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https://www.readbyqxmd.com/read/29047033/characterization-of-pulmonary-nodules-based-on-features-of-margin-sharpness-and-texture
#1
José Raniery Ferreira, Marcelo Costa Oliveira, Paulo Mazzoncini de Azevedo-Marques
Lung cancer is the leading cause of cancer-related deaths in the world, and one of its manifestations occurs with the appearance of pulmonary nodules. The classification of pulmonary nodules may be a complex task to specialists due to temporal, subjective, and qualitative aspects. Therefore, it is important to integrate computational tools to the early pulmonary nodule classification process, since they have the potential to characterize objectively and quantitatively the lesions. In this context, the goal of this work is to perform the classification of pulmonary nodules based on image features of texture and margin sharpness...
October 18, 2017: Journal of Digital Imaging: the Official Journal of the Society for Computer Applications in Radiology
https://www.readbyqxmd.com/read/29036877/a-hybrid-cnn-feature-model-for-pulmonary-nodule-malignancy-risk-differentiation
#2
Huafeng Wang, Tingting Zhao, Lihong Connie Li, Haixia Pan, Wanquan Liu, Haoqi Gao, Fangfang Han, Yuehai Wang, YiFang Qi, Zhengrong Liang
The malignancy risk differentiation of pulmonary nodule is one of the most challenge tasks of computer-aided diagnosis (CADx). Most recently reported CADx methods or schemes based on texture and shape estimation have shown relatively satisfactory on differentiating the risk level of malignancy among the nodules detected in lung cancer screening. However, the existing CADx schemes tend to detect and analyze characteristics of pulmonary nodules from a statistical perspective according to local features only. Enlightened by the currently prevailing learning ability of convolutional neural network (CNN), which simulates human neural network for target recognition and our previously research on texture features, we present a hybrid model that takes into consideration of both global and local features for pulmonary nodule differentiation using the largest public database founded by the Lung Image Database Consortium and Image Database Resource Initiative (LIDC-IDRI)...
October 10, 2017: Journal of X-ray Science and Technology
https://www.readbyqxmd.com/read/29036692/clinical-utility-of-texture-analysis-of-18f-fdg-pet-ct-in-patients-with-stage-i-lung-cancer-treated-with-stereotactic-body-radiotherapy
#3
Kazuya Takeda, Kentaro Takanami, Yuko Shirata, Takaya Yamamoto, Noriyoshi Takahashi, Kengo Ito, Kei Takase, Keiichi Jingu
We evaluated the reproducibility and predictive value of texture parameters and existing parameters of 18F-FDG PET/CT images in Stage I non-small-cell lung cancer (NSCLC) patients treated with stereotactic body radiotherapy (SBRT). Twenty-six patients with Stage I NSCLC (T1-2N0M0) were retrospectively analyzed. All of the patients underwent an 18F-FDG PET/CT scan before treatment and were treated with SBRT. Each tumor was delineated using PET Edge (MIM Software Inc., Cleveland, OH), and texture parameters were calculated using open-source code CGITA...
September 21, 2017: Journal of Radiation Research
https://www.readbyqxmd.com/read/28989563/generative-method-to-discover-emphysema-subtypes-with-unsupervised-learning-using-lung-macroscopic-patterns-lmps-the-mesa-copd-study
#4
Jingkuan Song, Jie Yang, Benjamin Smith, Pallavi Balte, Eric A Hoffman, R Graham Barr, Andrew F Laine, Elsa D Angelini
Pulmonary emphysema overlaps considerably with chronic obstructive pulmonary disease (COPD), and is traditionally subcategorized into three subtypes: centrilobular emphysema (CLE), panlobular emphysema (PLE) and paraseptal emphysema (PSE). Automated classification methods based on supervised learning are generally based upon the current definition of emphysema subtypes, while unsupervised learning of texture patterns enables the objective discovery of possible new radiological emphysema subtypes. In this work, we use a variant of the Latent Dirichlet Allocation (LDA) model to discover lung macroscopic patterns (LMPs) in an unsupervised way from lung regions that encode emphysematous areas...
April 2017: Proceedings of the IEEE International Symposium on Biomedical Imaging: from Nano to Macro
https://www.readbyqxmd.com/read/28967214/defining-the-end-point-of-mastication-a-conceptual-model
#5
Eli M Gray-Stuart, Jim R Jones, John E Bronlund
The great risks of swallowing are choking and aspiration of food into the lungs. Both are rare in normal functioning humans, which is remarkable given the diversity of foods and the estimated 10 million swallows performed in a lifetime. Nevertheless, it remains a major challenge to define the food properties that are necessary to ensure a safe swallow. Here, the mouth is viewed as a well-controlled processor where mechanical sensory assessment occurs throughout the occlusion-circulation cycle of mastication...
