Use–Land Cover (LULC) classification approaches can be implemented, thanks to the availability of the many state-of-art functions comprising ...
Marco Vizzari, Vizzari Marco
exaly   +2 more sources

Quantitative Assessment of Hyperpigmentation Changes in Human Skin after Microneedle Mesotherapy Using the Gray-Level Co-Occurrence Matrix (GLCM) Method

Journal of Clinical Medicine, 2023
Aim: The aim of the study was to quantitatively assess the effectiveness of microneedle mesotherapy in reducing skin discoloration. The results were analyzed using the gray-level co-occurrence matrix (GLCM) method.
Mansur Rahnama, Sławomir Wilczynski, Anna Wawrzyk   +2 more
exaly   +2 more sources

3D Texture Feature Extraction and Classification Using GLCM and LBP-Based Descriptors

Applied Sciences (Switzerland), 2021
Lately, 3D imaging techniques have achieved a lot of progress due to recent developments in 3D sensor technologies. This leads to a great interest regarding 3D image feature extraction and classification techniques.
Romulus Terebes, Stefania Barburiceanu, Barburiceanu Stefania   +2 more
exaly   +2 more sources

Influence of GLCM texture parameters on lithological mapping using Sentinel-1 imagery

Geocarto International
Gray Level Co-Occurrence Matrix (GLCM) textures demonstrate great potential in lithological mapping, yet the influence of GLCM parameters (window size, distance, and angle) on mapping lithology using Sentinel-1 images has never been thoroughly explored ...
Changbao Yang
exaly   +2 more sources