Results 91 to 100 of about 15,845 (235)

Lung Cancer Classification using Gray-Level Co-Occurrence Matrix Feature Extraction and Forward Selection Feature Selection based on the K-Nearest Neighbor Algorithm

Indonesian Journal of Applied Physics
In diagnosing lung cancer, the medical imaging team manually identifies CT-scan images of the lungs. This identification process makes it difficult for the medical imaging team to differentiate between lung cancer and normal images. This is because there
Soeparmi Soeparmi, Mohtar Yunianto, Lukmaniyah Rizky Amalia   +2 more
doaj   +1 more source

Radiomics Analysis for Predicting Medication‐Related Osteonecrosis of the Jaw Using Computed Tomography

Oral Diseases, EarlyView.
ABSTRACT Objectives To determine whether pretreatment radiomics can predict medication‐related osteonecrosis of the jaw (MRONJ). Methods Patients with mandibular MRONJ at Hiroshima University Hospital (2009–2024) who underwent MDCT before initiating bone resorption inhibitors were retrospectively identified. Records from 2009 to 2020 were also reviewed
Masaru Konishi
wiley   +1 more source

Classification of Rice Leaf Diseases Using Support Vector Machine with HSV and GLCM-Based Feature Extraction

Journal of Applied Informatics and Computing
This study aims to classify rice leaf diseases using the Support Vector Machine (SVM) algorithm based on image processing and feature extraction. A total of 600 rice leaf images were collected, each representing one of five disease types: bacterial ...
Rizal Ramli, Evanita Evanita, Aditya Akbar Riadi   +2 more
doaj   +1 more source

UAV‐based deep transfer learning to improve grain yield prediction in winter wheat across temporal and spatial variability

The Plant Phenome Journal, Volume 9, Issue 1, December 2026.
Abstract Accurate prediction of grain yield (GY) remains a major challenge in plant breeding due to complex interactions between genotype, environment, and management (G × E × M) factors. Remote sensing data from unmanned aerial vehicles (UAVs) equipped with multispectral sensors have emerged as a pivotal resource for high‐throughput phenotyping.
Swas Kaushal, Mohammad Maruf Billah, Mandeep Singh, Dante Koupal, Pradeep Raj Sitaula, Jyotirmoy Halder, Jagdeep Sidhu, Maitiniyazi Maimaitijiang, Sunish K. Sehgal   +8 more
wiley   +1 more source

Perbandingan Kinerja Support Vector Machine (SVM) Dalam Mengenali Wajah Menggunakan SURF DAN GLCM

, 2019
Face recognition is one part of the biometrics research. Face recognition is widely used in identification and recognition process. Speed-up Robust Feature (SURF) is one of feature extraction method used in face recognition system.
Khairun Saddami, Kahlil Muchtar, Arnia, Fitri, Muchtar, Kahlil, Saddami, Khairun, Syamsul Bahri, Bahri, Syamsul, Fitri Arnia   +7 more
core   +1 more source

Development of a Prediction Model for Progression Risk in High‐Grade Gliomas Based on Habitat Radiomics and Pathomics

Annals of Clinical and Translational Neurology, Volume 13, Issue 6, Page 1141-1153, June 2026.
ABSTRACT Objective To investigate the value of constructing models based on habitat radiomics and pathomics for predicting the risk of progression in high‐grade gliomas. Methods This study conducted a retrospective analysis of preoperative magnetic resonance (MR) images and pathological sections from 72 patients diagnosed with high‐grade gliomas (52 ...
Yuchen Zhu, Yuxi Gong, Weilin Xu, Xingjian Sun, Gefei Jiang, Lei Qiu, Kexin Shi, Mengxing Wu, Yinjiao Fei, Jinling Yuan, Jinyan Luo, Yurong Li, Yuandong Cao, Minhong Pan, Shu Zhou   +14 more
wiley   +1 more source

System informatyczny OS-GLCM przeznaczony do generowania macierzy GLCM opisującej teksturę obrazów cyfrowych rzepaku

, 2017
The purpose of this paper is to produce original software for calculating the GLCM matrix and its properties. Application mechanics is based on two AForge.Net library for image segmentation, and the Accord.Net library for calculating the GLCM matrix. The
Jurek, P., Okoń, P., Kozłowski, R. J., Fojud, A., Boniecki, P., Górna, K.   +5 more
core  

Automated Tuberculosis Detection in Chest Radiographs: A Hybrid Deep Learning Framework for Clinical Decision Support

Applied AI Letters, Volume 7, Issue 2, June 2026.
A hybrid deep learning framework integrating VGG16, ResNet50, and DenseNet121 is proposed for automated tuberculosis detection from chest X‐ray images. Feature‐level fusion enhances robustness and generalization, achieving 97.4% accuracy across multiple public datasets, supporting reliable clinical decision‐making in resource‐limited healthcare ...
Md. Tahmid Hossain, Hrittik Mural, Monowar Wadud Hridoy   +2 more
wiley   +1 more source

FUNGSI GLCM PADA BACKPROPAGATION UNTUK IDENTIFIKASI SIDIK JARI [PDF]

, 2019
The use of fingerprints for identification has been done a lot, both in the police for investigations, in government for absences, in population and much more. To identify fingerprints, various methods are widely used which purpose is to produce a better

core   +1 more source

Hybrid methods for feature extraction for breast masses classification

Egyptian Informatics Journal, 2018
This paper is focusing on feature extraction methods for malignant masses in mammograms and its classification. It proposes seven texture features for GLCM method and to be applied on sub-images to enhance its performance.
Mohamed A. Berbar
doaj   +1 more source