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https://www.readbyqxmd.com/read/28169141/measuring-interobserver-disagreement-in-rating-diagnostic-characteristics-of-pulmonary-nodule-using-the-lung-imaging-database-consortium-and-image-database-resource-initiative
#1
Hongli Lin, Changxing Huang, Weisheng Wang, Jiawei Luo, Xuedong Yang, Yuling Liu
RATIONALE AND OBJECTIVES: The purpose of this study was to measure and analyze interobserver disagreement in rating diagnostic characteristics of pulmonary nodules on computed tomography scans using the Lung Imaging Database Consortium and Image Database Resource Initiative (LIDC/IDRI) database, and then to provide investigators with understanding the variability in rating diagnostic characteristics among radiologists. MATERIALS AND METHODS: A histogram-based accumulated nodule-level approach is proposed to measure interobserver disagreement in rating diagnostic characteristics of pulmonary nodules among radiologists...
February 3, 2017: Academic Radiology
https://www.readbyqxmd.com/read/28166511/a-solitary-feature-based-lung-nodule-detection-approach-for-chest-x-ray-radiographs
#2
Xuechen Li, Linlin Shen, Suhuai Luo
Lung cancer is one of the most deadly diseases. It has a high death rate and its incidence rate has been increasing all over the world. Lung cancer appears as a solitary nodule in chest x-ray radiograph (CXR). Therefore, lung nodule detection in CXR could have a significant impact on early detection of lung cancer. Radiologists define a lung nodule in chest x-ray radiographs as "solitary white nodule-like blob". However, the solitary feature has not been employed for lung nodule detection before. In this paper, a solitary feature-based lung nodule detection method was proposed...
January 31, 2017: IEEE Journal of Biomedical and Health Informatics
https://www.readbyqxmd.com/read/28149958/radiomics-of-lung-nodules-a-multi-institutional-study-of-robustness-and-agreement-of-quantitative-imaging-features
#3
Jayashree Kalpathy-Cramer, Artem Mamomov, Binsheng Zhao, Lin Lu, Dmitry Cherezov, Sandy Napel, Sebastian Echegaray, Daniel Rubin, Michael McNitt-Gray, Pechin Lo, Jessica C Sieren, Johanna Uthoff, Samantha K N Dilger, Brandan Driscoll, Ivan Yeung, Lubomir Hadjiiski, Kenny Cha, Yoganand Balagurunathan, Robert Gillies, Dmitry Goldgof
Radiomics is to provide quantitative descriptors of normal and abnormal tissues during classification and prediction tasks in radiology and oncology. Quantitative Imaging Network members are developing radiomic "feature" sets to characterize tumors, in general, the size, shape, texture, intensity, margin, and other aspects of the imaging features of nodules and lesions. Efforts are ongoing for developing an ontology to describe radiomic features for lung nodules, with the main classes consisting of size, local and global shape descriptors, margin, intensity, and texture-based features, which are based on wavelets, Laplacian of Gaussians, Law's features, gray-level co-occurrence matrices, and run-length features...
December 2016: Tomography: a Journal for Imaging Research
https://www.readbyqxmd.com/read/28130689/comparison-of-machine-learning-methods-for-classifying-mediastinal-lymph-node-metastasis-of-non-small-cell-lung-cancer-from-18-f-fdg-pet-ct-images
#4
Hongkai Wang, Zongwei Zhou, Yingci Li, Zhonghua Chen, Peiou Lu, Wenzhi Wang, Wanyu Liu, Lijuan Yu
BACKGROUND: This study aimed to compare one state-of-the-art deep learning method and four classical machine learning methods for classifying mediastinal lymph node metastasis of non-small cell lung cancer (NSCLC) from (18)F-FDG PET/CT images. Another objective was to compare the discriminative power of the recently popular PET/CT texture features with the widely used diagnostic features such as tumor size, CT value, SUV, image contrast, and intensity standard deviation. The four classical machine learning methods included random forests, support vector machines, adaptive boosting, and artificial neural network...
