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Texture Lung

Guohui Wei, He Ma, Wei Qian, Min Qiu
PURPOSE: To develop a new algorithm to measure the similarity between the query lung mass and reference lung mass data set for content-based medical image retrieval (CBMIR). METHODS: A lung mass data set including 746 mass regions of interest (ROIs) was assembled. Among them, 375 ROIs depicted malignant lesions and 371 depicted benign lesions. Each mass ROI is represented by a vector of 26 texture features. A kernel function was employed to map the original data in input space to a feature space...
December 2016: Medical Physics
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
Motahare Soufi, Alireza Kamali-Asl, Parham Geramifar, Arman Rahmim
PURPOSE: Determination of intra-tumor high-uptake area using 2-deoxy-2-[(18)F]fluoro-D-glucose ([(18)F]FDG) positron emission tomography (PET) imaging is an important consideration for dose painting in radiation treatment applications. The aim of our study was to develop a framework towards automated segmentation and labeling of homogeneous vs. heterogeneous tumors in clinical lung [(18)F]FDG-PET with the capability of intra-tumor high-uptake region delineation. PROCEDURES: We utilized and extended a fuzzy random walk PET tumor segmentation algorithm to delineate intra-tumor high-uptake areas...
October 21, 2016: Molecular Imaging and Biology: MIB: the Official Publication of the Academy of Molecular Imaging
Margaret L Salisbury, David A Lynch, Edwin J R van Beek, Ella A Kazerooni, Junfeng Guo, Meng Xia, Susan Murray, Kevin J Anstrom, Eric Yow, Fernando J Martinez, Eric A Hoffman, Kevin R Flaherty
RATIONALE: Adaptive Multiple Features Method (AMFM) lung texture analysis software recognizes high-resolution computed tomography (HRCT) patterns. OBJECTIVES: We evaluated AMFM and visual quantification of HRCT patterns and their relationship with disease progression in Idiopathic Pulmonary Fibrosis. METHODS: IPF patients in a clinical trial of prednisone, azathioprine, and N-acetylcysteine underwent HRCT at study start and finish. Proportion of lung occupied by ground glass, ground glass-reticular (GGR), honeycombing, emphysema, and normal were measured by AMFM and 3 radiologists, documenting baseline disease extent and post-baseline change...
October 21, 2016: American Journal of Respiratory and Critical Care Medicine
Marie-Charlotte Desseroit, Florent Tixier, Wolfgang Andreas Weber, Barry Alan Siegel, Catherine Cheze Le Rest, Dimitris Visvikis, Mathieu Hatt
PURPOSE: The main purpose of this study was to assess the reliability of shape and heterogeneity features in both PET and low-dose CT components of PET/CT. A secondary objective was to investigate the impact of image quantization. MATERIAL AND METHODS: A HIPAA-compliant secondary analysis of deidentified prospectively acquired PET/CT test-retest datasets of 74 patients from multi-center Merck and ACRIN trials was performed. Metabolically active volumes were automatically delineated on PET with Fuzzy Locally Adaptive Bayesian (FLAB) algorithm...
October 20, 2016: Journal of Nuclear Medicine: Official Publication, Society of Nuclear Medicine
Pol Cirujeda, Yashin Dicente Cid, Henning Muller, Daniel Rubin, Todd A Aguilera, Billy W Loo, Maximilian Diehn, Xavier Binefa, Adrien Depeursinge
This paper proposes a novel imaging biomarker of lung cancer relapse from 3-D texture analysis of CT images. Three-dimensional morphological nodular tissue properties are described in terms of 3-D Riesz-wavelets. The responses of the latter are aggregated within nodular regions by means of feature covariances, which leverage rich intra- and inter- variations of the feature space dimensions. When compared to the classical use of the average for feature aggregation, feature covariances preserve spatial co-variations between features...
