keyword
MENU ▼
Read by QxMD icon Read
search

Texture mri

keyword
https://www.readbyqxmd.com/read/28217825/preoperative-prediction-of-muscular-invasiveness-of-bladder-cancer-with-radiomic-features-on-conventional-mri-and-its-high-order-derivative-maps
#1
Xiaopan Xu, Yang Liu, Xi Zhang, Qiang Tian, Yuxia Wu, Guopeng Zhang, Jiang Meng, Zengyue Yang, Hongbing Lu
PURPOSE: To determine radiomic features which are capable of reflecting muscular invasiveness of bladder cancer (BC) and propose a non-invasive strategy for the differentiation of muscular invasiveness preoperatively. METHODS: Sixty-eight patients with clinicopathologically confirmed BC were included in this retrospective study. A total of 118 cancerous volumes of interest (VOI) were segmented from patients' T2 weighted MR images (T2WI), including 34 non-muscle invasive bladder carcinomas (NMIBCs, stage <T2) and 84 muscle invasive ones (MIBCs, stage ≥T2)...
February 20, 2017: Abdominal Radiology
https://www.readbyqxmd.com/read/28199039/radiomics-assessment-of-bladder-cancer-grade-using-texture-features-from-diffusion-weighted-imaging
#2
Xi Zhang, Xiaopan Xu, Qiang Tian, Baojuan Li, Yuxia Wu, Zengyue Yang, Zhengrong Liang, Yang Liu, Guangbin Cui, Hongbing Lu
PURPOSE: To 1) describe textural features from diffusion-weighted images (DWI) and apparent diffusion coefficient (ADC) maps that can distinguish low-grade bladder cancer from high-grade, and 2) propose a radiomics-based strategy for cancer grading using texture features. MATERIALS AND METHODS: In all, 61 patients with bladder cancer (29 in high- and 32 in low-grade groups) were enrolled in this retrospective study. Histogram- and gray-level co-occurrence matrix (GLCM)-based radiomics features were extracted from cancerous volumes of interest (VOIs) on DWI and corresponding ADC maps of each patient acquired from 3...
February 15, 2017: Journal of Magnetic Resonance Imaging: JMRI
https://www.readbyqxmd.com/read/28196476/automatic-mri-segmentation-of-para-pharyngeal-fat-pads-using-interactive-visual-feature-space-analysis-for-classification
#3
Muhammad Laiq Ur Rahman Shahid, Teodora Chitiboi, Tetyana Ivanovska, Vladimir Molchanov, Henry Völzke, Lars Linsen
BACKGROUND: Obstructive sleep apnea (OSA) is a public health problem. Detailed analysis of the para-pharyngeal fat pads can help us to understand the pathogenesis of OSA and may mediate the intervention of this sleeping disorder. A reliable and automatic para-pharyngeal fat pads segmentation technique plays a vital role in investigating larger data bases to identify the anatomic risk factors for the OSA. METHODS: Our research aims to develop a context-based automatic segmentation algorithm to delineate the fat pads from magnetic resonance images in a population-based study...
February 14, 2017: BMC Medical Imaging
https://www.readbyqxmd.com/read/28190856/virilism-and-ectopic-expression-of-hsd17b5-in-mature-cystic-teratoma
#4
Yohei Kawaguchi, Hiroko Mizuno, Mai Horikawa, Mayuko Kano, Kengo Yamada, Fumiko Yamakawa, Takashi Maekawa, Yuto Yamazaki, Keely M McNamara, Hironobu Sasano, Masayuki Hayashi
Mature cystic teratoma (MCT) is rarely involved in the overproduction of steroid hormones in contrast to sex cord stromal tumors. A 31-year-old woman visited our hospital with hirsutism, hoarseness, and hair loss from the scalp. Serum testosterone and free-testosterone levels were 7.3 ng/ml and 2.3 pg/ml, respectively, which were markedly in excess of the age adjusted female standard levels. Basal blood levels of steroid hormones and serum levels of 17-hydroxyprogesterone at 1 h after intravenous injection of adrenocorticotropic hormone demonstrated that 21-hydroxylase deficiency was not the underlying cause of her virilization...
2017: Tohoku Journal of Experimental Medicine
https://www.readbyqxmd.com/read/28187893/computer-aided-grading-of-gliomas-based-on-local-and-global-mri-features
#5
Kevin Li-Chun Hsieh, Chung-Ming Lo, Chih-Jou Hsiao
BACKGROUND AND OBJECTIVES: A computer-aided diagnosis (CAD) system based on quantitative magnetic resonance imaging (MRI) features was developed to evaluate the malignancy of diffuse gliomas, which are central nervous system tumors. METHODS: The acquired image database for the CAD performance evaluation was composed of 34 glioblastomas and 73 diffuse lower-grade gliomas. In each case, tissues enclosed in a delineated tumor area were analyzed according to their gray-scale intensities on MRI scans...
February 2017: Computer Methods and Programs in Biomedicine