December 2017: EJNMMI Research
https://www.readbyqxmd.com/read/28129196/edge-preserving-depth-map-upsampling-by-joint-trilateral-filter
#5
Kai-Han Lo, Yu-Chiang Frank Wang, Kai-Lung Hua
Compared to the color images, their associated depth images captured by the RGB-D sensors are typically with lower resolution. The task of depth map super-resolution (SR) aims at increasing the resolution of the range data by utilizing the high-resolution (HR) color image, while the details of the depth information are to be properly preserved. In this paper, we present a joint trilateral filtering (JTF) algorithm for depth image SR. The proposed JTF first observes context information from the HR color image...
January 24, 2017: IEEE Transactions on Cybernetics
https://www.readbyqxmd.com/read/28114048/multi-source-transfer-learning-with-convolutional-neural-networks-for-lung-pattern-analysis
#6
Stergios Christodoulidis, Marios Anthimopoulos, Lukas Ebner, Andreas Christe, Stavroula Mougiakakou
Early diagnosis of interstitial lung diseases is crucial for their treatment, but even experienced physicians find it difficult, as their clinical manifestations are similar. In order to assist with the diagnosis, computer-aided diagnosis (CAD) systems have been developed. These commonly rely on a fixed scale classifier that scans CT images, recognizes textural lung patterns and generates a map of pathologies. In a previous study, we proposed a method for classifying lung tissue patterns using a deep convolutional neural network (CNN), with an architecture designed for the specific problem...
December 7, 2016: IEEE Journal of Biomedical and Health Informatics
https://www.readbyqxmd.com/read/28113928/automatic-scoring-of-multiple-semantic-attributes-with-multi-task-feature-leverage-a-study-on-pulmonary-nodules-in-ct-images
#7
Sihong Chen, Jing Qin, Xing Ji, Baiying Lei, Tianfu Wang, Dong Ni, Jie-Zhi Cheng
The gap between the computational and semantic features is the one of major factors that bottlenecks the computer-aided diagnosis (CAD) performance from clinical usage. To bridge this gap, we exploit three multi-task learning (MTL) schemes to leverage heterogeneous computational features derived from deep learning models of stacked denoising autoencoder (SDAE) and convolutional neural network (CNN), as well as hand-crafted Haar-like and HoG features, for the description of 9 semantic features for lung nodules in CT images...
November 16, 2016: IEEE Transactions on Medical Imaging
https://www.readbyqxmd.com/read/28097934/automatic-and-quantitative-measurement-of-laryngeal-video-stroboscopic-images
#8
Chung-Feng Jeffrey Kuo, Joseph Kuo, Shang-Wun Hsiao, Chi-Lung Lee, Jih-Chin Lee, Bo-Han Ke
The laryngeal video stroboscope is an important instrument for physicians to analyze abnormalities and diseases in the glottal area. Stroboscope has been widely used around the world. However, without quantized indices, physicians can only make subjective judgment on glottal images. We designed a new laser projection marking module and applied it onto the laryngeal video stroboscope to provide scale conversion reference parameters for glottal imaging and to convert the physiological parameters of glottis. Image processing technology was used to segment the important image regions of interest...
January 2017: Proceedings of the Institution of Mechanical Engineers. Part H, Journal of Engineering in Medicine
https://www.readbyqxmd.com/read/28068363/quantitative-computed-tomography-features-for-predicting-tumor-recurrence-in-patients-with-surgically-resected-adenocarcinoma-of-the-lung
#9
Hyun Jung Koo, Yu Sub Sung, Woo Hyun Shim, Hai Xu, Chang-Min Choi, Hyeong Ryul Kim, Jung Bok Lee, Mi Young Kim
PURPOSE: The purpose of this study was to determine if preoperative quantitative computed tomography (CT) features including texture and histogram analysis measurements are associated with tumor recurrence in patients with surgically resected adenocarcinoma of the lung. METHODS: The study included 194 patients with surgically resected lung adenocarcinoma who underwent preoperative CT between January 2013 and December 2013. Quantitative CT feature analysis of the lung adenocarcinomas were performed using in-house software based on plug-in package for ImageJ...
