Computerized detection of pulmonary nodules in chest radiographs based on morphological features and wavelet snake model.

Abstract:

:We have developed a new computer-aided diagnosis scheme for automated detection of lung nodules in digital chest radiographs based on a combination of morphological features and the wavelet snake. In our scheme, two processes were applied in parallel to reduce the false-positive detections after initial nodule candidates were selected. One process consisted of adaptive filtering for enhancement of nodules and suppression of normal lung structures, followed by extraction of conventional morphological features. The other process consisted of a novel approach for elimination of false positives called the edge-guided wavelet snake model. In the latter process, multiscale edges of the candidate nodules were extracted to yield parts of the nodule boundaries. A wavelet snake was then used for fitting of these multiscale edges for approximation of the true boundaries of nodules. A boundary feature called the weighted overlap between the snake and the multiscale edges was calculated and used for elimination of false positives. Finally, the weighted overlap and the morphological features were combined by use of an artificial neural network for efficient reduction of false positives. Our scheme was applied to a publicly available database of digital chest images for pulmonary nodules. Receiver operating characteristic analysis was employed for evaluation of the performance of each process in the scheme. The combined features yielded a large reduction of false positives, and thus achieved a high performance in discriminating between true and false positives. These results show that our new method, in particular the false-positive reduction method based on the wavelet snake, is effective in improving the performance of a computerized scheme for detection of pulmonary nodules in chest radiographs.

journal_name

Med Image Anal

journal_title

Medical image analysis

authors

Keserci B,Yoshida H

doi

10.1016/s1361-8415(02)00064-6

subject

Has Abstract

pub_date

2002-12-01 00:00:00

pages

431-47

issue

4

eissn

1361-8415

issn

1361-8423

pii

S1361-8415(02)00064-6

journal_volume

6

pub_type

杂志文章
  • Context specific descriptors for tracking deforming tissue.

    abstract::In minimally invasive surgery, deployment of motion compensation, dynamic active constraints and adaptive intra-operative guidance require accurate estimation of deforming tissue in 3D. To this end, the use of vision-based techniques is advantageous in that it does not require the integration of additional hardware to...

    journal_title:Medical image analysis

    pub_type: 杂志文章

    doi:10.1016/j.media.2011.02.010

    authors: Mountney P,Yang GZ

    更新日期:2012-04-01 00:00:00

  • Image guidance in orthopaedics and traumatology: A historical perspective.

    abstract::In this note we summarize the history of computer aided surgery in orthopaedics and traumatology from the end of the nineteenth century to currently observable future trends. We concentrate on the two major components of such systems, pre-operative planning and intra-operative execution. The evolution of the necessary...

    journal_title:Medical image analysis

    pub_type: 社论

    doi:10.1016/j.media.2016.06.033

    authors: Székely G,Nolte LP

    更新日期:2016-10-01 00:00:00

  • Suite of meshless algorithms for accurate computation of soft tissue deformation for surgical simulation.

    abstract::The ability to predict patient-specific soft tissue deformations is key for computer-integrated surgery systems and the core enabling technology for a new era of personalized medicine. Element-Free Galerkin (EFG) methods are better suited for solving soft tissue deformation problems than the finite element method (FEM...

    journal_title:Medical image analysis

    pub_type: 杂志文章

    doi:10.1016/j.media.2019.06.004

    authors: Joldes G,Bourantas G,Zwick B,Chowdhury H,Wittek A,Agrawal S,Mountris K,Hyde D,Warfield SK,Miller K

    更新日期:2019-08-01 00:00:00

  • DT-MRI denoising and neuronal fiber tracking.

    abstract::Diffusion tensor imaging can provide the fundamental information required for viewing structural connectivity. However, robust and accurate acquisition and processing algorithms are needed to accurately map the nerve connectivity. In this paper, we present a novel algorithm for extracting and visualizing the fiber tra...