https://www.readbyqxmd.com/read/28177554/identifying-relations-between-imaging-phenotypes-and-molecular-subtypes-of-breast-cancer-model-discovery-and-external-validation
#6
Jia Wu, Xiaoli Sun, Jeff Wang, Yi Cui, Fumi Kato, Hiroki Shirato, Debra M Ikeda, Ruijiang Li
PURPOSE: To determine whether dynamic contrast enhancement magnetic resonance imaging (DCE-MRI) characteristics of the breast tumor and background parenchyma can distinguish molecular subtypes (ie, luminal A/B or basal) of breast cancer. MATERIALS AND METHODS: In all, 84 patients from one institution and 126 patients from The Cancer Genome Atlas (TCGA) were used for discovery and external validation, respectively. Thirty-five quantitative image features were extracted from DCE-MRI (1...
February 8, 2017: Journal of Magnetic Resonance Imaging: JMRI
https://www.readbyqxmd.com/read/28166261/radiomic-analysis-reveals-dce-mri-features-for-prediction-of-molecular-subtypes-of-breast-cancer
#7
Ming Fan, Hui Li, Shijian Wang, Bin Zheng, Juan Zhang, Lihua Li
The purpose of this study was to investigate the role of features derived from breast dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) and to incorporated clinical information to predict the molecular subtypes of breast cancer. In particular, 60 breast cancers with the following four molecular subtypes were analyzed: luminal A, luminal B, human epidermal growth factor receptor-2 (HER2)-over-expressing and basal-like. The breast region was segmented and the suspicious tumor was depicted on sequentially scanned MR images from each case...
2017: PloS One
https://www.readbyqxmd.com/read/28157660/adaptive-local-window-for-level-set-segmentation-of-ct-and-mri-liver-lesions
#8
Assaf Hoogi, Christopher F Beaulieu, Guilherme M Cunha, Elhamy Heba, Claude B Sirlin, Sandy Napel, Daniel L Rubin
We propose a novel method, the adaptive local window, for improving level set segmentation technique. The window is estimated separately for each contour point, over iterations of the segmentation process, and for each individual object. Our method considers the object scale, the spatial texture, and the changes of the energy functional over iterations. Global and local statistics are considered by calculating several gray level co-occurrence matrices. We demonstrate the capabilities of the method in the domain of medical imaging for segmenting 233 images with liver lesions...
January 13, 2017: Medical Image Analysis
https://www.readbyqxmd.com/read/28153351/non-invasive-identification-of-vulnerable-atherosclerotic-plaques-using-texture-analysis-in-ultrasound-carotid-elastography-an-in%C3%A2-vivo-feasibility-study-validated-by-magnetic-resonance-imaging
#9
Chengwu Huang, Qiong He, Manwei Huang, Lingyun Huang, Xihai Zhao, Chun Yuan, Jianwen Luo
The aims of this study were to quantify the textural information of strain rate images in ultrasound carotid elastography and evaluate the feasibility of using the textural features in discriminating stable and vulnerable plaques with magnetic resonance imaging as an in vivo reference. Ultrasound radiofrequency data were acquired in 80 carotid plaques from 52 patients, mainly in the longitudinal imaging view, and axial strain rate images were estimated with an ultrasound carotid elastography technique based on an optical flow algorithm...
January 30, 2017: Ultrasound in Medicine & Biology
https://www.readbyqxmd.com/read/28145505/brain-networks-involved-in-tactile-speed-classification-of-moving-dot-patterns-the-effects-of-speed-and-dot-periodicity
#10
Jiajia Yang, Ryo Kitada, Takanori Kochiyama, Yinghua Yu, Kai Makita, Yuta Araki, Jinglong Wu, Norihiro Sadato
Humans are able to judge the speed of an object's motion by touch. Research has suggested that tactile judgment of speed is influenced by physical properties of the moving object, though the neural mechanisms underlying this process remain poorly understood. In the present study, functional magnetic resonance imaging was used to investigate brain networks that may be involved in tactile speed classification and how such networks may be affected by an object's texture. Participants were asked to classify the speed of 2-D raised dot patterns passing under their right middle finger...
February 1, 2017: Scientific Reports
https://www.readbyqxmd.com/read/28119818/differential-diagnosis-of-mild-cognitive-impairment-and-alzheimer-s-disease-using-structural-mri-cortical-thickness-hippocampal-shape-hippocampal-texture-and-volumetry
#11
