Multi-scale gray level co-occurrence matrices for texture description

FR De Siqueira, WR Schwartz, H Pedrini - Neurocomputing, 2013 - Elsevier
Texture information plays an important role in image analysis. Although several descriptors
have been proposed to extract and analyze texture, the development of automatic systems …

Automated stratification of liver disease in ultrasound: an online accurate feature classification paradigm

L Saba, N Dey, AS Ashour, S Samanta, SS Nath… - Computer methods and …, 2016 - Elsevier
Purpose Fatty liver disease (FLD) is one of the most common diseases in liver. Early
detection can improve the prognosis considerably. Using ultrasound for FLD detection is …

Automatic classification for pathological prostate images based on fractal analysis

PW Huang, CH Lee - IEEE transactions on medical imaging, 2009 - ieeexplore.ieee.org
Accurate grading for prostatic carcinoma in pathological images is important to prognosis
and treatment planning. Since human grading is always time-consuming and subjective, this …

CT texture features are associated with overall survival in pancreatic ductal adenocarcinoma–a quantitative analysis

A Eilaghi, S Baig, Y Zhang, J Zhang, P Karanicolas… - BMC medical …, 2017 - Springer
Background To assess whether CT-derived texture features predict survival in patients
undergoing resection for pancreatic ductal adenocarcinoma (PDAC). Methods Thirty …

[HTML][HTML] Mammography image-based diagnosis of breast cancer using machine learning: a pilot study

MM Alshammari, A Almuhanna, J Alhiyafi - Sensors, 2021 - mdpi.com
A tumor is an abnormal tissue classified as either benign or malignant. A breast tumor is one
of the most common tumors in women. Radiologists use mammograms to identify a breast …

Breast mass classification on mammograms using radial local ternary patterns

C Muramatsu, T Hara, T Endo, H Fujita - Computers in biology and …, 2016 - Elsevier
Textural features can be useful in differentiating between benign and malignant breast
lesions on mammograms. Unlike previous computerized schemes, which relied largely on …

Content based medical image retrieval using dictionary learning

M Srinivas, RR Naidu, CS Sastry, CK Mohan - Neurocomputing, 2015 - Elsevier
In this paper, a clustering method using dictionary learning is proposed to group large
medical databases. An approach grou** similar images into clusters that are sparsely …

RETRACTED: Optimal brain tumor diagnosis based on deep learning and balanced sparrow search algorithm

T Liu, Z Yuan, L Wu, B Badami - International Journal of …, 2021 - Wiley Online Library
In recent years, the diagnosis of brain tumors with the help of magnetic resonance imaging
(MRI) methods has received significant attention. MRI techniques with substantial …

Study of Haralick's and GLCM texture analysis on 3D medical images

B Dhruv, N Mittal, M Modi - international journal of Neuroscience, 2019 - Taylor & Francis
Purpose of the study: Medical field has highly evolved with advancements in the
technologies which prove to be beneficial for radiologists and patients for better diagnosis …

Hybrid classifier based human activity recognition using the silhouette and cells

DK Vishwakarma, R Kapoor - Expert Systems with Applications, 2015 - Elsevier
The aim of this paper is to present a new approach for human activity recognition in a video
sequence by exploiting the key poses of the human silhouettes, and constructing a new …