    journal_title:Medical image analysis

    pub_type: 杂志文章

    doi:10.1016/j.media.2003.12.001

    authors: McGraw T,Vemuri BC,Chen Y,Rao M,Mareci T

    更新日期:2004-06-01 00:00:00

  • An accurate, fast and robust method to generate patient-specific cubic Hermite meshes.

    abstract::In-silico continuum simulations of organ and tissue scale physiology often require a discretisation or mesh of the solution domain. Cubic Hermite meshes provide a smooth representation of anatomy that is well-suited for simulating large deformation mechanics. Models of organ mechanics and deformation have demonstrated...

    journal_title:Medical image analysis

    pub_type: 杂志文章

    doi:10.1016/j.media.2011.06.010

    authors: Lamata P,Niederer S,Nordsletten D,Barber DC,Roy I,Hose DR,Smith N

    更新日期:2011-12-01 00:00:00

  • Improved fidelity of brain microstructure mapping from single-shell diffusion MRI.

    abstract::Diffusion weighted imaging (DWI) is sensitive to alterations in the diffusion of water molecules caused by microstructural barriers. Different microstructural compartments are characterized by differences in DWI signal. Diffusion tensor imaging conflates the signal from these compartments into a single tensor, which p...

    journal_title:Medical image analysis

    pub_type: 杂志文章

    doi:10.1016/j.media.2015.10.004

    authors: Taquet M,Scherrer B,Boumal N,Peters JM,Macq B,Warfield SK

    更新日期:2015-12-01 00:00:00

  • Real-time image-based rigid registration of three-dimensional ultrasound.

    abstract::Registration of three-dimensional ultrasound (3DUS) volumes is necessary in several applications, such as when stitching volumes to expand the field of view or when stabilizing a temporal sequence of volumes to cancel out motion of the probe or anatomy. Current systems that register 3DUS volumes either use external tr...

    journal_title:Medical image analysis

    pub_type: 杂志文章

    doi:10.1016/j.media.2011.10.004

    authors: Schneider RJ,Perrin DP,Vasilyev NV,Marx GR,Del Nido PJ,Howe RD

    更新日期:2012-02-01 00:00:00

  • Wavelet optimization for content-based image retrieval in medical databases.

    abstract::We propose in this article a content-based image retrieval (CBIR) method for diagnosis aid in medical fields. In the proposed system, images are indexed in a generic fashion, without extracting domain-specific features: a signature is built for each image from its wavelet transform. These image signatures characterize...

    journal_title:Medical image analysis

    pub_type: 杂志文章

    doi:10.1016/j.media.2009.11.004

    authors: Quellec G,Lamard M,Cazuguel G,Cochener B,Roux C

    更新日期:2010-04-01 00:00:00

  • Automated localization of breast cancer in DCE-MRI.

    abstract::Dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) is increasingly being used for the detection and diagnosis of breast cancer. Compared to mammography, DCE-MRI provides higher sensitivity, however its specificity is variable. Moreover, DCE-MRI data analysis is time consuming and depends on reader expertis...

    journal_title:Medical image analysis

    pub_type: 杂志文章

    doi:10.1016/j.media.2014.12.001

    authors: Gubern-Mérida A,Martí R,Melendez J,Hauth JL,Mann RM,Karssemeijer N,Platel B

    更新日期:2015-02-01 00:00:00

  • Cardiac function estimation from MRI using a heart model and data assimilation: advances and difficulties.

    abstract::In this paper, we present a framework to estimate local ventricular myocardium contractility using clinical MRI, a heart model and data assimilation. First, we build a generic anatomical model of the ventricles including muscle fibre orientations and anatomical subdivisions. Then, this model is deformed to fit a clini...

    journal_title:Medical image analysis

    pub_type: 杂志文章

    doi:10.1016/j.media.2006.04.002

    authors: Sermesant M,Moireau P,Camara O,Sainte-Marie J,Andriantsimiavona R,Cimrman R,Hill DL,Chapelle D,Razavi R

