SU-D-BRA-01: Therapeutic Response Assessment Using a Novel Gray Level Local Power Matrix (GLLPM) in DCE-MRI Texture Analysis: Feasibility Study

2015 ◽  
Vol 42 (6) ◽  
pp. 3212-3213 ◽  
Author(s):  
C Wang ◽  
E Subashi ◽  
F Yin ◽  
Z Chang
Keyword(s):  
Texture Analysis ◽  
Feasibility Study ◽  
Therapeutic Response ◽  
Response Assessment ◽  
Gray Level ◽  
Local Power ◽  
Dce Mri ◽  
Power Matrix

Characterization of Pancreas at Diabetic Patients in CT images using Texture Analysis

2017 ◽  
Vol 7 (7) ◽  
pp. 8
Author(s):  
Mona E. Elbashier ◽  
Suhaib Alameen ◽  
Caroline Edward Ayad ◽  
Mohamed E. M. Gar-Elnabi
Keyword(s):  
Size Distribution ◽  
Texture Analysis ◽  
Classification Accuracy ◽  
Ct Images ◽  
Diabetic Patients ◽  
Gray Level ◽  
Grey Level ◽  
Run Length ◽  
Interactive Data

This study concern to characterize the pancreas areato head, body and tail using Gray Level Run Length Matrix (GLRLM) and extract classification features from CT images. The GLRLM techniques included eleven’s features. To find the gray level distribution in CT images it complements the GLRLM features extracted from CT images with runs of gray level in pixels and estimate the size distribution of thesubpatterns. analyzing the image with Interactive Data Language IDL software to measure the grey level distribution of images. The results show that the Gray Level Run Length Matrix and  features give classification accuracy of pancreashead 89.2%, body 93.6 and the tail classification accuracy 93.5%. The overall classification accuracy of pancreas area 92.0%.These relationships are stored in a Texture Dictionary that can be later used to automatically annotate new CT images with the appropriate pancreas area names.

scholarly journals WRITER IDENTIFICATION BY TEXTURE ANALYSIS BASED ON KANNADA HANDWRITING

2012 ◽  
pp. 80-85
Author(s):  
B.V. DHANDRA ◽  
VIJAYALAXMI.M. B ◽  
GURURAJ MUKARAMBI ◽  
MALLIKARJUN. HANGARGE
Keyword(s):  
Texture Analysis ◽  
Identification Problem ◽  
Document Image ◽  
Independent Method ◽  
Gray Level ◽  
Writer Identification ◽  
Texture Image ◽  
Major Research ◽  
Gabor Filtering ◽  
Occurrence Matrix

Writer identification problem is one of the important area of research due to its various applications and is a challenging task. The major research on writer identification is based on handwritten English documents with text independent and dependent. However, there is no significant work on identification of writers based on Kannada document. Hence, in this paper, we propose a text-independent method for off-line writer identification based on Kannada handwritten scripts. By observing each individual’s handwriting as a different texture image, a set of features based on Discrete Cosine Transform, Gabor filtering and gray level co-occurrence matrix, are extracted from preprocessed document image blocks. Experimental results demonstrate that the Gabor energy features are more potential than the DCTs and GLCMs based features for writer identification from 20 people.

Assessment of therapeutic response of lymphoma patients by PET/CT

QJM ◽  
2021 ◽  
Vol 114 (Supplement_1) ◽  
Author(s):  
Aya Y Ahmed ◽  
Mona A Nagi ◽  
Radwa H. El Sheikh
Keyword(s):  
Therapeutic Response ◽  
Imaging Modality ◽  
Treatment Plan ◽  
Response Assessment ◽  
Response To Therapy ◽  
University Hospital ◽  
Lymphoid Tissues ◽  
Cross Sectional ◽  
End Of Treatment ◽  
Pet Ct

Abstract Background Lymphoma compromises а histologically heterogeneous group of cancers derived from the cells of the immune system. The hallmark of the disease is the enlargement and proliferation of lymph nodes or secondary lymphoid tissues. Aim of the Work to evaluate the role of Positron emission tomography in the assessment of response to therapy in lymphoma patients: in particular, a five-point scale (Deauville criteria), which can be employed for early- and late-therapeutic response assessment. Patients and Methods This cross sectional study was conducted on 20 Patients with different types of lymphoma recruited and enrolled from Ain Shams university hospital. Results PET/CT and Contrast enhanced computed tomography were concurrent in results in 55% of cases during treatment and 75 % at the end of treatment with CT sensitivity of 61.1%, specificity of 92.2% and accuracy of 76.2% during treatment in comparison to 100 % sensitivity and specificity of PET/CT.While sensitivity of CT at end of treatment is 57.5% with specificity of 86.7% and accuracy of 71.6%. Conclusion PET/СT using 2-deoxy-2[18F]fluoro-D-glucose is considered one of the best oncologic imaging modality at the time being with valuable applications in lymphoma.It is very efficient with least possible pitfalls and false results compared to either of its components alone and to side by side reading of separately acquired PET and СT. It is becoming а standard modality for lymphoma providing а new vision to management and treatment plan.

scholarly journals NIR nanoprobe-facilitated cross-referencing manifestation of local disease biology for dynamic therapeutic response assessment

2020 ◽  
Vol 11 (3) ◽  
pp. 803-811 ◽  
Author(s):  
Zhimin Wang ◽  
Xiangzhao Ai ◽  
Zhijun Zhang ◽  
Yong Wang ◽  
Xiangyang Wu ◽  
...  
Keyword(s):  
Oxidative Stress ◽  
Therapeutic Response ◽  
Response Assessment ◽  
Local Disease ◽  
Disease Biology

NIR photoacoustic and upconversion luminescent nanoprobe-facilitated cross-referencing manifestation of oxidative stress-induced liver pathophysiology for dynamic therapeutic response assessment.

scholarly journals ALTEA: A Software Tool for the Evaluation of New Biomarkers for Alzheimer’s Disease by Means of Textures Analysis on Magnetic Resonance Images

Diagnostics ◽  
2018 ◽  
Vol 8 (3) ◽  
pp. 47 ◽  
Author(s):  
Carlos López-Gómez ◽  
Rafael Ortiz-Ramón ◽  
Enrique Mollá-Olmos ◽  
David Moratal ◽  
Keyword(s):  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Magnetic Resonance ◽  
Texture Analysis ◽  
Software Tool ◽  
Magnetic Resonance Images ◽  
Gray Level ◽  
Predictive Capacity ◽  
Texture Parameters ◽  
New Biomarkers

The current criteria for diagnosing Alzheimer’s disease (AD) require the presence of relevant cognitive deficits, so the underlying neuropathological damage is important by the time the diagnosis is made. Therefore, the evaluation of new biomarkers to detect AD in its early stages has become one of the main research focuses. The purpose of the present study was to evaluate a set of texture parameters as potential biomarkers of the disease. To this end, the ALTEA (ALzheimer TExture Analyzer) software tool was created to perform 2D and 3D texture analysis on magnetic resonance images. This intuitive tool was used to analyze textures of circular and spherical regions situated in the right and left hippocampi of a cohort of 105 patients: 35 AD patients, 35 patients with early mild cognitive impairment (EMCI) and 35 cognitively normal (CN) subjects. A total of 25 statistical texture parameters derived from the histogram, the Gray-Level Co-occurrence Matrix and the Gray-Level Run-Length Matrix, were extracted from each region and analyzed statistically to study their predictive capacity. Several textural parameters were statistically significant (p < 0.05) when differentiating AD subjects from CN and EMCI patients, which indicates that texture analysis could help to identify the presence of AD.

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