October 2017: Journal of Texture Studies
https://www.readbyqxmd.com/read/28966837/a-methodology-for-texture-feature-based-quality-assessment-in-nucleus-segmentation-of-histopathology-image
#6
Si Wen, Tahsin M Kurc, Yi Gao, Tianhao Zhao, Joel H Saltz, Wei Zhu
CONTEXT: Image segmentation pipelines often are sensitive to algorithm input parameters. Algorithm parameters optimized for a set of images do not necessarily produce good-quality-segmentation results for other images. Even within an image, some regions may not be well segmented due to a number of factors, including multiple pieces of tissue with distinct characteristics, differences in staining of the tissue, normal versus tumor regions, and tumor heterogeneity. Evaluation of quality of segmentation results is an important step in image analysis...
2017: Journal of Pathology Informatics
https://www.readbyqxmd.com/read/28961108/low-dose-lung-ct-image-restoration-using-adaptive-prior-features-from-full-dose-training-database
#7
Yuanke Zhang, Junyan Rong, Hongbing Lu, Yuxiang Xing, Jing Meng
The valuable structure features in full-dose CT (FdCT) scans can be exploited as prior knowledge for low-dose CT (LdCT) imaging. However, lacking the capability to represent local characteristics of interested structures of the LdCT image adaptively may result in poor preservation of details/textures in LdCT image. This study aims to explore a novel prior knowledge retrieval and representation paradigm, called adaptive prior features assisted restoration algorithm (APFA), for the purpose of better restoration of the low-dose lung CT images by capturing local features from FdCT scans adaptively...
September 27, 2017: IEEE Transactions on Medical Imaging
https://www.readbyqxmd.com/read/28944403/prediction-of-disease-free-survival-by-the-pet-ct-radiomic-signature-in-non-small-cell-lung-cancer-patients-undergoing-surgery
#8
Margarita Kirienko, Luca Cozzi, Lidija Antunovic, Lisa Lozza, Antonella Fogliata, Emanuele Voulaz, Alexia Rossi, Arturo Chiti, Martina Sollini
PURPOSE: Radiomic features derived from the texture analysis of different imaging modalities e show promise in lesion characterisation, response prediction, and prognostication in lung cancer patients. The present study aimed to identify an images-based radiomic signature capable of predicting disease-free survival (DFS) in non-small cell lung cancer (NSCLC) patients undergoing surgery. METHODS: A cohort of 295 patients was selected. Clinical parameters (age, sex, histological type, tumour grade, and stage) were recorded for all patients...
September 24, 2017: European Journal of Nuclear Medicine and Molecular Imaging
https://www.readbyqxmd.com/read/28943697/localization-of-cardiac-volume-and-patient-features-in-inverse-geometry-x-ray-fluoroscopy
#9
Michael A Speidel, Jordan M Slagowski, David A P Dunkerley, Martin Wagner, Tobias Funk, Amish N Raval
The scanning-beam digital x-ray (SBDX) system is an inverse geometry x-ray fluoroscopy technology that performs real-time tomosynthesis at planes perpendicular to the source-detector axis. The live display is a composite image which portrays sharp features (e.g. coronary arteries) extracted from a 16 cm thick reconstruction volume. We present a method for automatically determining the position of the cardiac volume prior to acquisition of a coronary angiogram. In the algorithm, a single non-contrast frame is reconstructed over a 44 cm thickness using shift-and-add digital tomosynthesis...
February 2017: Proceedings of SPIE
https://www.readbyqxmd.com/read/28939952/2d-and-3d-texture-analysis-to-differentiate-brain-metastases-on-mr-images-proceed-with-caution
#10
Monika Béresová, Andrés Larroza, Estanislao Arana, József Varga, László Balkay, David Moratal
OBJECTIVE: To find structural differences between brain metastases of lung and breast cancer, computing their heterogeneity parameters by means of both 2D and 3D texture analysis (TA). MATERIALS AND METHODS: Patients with 58 brain metastases from breast (26) and lung cancer (32) were examined by MR imaging. Brain lesions were manually delineated by 2D ROIs on the slices of contrast-enhanced T1-weighted (CET1) images, and local binary patterns (LBP) maps were created from each region...