    更新日期:2006-08-01 00:00:00

  • Ω-Net (Omega-Net): Fully automatic, multi-view cardiac MR detection, orientation, and segmentation with deep neural networks.

    abstract::Pixelwise segmentation of the left ventricular (LV) myocardium and the four cardiac chambers in 2-D steady state free precession (SSFP) cine sequences is an essential preprocessing step for a wide range of analyses. Variability in contrast, appearance, orientation, and placement of the heart between patients, clinical...

    journal_title:Medical image analysis

    pub_type: 杂志文章

    doi:10.1016/j.media.2018.05.008

    authors: Vigneault DM,Xie W,Ho CY,Bluemke DA,Noble JA

    更新日期:2018-08-01 00:00:00

  • Respiratory motion models: a review.

    abstract::The problem of respiratory motion has proved a serious obstacle in developing techniques to acquire images or guide interventions in abdominal and thoracic organs. Motion models offer a possible solution to these problems, and as a result the field of respiratory motion modelling has become an active one over the past...

    journal_title:Medical image analysis

    pub_type: 杂志文章,评审

    doi:10.1016/j.media.2012.09.005

    authors: McClelland JR,Hawkes DJ,Schaeffter T,King AP

    更新日期:2013-01-01 00:00:00

  • Personalized mitral valve closure computation and uncertainty analysis from 3D echocardiography.

    abstract::Intervention planning is essential for successful Mitral Valve (MV) repair procedures. Finite-element models (FEM) of the MV could be used to achieve this goal, but the translation to the clinical domain is challenging. Many input parameters for the FEM models, such as tissue properties, are not known. In addition, on...

    journal_title:Medical image analysis

    pub_type: 杂志文章

    doi:10.1016/j.media.2016.03.011

    authors: Grbic S,Easley TF,Mansi T,Bloodworth CH,Pierce EL,Voigt I,Neumann D,Krebs J,Yuh DD,Jensen MO,Comaniciu D,Yoganathan AP

    更新日期:2017-01-01 00:00:00

  • Multimodal image registration using floating regressors in the joint intensity scatter plot.

    abstract::This paper presents a new approach for multimodal medical image registration and compares it to normalized mutual information (NMI) and the correlation ratio (CR). Like NMI and CR, the new method's measure of registration quality is based on the distribution of points in the joint intensity scatter plot (JISP); compac...

    journal_title:Medical image analysis

    pub_type: 杂志文章

    doi:10.1016/j.media.2007.12.002

    authors: Orchard J

    更新日期:2008-08-01 00:00:00

  • RMDL: Recalibrated multi-instance deep learning for whole slide gastric image classification.

    abstract::The whole slide histopathology images (WSIs) play a critical role in gastric cancer diagnosis. However, due to the large scale of WSIs and various sizes of the abnormal area, how to select informative regions and analyze them are quite challenging during the automatic diagnosis process. The multi-instance learning bas...

    journal_title:Medical image analysis

    pub_type: 杂志文章

    doi:10.1016/j.media.2019.101549

    authors: Wang S,Zhu Y,Yu L,Chen H,Lin H,Wan X,Fan X,Heng PA

    更新日期:2019-12-01 00:00:00

  • Evaluation of algorithms for Multi-Modality Whole Heart Segmentation: An open-access grand challenge.

    abstract::Knowledge of whole heart anatomy is a prerequisite for many clinical applications. Whole heart segmentation (WHS), which delineates substructures of the heart, can be very valuable for modeling and analysis of the anatomy and functions of the heart. However, automating this segmentation can be challenging due to the l...

    journal_title:Medical image analysis

    pub_type: 杂志文章

    doi:10.1016/j.media.2019.101537

    authors: Zhuang X,Li L,Payer C,Štern D,Urschler M,Heinrich MP,Oster J,Wang C,Smedby Ö,Bian C,Yang X,Heng PA,Mortazi A,Bagci U,Yang G,Sun C,Galisot G,Ramel JY,Brouard T,Tong Q,Si W,Liao X,Zeng G,Shi Z,Zheng G,Wang