July 18, 2016: IEEE Transactions on Medical Imaging
Attila Forgacs, Hermann Pall Jonsson, Magnus Dahlbom, Freddie Daver, Matthew D DiFranco, Gabor Opposits, Aron K Krizsan, Ildiko Garai, Johannes Czernin, Jozsef Varga, Lajos Tron, Laszlo Balkay
Textural analysis might give new insights into the quantitative characterization of metabolically active tumors. More than thirty textural parameters have been investigated in former F18-FDG studies already. The purpose of the paper is to declare basic requirements as a selection strategy to identify the most appropriate heterogeneity parameters to measure textural features. Our predefined requirements were: a reliable heterogeneity parameter has to be volume independent, reproducible, and suitable for expressing quantitatively the degree of heterogeneity...
2016: PloS One
Ashis Kumar Dhara, Sudipta Mukhopadhyay, Anirvan Dutta, Mandeep Garg, Niranjan Khandelwal
Visual information of similar nodules could assist the budding radiologists in self-learning. This paper presents a content-based image retrieval (CBIR) system for pulmonary nodules, observed in lung CT images. The reported CBIR systems of pulmonary nodules cannot be put into practice as radiologists need to draw the boundary of nodules during query formation and feature database creation. In the proposed retrieval system, the pulmonary nodules are segmented using a semi-automated technique, which requires a seed point on the nodule from the end-user...
September 27, 2016: Journal of Digital Imaging: the Official Journal of the Society for Computer Applications in Radiology
J Chalubinska-Fendler, L Karolczak, W Fendler, J Bury, M Spych, A Materka, J Fijuth
No abstract text is available yet for this article.
October 1, 2016: International Journal of Radiation Oncology, Biology, Physics
P R Patel, E Schreibmann, A I Sutter, D Whitaker, J Switchenko, W J Curran, K A Higgins
No abstract text is available yet for this article.
October 1, 2016: International Journal of Radiation Oncology, Biology, Physics
J O Letham, B S Erdal, X Mo, S Salamekh, A Ayan, T M Williams, K E Haglund, L M Prevedello, J G Bazan, R D White, M X Welliver
No abstract text is available yet for this article.
October 1, 2016: International Journal of Radiation Oncology, Biology, Physics
Ying Liu, Yoganand Balagurunathan, Thomas Atwater, Sanja Antic, Qian Li, Ronald C Walker, Gary Smith, Pierre P Massion, Matthew B Schabath, Robert J Gillies
PURPOSE: We propose a systematic methodology to quantify incidentally identified pulmonary nodules based on observed radiological traits (semantics) quantified on a point scale and a machine learning method using these data to predict cancer status. MATERIALS AND METHODS: We investigated 172 patients who had low-dose computed tomography (LDCT) images, with 102 and 70 patients grouped into training and validation cohorts, respectively. On the images, 24 radiological traits were systematically scored and a linear classifier was built to relate the traits to malignant status...
September 23, 2016: Clinical Cancer Research: An Official Journal of the American Association for Cancer Research
Shoshana B Ginsburg, Jason Zhao, Stephen Humphries, Sungshick Jou, Kunihiro Yagihashi, David A Lynch, Joyce D Schroeder
RATIONALE AND OBJECTIVES: The effect of smoking cessation on centrilobular emphysema (CLE) and centrilobular nodularity (CN), two manifestations of smoking-related lung injury on computed tomography (CT) images, has not been clarified. The objective of this study is to leverage texture analysis to investigate differences in extent of CLE and CN between current and former smokers. MATERIALS AND METHODS: Chest CT scans from 350 current smokers, 401 former smokers, and 25 control subjects were obtained from the multicenter COPDGene Study, a Health Insurance Portability and Accountability Act-compliant study approved by the institutional review board of each participating clinical study center...
November 2016: Academic Radiology
José Raniery Ferreira, Paulo Mazzoncini de Azevedo-Marques, Marcelo Costa Oliveira
PURPOSE: Lung cancer is the leading cause of cancer-related deaths in the world. Its diagnosis is a challenge task to specialists due to several aspects on the classification of lung nodules. Therefore, it is important to integrate content-based image retrieval methods on the lung nodule classification process, since they are capable of retrieving similar cases from databases that were previously diagnosed. However, this mechanism depends on extracting relevant image features in order to obtain high efficiency...