2017: PloS One
https://www.readbyqxmd.com/read/28048907/su-f-r-46-predicting-distant-failure-in-lung-sbrt-using-multi-objective-radiomics-model
#10
Z Zhou, M Folkert, P Iyengar, Y Zhang, J Wang
PURPOSE: To predict distant failure in lung stereotactic body radiation therapy (SBRT) in early stage non-small cell lung cancer (NSCLC) by using a new multi-objective radiomics model. METHODS: Currently, most available radiomics models use the overall accuracy as the objective function. However, due to data imbalance, a single object may not reflect the performance of a predictive model. Therefore, we developed a multi-objective radiomics model which considers both sensitivity and specificity as the objective functions simultaneously...
June 2016: Medical Physics
https://www.readbyqxmd.com/read/28048420/su-f-r-27-use-local-shape-descriptor-based-on-geodesic-distance-to-predict-survival-in-non-small-cell-lung-cancer-after-radiotherapy
#11
H Zhang, L Yan, K Huang, F Kong, J Jin
PURPOSE: The shape of the Positron Emission Tomography (PET) image represents the heterogeneity of tumor growth in various directions, and thus could be associated with tumor malignancy. We have proposed a median geodesic distance (MGD) to represent the local complexity of the shape and use a normalized MGD (NMGD) to quantify the shape, and found a potential correlation of NMGD to survival in a 20-patient pilot study. This study was to verify the finding in a larger patient cohort. METHODS: Geodesic distance of two vertices on a surface is defined as the shortest path on the surface connecting the two vertices...
June 2016: Medical Physics
https://www.readbyqxmd.com/read/28048226/su-f-r-35-repeatability-of-texture-features-in-t1-and-t2-weighted-mr-images
#12
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/28048213/mo-de-207a-09-low-dose-ct-image-reconstruction-via-learning-from-different-patient-normal-dose-images
#13
H Han, L Xing, Z Liang
PURPOSE: To investigate a novel low-dose CT (LdCT) image reconstruction strategy for lung CT imaging in radiation therapy. METHODS: The proposed approach consists of four steps: (1) use the traditional filtered back-projection (FBP) method to reconstruct the LdCT image; (2) calculate structure similarity (SSIM) index between the FBP-reconstructed LdCT image and a set of normal-dose CT (NdCT) images, and select the NdCT image with the highest SSIM as the learning source; (3) segment the NdCT source image into lung and outside tissue regions via simple thresholding, and adopt multiple linear regression to learn high-order Markov random field (MRF) pattern for each tissue region in the NdCT source image; (4) segment the FBP-reconstructed LdCT image into lung and outside regions as well, and apply the learnt MRF prior in each tissue region for statistical iterative reconstruction of the LdCT image following the penalized weighted least squares (PWLS) framework...
June 2016: Medical Physics
https://www.readbyqxmd.com/read/28048179/su-f-r-54-ct-texture-based-early-tumor-treatment-response-assessment-during-radiation-therapy-delivery-small-cell-versus-non-small-cell-lung-cancers
#14
J Paul, E Gore, X Li
PURPOSE: Tumor treatment response may potentially be assessed during radiation therapy (RT) by analyzing changes in CT-textures. We investigated the different early RT-responses between small cell (SCLC) and non-small cell lung cancer (NSCLC) as assessed by CT-texture. METHODS: Daily diagnostic-quality CT acquired during routine CT-guided RT using a CT-on-Rails for 13-NSCLC and 5-SCLC patients were analyzed. These patient had ages ranging from 45-78 and 38-63 years, respectively, for NSCLC and SCLC groups, and tumor-stages ranging from T2-T4, and were treated with either RT or chemotherapy and RT with 45-66Gy/ 20-34 fractions...
June 2016: Medical Physics
https://www.readbyqxmd.com/read/28048125/su-f-r-31-identification-of-robust-normal-lung-ct-texture-features-for-the-prediction-of-radiation-induced-lung-disease
#15
W Choi, S Riyahi, W Lu
PURPOSE: Normal lung CT texture features have been used for the prediction of radiation-induced lung disease (radiation pneumonitis and radiation fibrosis). For these features to be clinically useful, they need to be relatively invariant (robust) to tumor size and not correlated with normal lung volume. METHODS: The free-breathing CTs of 14 lung SBRT patients were studied. Different sizes of GTVs were simulated with spheres placed at the upper lobe and lower lobe respectively in the normal lung (contralateral to tumor)...
