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Multi-scale gray level co-occurrence matrices for texture description
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 …
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
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 …
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 …
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
Background To assess whether CT-derived texture features predict survival in patients
undergoing resection for pancreatic ductal adenocarcinoma (PDAC). Methods Thirty …
undergoing resection for pancreatic ductal adenocarcinoma (PDAC). Methods Thirty …
[HTML][HTML] Mammography image-based diagnosis of breast cancer using machine learning: a pilot study
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 …
of the most common tumors in women. Radiologists use mammograms to identify a breast …
Breast mass classification on mammograms using radial local ternary patterns
Textural features can be useful in differentiating between benign and malignant breast
lesions on mammograms. Unlike previous computerized schemes, which relied largely on …
lesions on mammograms. Unlike previous computerized schemes, which relied largely on …
Content based medical image retrieval using dictionary learning
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 …
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 …
(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 …
technologies which prove to be beneficial for radiologists and patients for better diagnosis …
Hybrid classifier based human activity recognition using the silhouette and cells
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 …
sequence by exploiting the key poses of the human silhouettes, and constructing a new …