Lauge Sørensen, Christian Igel, Akshay Pai, Ioana Balas, Cecilie Anker, Martin Lillholm, Mads Nielsen
This paper presents a brain T1-weighted structural magnetic resonance imaging (MRI) biomarker that combines several individual MRI biomarkers (cortical thickness measurements, volumetric measurements, hippocampal shape, and hippocampal texture). The method was developed, trained, and evaluated using two publicly available reference datasets: a standardized dataset from the Alzheimer's Disease Neuroimaging Initiative (ADNI) and the imaging arm of the Australian Imaging Biomarkers and Lifestyle flagship study of ageing (AIBL)...
2017: NeuroImage: Clinical
https://www.readbyqxmd.com/read/28113927/adaptive-estimation-of-active-contour-parameters-using-convolutional-neural-networks-and-texture-analysis
#12
Assaf Hoogi, Arjun Subramaniam, Rishi Veerapaneni, Daniel Rubin
In this paper, we propose a generalization of the level set segmentation approach by supplying a novel method for adaptive estimation of active contour parameters. The presented segmentation method is fully automatic once the lesion has been detected. First, the location of the level set contour relative to the lesion is estimated using a convolutional neural network (CNN). The CNN has two convolutional layers for feature extraction, which lead into dense layers for classification. Second, the output CNN probabilities are then used to adaptively calculate the parameters of the active contour functional during the segmentation process...
November 11, 2016: IEEE Transactions on Medical Imaging
https://www.readbyqxmd.com/read/28110743/exploring-the-complementarity-of-thz-pulse-imaging-and-dce-mris-toward-a-unified-multi-channel-classification-and-a-deep-learning-framework
#13
REVIEW
X-X Yin, Y Zhang, J Cao, J-L Wu, S Hadjiloucas
We provide a comprehensive account of recent advances in biomedical image analysis and classification from two complementary imaging modalities: terahertz (THz) pulse imaging and dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI). The work aims to highlight underlining commonalities in both data structures so that a common multi-channel data fusion framework can be developed. Signal pre-processing in both datasets is discussed briefly taking into consideration advances in multi-resolution analysis and model based fractional order calculus system identification...
December 2016: Computer Methods and Programs in Biomedicine
https://www.readbyqxmd.com/read/28110476/three-dimensional-texture-features-from-intensity-and-high-order-derivative-maps-for-the-discrimination-between-bladder-tumors-and-wall-tissues-via-mri
#14
Xiaopan Xu, Xi Zhang, Qiang Tian, Guopeng Zhang, Yang Liu, Guangbin Cui, Jiang Meng, Yuxia Wu, Tianshuai Liu, Zengyue Yang, Hongbing Lu
PURPOSE: This study aims to determine the three-dimensional (3D) texture features extracted from intensity and high-order derivative maps that could reflect textural differences between bladder tumors and wall tissues, and propose a noninvasive, image-based strategy for bladder tumor differentiation preoperatively. METHODS: A total of 62 cancerous and 62 wall volumes of interest (VOI) were extracted from T2-weighted MRI datasets of 62 patients with pathologically confirmed bladder cancer...
January 21, 2017: International Journal of Computer Assisted Radiology and Surgery
https://www.readbyqxmd.com/read/28079702/radiomic-analysis-reveals-prognostic-information-in-t1-weighted-baseline-magnetic-resonance-imaging-in-patients-with-glioblastoma
#15
Michael Ingrisch, Moritz Jörg Schneider, Dominik Nörenberg, Giovanna Negrao de Figueiredo, Klaus Maier-Hein, Bogdana Suchorska, Ulrich Schüller, Nathalie Albert, Hartmut Brückmann, Maximilian Reiser, Jörg-Christian Tonn, Birgit Ertl-Wagner
OBJECTIVES: The aim of this study was to investigate whether radiomic analysis with random survival forests (RSFs) can predict overall survival from T1-weighted contrast-enhanced baseline magnetic resonance imaging (MRI) scans in a cohort of glioblastoma multiforme (GBM) patients with uniform treatment. MATERIALS AND METHODS: This retrospective study was approved by the institutional review board and informed consent was waived. The MRI scans from 66 patients with newly diagnosed GBM from a previous prospective study were analyzed...
January 9, 2017: Investigative Radiology
https://www.readbyqxmd.com/read/28048226/su-f-r-35-repeatability-of-texture-features-in-t1-and-t2-weighted-mr-images
#16
R Mahon, E Weiss, J Ford, K Karki, G Hugo