June 2016: Medical Physics
https://www.readbyqxmd.com/read/28048090/su-g-bra-06-quantification-of-tracking-performance-of-a-multi-layer-electronic-portal-imaging-device
#16
Y Hu, J Rottmann, M Myronakis, R Berbeco
PURPOSE: The purpose of this study was to quantify the improvement in tumor tracking, with and without fiducial markers, afforded by employing a multi-layer (MLI) electronic portal imaging device (EPID) over the current state-of-the-art, single-layer, digital megavolt imager (DMI) architecture. METHODS: An ideal observer signal-to-noise ratio (d') approach was used to quantify the ability of an MLI EPID and a current, state-of-the-art DMI EPID to track lung tumors from the treatment beam's-eye-view...
June 2016: Medical Physics
https://www.readbyqxmd.com/read/28047655/su-f-r-24-identifying-prognostic-imaging-biomarkers-in-early-stage-lung-cancer-using-radiomics
#17
X Zeng, J Wu, Y Cui, H Gao, R Li
PURPOSE: Patients diagnosed with early stage lung cancer have favorable outcomes when treated with surgery or stereotactic radiotherapy. However, a significant proportion (∼20%) of patients will develop metastatic disease and eventually die of the disease. The purpose of this work is to identify quantitative imaging biomarkers from CT for predicting overall survival in early stage lung cancer. METHODS: In this institutional review board-approved HIPPA-compliant retrospective study, we retrospectively analyzed the diagnostic CT scans of 110 patients with early stage lung cancer...
June 2016: Medical Physics
https://www.readbyqxmd.com/read/28047623/su-f-r-13-decoding-18f-fdg-uptake-heterogeneity-for-primary-and-lymphoma-tumors-by-using-texture-analysis-in-pet-images
#18
C Ma, Y Yin
PURPOSE: To explore 18F-FDG uptake heterogeneity of primary tumor and lymphoma tumor by texture features of PET image and quantify the heterogeneity difference between primary tumor and lymphoma tumor. METHODS: 18 patients with primary tumor and lymphoma tumor in lung cancer were enrolled. All patients underwent whole-body 18F-FDG PET/CT scans before treatment. Texture features, based on Gray-level Co-occurrence Matrix, second and high order matrices are extracted from code using MATLAB software to quantify 18F-FDG uptake heterogeneity...
June 2016: Medical Physics
https://www.readbyqxmd.com/read/28047538/su-f-r-20-image-texture-features-correlate-with-time-to-local-failure-in-lung-sbrt-patients
#19
M Andrews, M Abazeed, N Woody, K Stephans, G Videtic, P Xia, T Zhuang
PURPOSE: To explore possible correlation between CT image-based texture and histogram features and time-to-local-failure in early stage non-small cell lung cancer (NSCLC) patients treated with stereotactic body radiotherapy (SBRT). METHODS AND MATERIALS: From an IRB-approved lung SBRT registry for patients treated between 2009-2013 we selected 48 (20 male, 28 female) patients with local failure. Median patient age was 72.3±10.3 years. Mean time to local failure was 15 ± 7...
June 2016: Medical Physics
https://www.readbyqxmd.com/read/28047431/su-f-r-51-radiomics-in-ct-perfusion-maps-of-head-and-neck-cancer
#20
M Nesteruk, O Riesterer, R Bundschuh, P Veit-Haibach, M Huellner, G Studer, S Stieb, S Glatz, M Pruschy, M Guckenberger, S Tanadini-Lang
PURPOSE: The aim of this study was to test the predictive value of radiomics features of CT perfusion (CTP) for tumor control, based on a preselection of radiomics features in a robustness study. METHODS: 11 patients with head and neck cancer (HNC) and 11 patients with lung cancer were included in the robustness study to preselect stable radiomics parameters. Data from 36 HNC patients treated with definitive radiochemotherapy (median follow-up 30 months) was used to build a predictive model based on these parameters...
June 2016: Medical Physics
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