August 23, 2016: International Journal of Computer Assisted Radiology and Surgery
Hyungjin Kim, Chang Min Park, Sang Joon Park, Yong Sub Song, Jong Hyuk Lee, Eui Jin Hwang, Jin Mo Goo
OBJECTIVES: The aim of this study was to describe the temporal changes of various texture features extracted from pulmonary nodules on dynamic contrast-enhanced computed tomography (DCE-CT) and to compare the feature values among multiple scanning time points. We also aimed to analyze the variability of texture features across multiple scan delay times. MATERIALS AND METHODS: This retrospective study was approved by the institutional review board of Seoul National University Hospital with waiver of patients' informed consent...
September 2016: Investigative Radiology
P Lo, S Young, H J Kim, M S Brown, M F McNitt-Gray
PURPOSE: To investigate the effects of dose level and reconstruction method on density and texture based features computed from CT lung nodules. METHODS: This study had two major components. In the first component, a uniform water phantom was scanned at three dose levels and images were reconstructed using four conventional filtered backprojection (FBP) and four iterative reconstruction (IR) methods for a total of 24 different combinations of acquisition and reconstruction conditions...
August 2016: Medical Physics
Mingzan Zhuang, Rudi A J O Dierckx, Habib Zaidi
PURPOSE: Although positron emission tomography (PET) images have shown potential to improve the accuracy of targeting in radiation therapy planning and assessment of response to treatment, the boundaries of tumors are not easily distinguishable from surrounding normal tissue owing to the low spatial resolution and inherent noisy characteristics of PET images. The objective of this study is to develop a generic and robust method for automatic delineation of tumor volumes using an active contour model and to evaluate its performance using phantom and clinical studies...
August 2016: Medical Physics
Satoshi Ikeda, Akimasa Sekine, Tomohisa Baba, Koji Okudela, Tae Iwasawa, Fumikazu Sakai, Kenji Notohara, Kenichi Ohashi, Tamiko Takemura, Takashi Ogura
AIMS: There have been few reports on immunoglobulin-G4 (IgG4)-related interstitial pneumonia (IP), and its clinical features remain unclear. The objective of this study was to assess whether IP with marked IgG4-positive plasma cell infiltration without extrathoracic lesions of IgG4-related disease (RD) should be diagnosed as a subtype of IgG4-RD or a separate entity. METHODS AND RESULTS: All consecutive patients with surgical lung biopsy-proven idiopathic IP with an IgG4/IgG-positive cell ratio of >40% and >50 IgG4(+) plasma cells in a high-power field without extrathoracic lesions of IgG4-RD were reviewed retrospectively...
August 2, 2016: Histopathology
José Raniery Ferreira Junior, Marcelo Costa Oliveira, Paulo Mazzoncini de Azevedo-Marques
Lung cancer is the leading cause of cancer-related deaths in the world, and its main manifestation is pulmonary nodules. Detection and classification of pulmonary nodules are challenging tasks that must be done by qualified specialists, but image interpretation errors make those tasks difficult. In order to aid radiologists on those hard tasks, it is important to integrate the computer-based tools with the lesion detection, pathology diagnosis, and image interpretation processes. However, computer-aided diagnosis research faces the problem of not having enough shared medical reference data for the development, testing, and evaluation of computational methods for diagnosis...
December 2016: Journal of Digital Imaging: the Official Journal of the Society for Computer Applications in Radiology
Thessa T J P Kockelkorn, Pim A de Jong, Cornelia M Schaefer-Prokop, Rianne Wittenberg, Audrey M Tiehuis, Hester A Gietema, Jan C Grutters, Max A Viergever, Bram van Ginneken
The textural patterns in the lung parenchyma, as visible on computed tomography (CT) scans, are essential to make a correct diagnosis in interstitial lung disease. We developed one automatic and two interactive protocols for classification of normal and seven types of abnormal lung textures. Lungs were segmented and subdivided into volumes of interest (VOIs) with homogeneous texture using a clustering approach. In the automatic protocol, VOIs were classified automatically by an extra-trees classifier that was trained using annotations of VOIs from other CT scans...
August 21, 2016: Physics in Medicine and Biology
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