September 22, 2017: Magma
https://www.readbyqxmd.com/read/28934225/harmonizing-the-pixel-size-in-retrospective-computed-tomography-radiomics-studies
#11
Dennis Mackin, Xenia Fave, Lifei Zhang, Jinzhong Yang, A Kyle Jones, Chaan S Ng, Laurence Court
Consistent pixel sizes are of fundamental importance for assessing texture features that relate intensity and spatial information in radiomics studies. To correct for the effects of variable pixel sizes, we combined image resampling with Butterworth filtering in the frequency domain and tested the correction on computed tomography (CT) scans of lung cancer patients reconstructed 5 times with pixel sizes varying from 0.59 to 0.98 mm. One hundred fifty radiomics features were calculated for each preprocessing and field-of-view combination...
2017: PloS One
https://www.readbyqxmd.com/read/28929225/prediction-of-survival-by-texture-based-automated-quantitative-assessment-of-regional-disease-patterns-on-ct-in-idiopathic-pulmonary-fibrosis
#12
Sang Min Lee, Joon Beom Seo, Sang Young Oh, Tae Hoon Kim, Jin Woo Song, Sang Min Lee, Namkug Kim
OBJECTIVES: To retrospectively investigate whether the baseline extent and 1-year change in regional disease patterns on CT can predict survival of patients with idiopathic pulmonary fibrosis (IPF). METHODS: A total of 144 IPF patients with CT scans at the time of diagnosis and 1 year later were included. The extents of five regional disease patterns were quantified using an in-house texture-based automated system. The fibrosis score was defined as the sum of the extent of honeycombing and reticular opacity...
September 19, 2017: European Radiology
https://www.readbyqxmd.com/read/28898189/ct-texture-analysis-definitions-applications-biologic-correlates-and-challenges
#13
Meghan G Lubner, Andrew D Smith, Kumar Sandrasegaran, Dushyant V Sahani, Perry J Pickhardt
This review discusses potential oncologic and nononcologic applications of CT texture analysis ( CTTA CT texture analysis ), an emerging area of "radiomics" that extracts, analyzes, and interprets quantitative imaging features. CTTA CT texture analysis allows objective assessment of lesion and organ heterogeneity beyond what is possible with subjective visual interpretation and may reflect information about the tissue microenvironment. CTTA CT texture analysis has shown promise in lesion characterization, such as differentiating benign from malignant or more biologically aggressive lesions...
September 2017: Radiographics: a Review Publication of the Radiological Society of North America, Inc
https://www.readbyqxmd.com/read/28887836/a-novel-method-for-quantification-of-beam-s-eye-view-tumor-tracking-performance
#14
Yue-Houng Hu, Marios Myronakis, Joerg Rottmann, Adam Wang, Daniel Morf, Daniel Shedlock, Paul Baturin, Josh Star-Lack, Ross Berbeco
PURPOSE: In-treatment imaging using an electronic portal imaging device (EPID) can be used to confirm patient and tumor positioning. Real-time tumor tracking performance using current digital megavolt (MV) imagers is hindered by poor image quality. Novel EPID designs may help to improve quantum noise response, while also preserving the high spatial resolution of the current clinical detector. Recently investigated EPID design improvements include but are not limited to multi-layer imager (MLI) architecture, thick crystalline and amorphous scintillators, and phosphor pixilation and focusing...
September 9, 2017: Medical Physics
https://www.readbyqxmd.com/read/28884381/development-of-a-computer-aided-differential-diagnosis-system-to-distinguish-between-usual-interstitial-pneumonia-and-non-specific-interstitial-pneumonia-using-texture-and-shape-based-hierarchical-classifiers-on-hrct-images
#15
SangHoon Jun, BeomHee Park, Joon Beom Seo, SangMin Lee, Namkug Kim
A computer-aided differential diagnosis (CADD) system that distinguishes between usual interstitial pneumonia (UIP) and non-specific interstitial pneumonia (NSIP) using high-resolution computed tomography (HRCT) images was developed, and its results compared against the decision of a radiologist. Six local interstitial lung disease patterns in the images were determined, and 900 typical regions of interest were marked by an experienced radiologist. A support vector machine classifier was used to train and label the regions of interest of the lung parenchyma based on the texture and shape characteristics...