PURPOSE: To evaluate repeatability of lung tumor texture features from inspiration/expiration MR image pairs for potential use in patient specific care models and applications. Repeatability is a desirable and necessary characteristic of features included in such models. METHODS: T1-weighted Volumetric Interpolation Breath-Hold Examination (VIBE) and/or T2-weighted MRI scans were acquired for 15 patients with non-small cell lung cancer before and during radiotherapy for a total of 32 and 34 same session inspiration-expiration breath-hold image pairs respectively...
June 2016: Medical Physics
https://www.readbyqxmd.com/read/28048162/su-f-r-08-can-normalization-of-brain-mri-texture-features-reduce-scanner-dependent-effects-in-unsupervised-machine-learning
#17
K Ogden, T Bradford, L Cussen, R O'Dwyer
PURPOSE: To reduce differences in features calculated from MRI brain scans acquired at different field strengths with or without Gadolinium contrast. METHODS: Brain scans were processed for 111 epilepsy patients to extract hippocampus and thalamus features. Scans were acquired on 1.5 T scanners with Gadolinium contrast (group A), 1.5T scanners without Gd (group B), and 3.0 T scanners without Gd (group C). A total of 72 features were extracted. Features were extracted from original scans and from scans where the image pixel values were rescaled to the mean of the hippocampi and thalami values...
June 2016: Medical Physics
https://www.readbyqxmd.com/read/28047742/su-f-r-17-advancing-glioblastoma-multiforme-gbm-recurrence-detection-with-mri-image-texture-feature-extraction-and-machine-learning
#18
V Yu, D Ruan, D Nguyen, T Kaprealian, R Chin, K Sheng
PURPOSE: To test the potential of early Glioblastoma Multiforme (GBM) recurrence detection utilizing image texture pattern analysis in serial MR images post primary treatment intervention. METHODS: MR image-sets of six time points prior to the confirmed recurrence diagnosis of a GBM patient were included in this study, with each time point containing T1 pre-contrast, T1 post-contrast, T2-Flair, and T2-TSE images. Eight Gray-level co-occurrence matrix (GLCM) texture features including Contrast, Correlation, Dissimilarity, Energy, Entropy, Homogeneity, Sum-Average, and Variance were calculated from all images, resulting in a total of 32 features at each time point...
June 2016: Medical Physics
https://www.readbyqxmd.com/read/28047590/su-f-r-02-imaging-genomics-for-predicting-gbm-molecular-subclasses-and-survival
#19
F Mahmoudi, L Poisson, H Bagher-Ebadian, M Nazem-Zadeh, H Soltanian-Zadeh
PURPOSE: Glioblastoma (GBM) is the most common and fatal primary intracranial neoplasm. GBM is categorized into five sub-classes (classical, G-CIMP, mesenchymal, proneural and neural) that can only be determined by an invasive brain biopsy followed by RNA and DNA methylation profiling. The goal of this study is to develop imaging features extracted from conventional MRI scans and an ensemble-classification method as a potential noninvasive method to predict the five molecular sub-classes and 12-month survival status...
June 2016: Medical Physics
https://www.readbyqxmd.com/read/28047470/su-f-r-32-evaluation-of-mri-acquisition-parameter-variations-on-texture-feature-extraction-using-acr-phantom
#20
Y Xie, J Wang, C Wang, Z Chang
PURPOSE: To investigate the sensitivity of classic texture features to variations of MRI acquisition parameters. METHODS: This study was performed on American College of Radiology (ACR) MRI Accreditation Program Phantom. MR imaging was acquired on a GE 750 3T scanner with XRM explain gradient, employing a T1-weighted images (TR/TE=500/20ms) with the following parameters as the reference standard: number of signal average (NEX) = 1, matrix size = 256×256, flip angle = 90°, slice thickness = 5mm...
June 2016: Medical Physics
keyword
keyword
106410
1
2
Fetch more papers »
Fetching more papers... Fetching...
Read by QxMD. Sign in or create an account to discover new knowledge that matter to you.
Remove bar
Read by QxMD icon Read
×

Search Tips

Use Boolean operators: AND/OR

diabetic AND foot
diabetes OR diabetic

Exclude a word using the 'minus' sign

Virchow -triad

Use Parentheses

water AND (cup OR glass)

Add an asterisk (*) at end of a word to include word stems

Neuro* will search for Neurology, Neuroscientist, Neurological, and so on

Use quotes to search for an exact phrase

"primary prevention of cancer"
(heart or cardiac or cardio*) AND arrest -"American Heart Association"