September 7, 2017: Journal of Digital Imaging: the Official Journal of the Society for Computer Applications in Radiology
https://www.readbyqxmd.com/read/28881840/tumor-heterogeneity-assessed-by-texture-analysis-on-contrast-enhanced-ct-in-lung-adenocarcinoma-association-with-pathologic-grade
#16
Ying Liu, Shichang Liu, Fangyuan Qu, Qian Li, Runfen Cheng, Zhaoxiang Ye
Objectives To investigate whether texture features on contrast-enhanced computed tomography (CECT) images of lung adenocarcinoma have association with pathologic grade. Methods A cohort of 148 patients with surgically operated adenocarcinoma was retrospectively reviewed. Fifty-four CT features of the primary lung tumor were extracted from CECT images using open-source 3D Slicer software; meanwhile, enhancement homogeneity was evaluated by two radiologists using visual assessment. Multivariate logistic regression analysis was performed to determine significant image indicator of pathologic grade...
August 8, 2017: Oncotarget
https://www.readbyqxmd.com/read/28872054/enhancement-of-multimodality-texture-based-prediction-models-via-optimization-of-pet-and-mr-image-acquisition-protocols-a-proof-of-concept
#17
Martin Vallières, Sébastien Laberge, André Diamant, Issam El Naqa
Texture-based radiomic models constructed from medical images have the potential to support cancer treatment management via personalized assessment of tumour aggressiveness. While the identification of stable texture features under varying imaging settings is crucial for the translation of radiomics analysis into routine clinical practice, we hypothesize in this work that a complementary optimization of image acquisition parameters prior to texture feature extraction could enhance the predictive performance of texture-based radiomic models...
September 5, 2017: Physics in Medicine and Biology
https://www.readbyqxmd.com/read/28869399/clinical-applications-of-textural-analysis-in-non-small-cell-lung-cancer
#18
Iain Phillips, Mazhar Ajaz, Veni Ezhil, Vineet Prakash, Sheaka Alobaidli, Sarah J McQuaid, Christopher South, James Scuffham, Andrew Nisbet, Philip Evans
Lung cancer is the leading cause of cancer mortality worldwide. Treatment pathways include regular cross-sectional imaging, generating large data sets which present intriguing possibilities for exploitation beyond standard visual interpretation. This additional data mining has been termed 'radiomics' and includes semantic and agnostic approaches. Texture Analysis (TA) is an example of the latter, and uses a range of mathematically derived features to describe an image or region of an image. Often TA is used to describe a suspected or known tumour...
September 4, 2017: British Journal of Radiology
https://www.readbyqxmd.com/read/28856247/quantitative-image-quality-comparison-of-reduced-and-standard-dose-dual-energy-multiphase-chest-abdomen-and-pelvis-ct
#19
Mario Buty, Ziyue Xu, Aaron Wu, Mingchen Gao, Chelyse Nelson, Georgios Z Papadakis, Uygar Teomete, Haydar Celik, Baris Turkbey, Peter Choyke, Daniel J Mollura, Ulas Bagci, Les R Folio
We present a new image quality assessment method for determining whether reducing radiation dose impairs the image quality of computed tomography (CT) in qualitative and quantitative clinical analyses tasks. In this Institutional Review Board-exempt study, we conducted a review of 50 patients (male, 22; female, 28) who underwent reduced-dose CT scanning on the first follow-up after standard-dose multiphase CT scanning. Scans were for surveillance of von Hippel-Lindau disease (N = 26) and renal cell carcinoma (N = 10)...
June 2017: Tomography: a Journal for Imaging Research
https://www.readbyqxmd.com/read/28844845/lepidic-predominant-pulmonary-lesions-lpl-ct-based-distinction-from-more-invasive-adenocarcinomas-using-3d-volumetric-density-and-first-order-ct-texture-analysis
#20
Jeffrey B Alpert, Henry Rusinek, Jane P Ko, Bari Dane, Harvey I Pass, Bernard K Crawford, Amy Rapkiewicz, David P Naidich
RATIONALE AND OBJECTIVES: This study aimed to differentiate pathologically defined lepidic predominant lesions (LPL) from more invasive adenocarcinomas (INV) using three-dimensional (3D) volumetric density and first-order texture histogram analysis of surgically excised stage 1 lung adenocarcinomas. MATERIALS AND METHODS: This retrospective study was institutional review board approved and Health Insurance Portability and Accountability Act compliant. Sixty-four cases of pathologically proven stage 1 lung adenocarcinoma surgically resected between September 2006 and October 2015, including LPL (n = 43) and INV (n = 21), were evaluated using high-resolution computed tomography...
August 24, 2017: Academic Radiology
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