    更新日期:2019-12-01 00:00:00

  • A novel deformation method for fast simulation of biological tissue formed by fibers and fluid.

    abstract::This paper presents a new approach to the simulation of soft tissues deformation suitable for real time computation, particularly intriguing for medical applications. The approach implements a quasi-static solution for elastic global deformations of objects filled with fluid and fibers, which can be a good approximati...

    journal_title:Medical image analysis

    pub_type: 杂志文章

    doi:10.1016/j.media.2012.04.002

    authors: Costa IF

    更新日期:2012-07-01 00:00:00

  • Sequential conditional reinforcement learning for simultaneous vertebral body detection and segmentation with modeling the spine anatomy.

    abstract::Accurate vertebral body (VB) detection and segmentation are critical for spine disease identification and diagnosis. Existing automatic VB detection and segmentation methods may cause false-positive results to the background tissue or inaccurate results to the desirable VB. Because they usually cannot take both the gl...

    journal_title:Medical image analysis

    pub_type: 杂志文章

    doi:10.1016/j.media.2020.101861

    authors: Zhang D,Chen B,Li S

    更新日期:2021-01-01 00:00:00

  • Nonlinear multiscale regularisation in MR elastography: Towards fine feature mapping.

    abstract::Fine-featured elastograms may provide additional information of radiological interest in the context of in vivo elastography. Here a new image processing pipeline called ESP (Elastography Software Pipeline) is developed to create Magnetic Resonance Elastography (MRE) maps of viscoelastic parameters (complex modulus ma...

    journal_title:Medical image analysis

    pub_type: 杂志文章

    doi:10.1016/j.media.2016.05.012

    authors: Barnhill E,Hollis L,Sack I,Braun J,Hoskins PR,Pankaj P,Brown C,van Beek EJR,Roberts N

    更新日期:2017-01-01 00:00:00

  • Discriminant snakes for 3D reconstruction of anatomical organs.

    abstract::In this work a new statistic deformable model for 3D segmentation of anatomical organs in medical images is proposed. A statistic discriminant snake performs a supervised learning of the object boundary in an image slice to segment the next slice of the image sequence. Each part of the object boundary is projected in ...

    journal_title:Medical image analysis

    pub_type: 杂志文章

    doi:10.1016/s1361-8415(03)00014-8

    authors: Pardo XM,Radeva P,Cabello D

    更新日期:2003-09-01 00:00:00

  • Neighborhood resolved fiber orientation distributions (NRFOD) in automatic labeling of white matter fiber pathways.

    abstract::Accurate digital representation of major white matter bundles in the brain is an important goal in neuroscience image computing since the representations can be used for surgical planning, intra-patient longitudinal analysis and inter-subject population connectivity studies. Reconstructing desired fiber bundles genera...

    journal_title:Medical image analysis

    pub_type: 杂志文章

    doi:10.1016/j.media.2018.02.008

    authors: Ugurlu D,Firat Z,Türe U,Unal G

    更新日期:2018-05-01 00:00:00

  • An efficient Riemannian statistical shape model using differential coordinates: With application to the classification of data from the Osteoarthritis Initiative.

    abstract::We propose a novel Riemannian framework for statistical analysis of shapes that is able to account for the nonlinearity in shape variation. By adopting a physical perspective, we introduce a differential representation that puts the local geometric variability into focus. We model these differential coordinates as ele...

    journal_title:Medical image analysis

    pub_type: 杂志文章

    doi:10.1016/j.media.2017.09.004

    authors: von Tycowicz C,Ambellan F,Mukhopadhyay A,Zachow S

    更新日期:2018-01-01 00:00:00

  • Predicting the progression of mild cognitive impairment using machine learning: A systematic, quantitative and critical review.

    abstract::We performed a systematic review of studies focusing on the automatic prediction of the progression of mild cognitive impairment to Alzheimer's disease (AD) dementia, and a quantitative analysis of the methodological choices impacting performance. This review included 172 articles, from which 234 experiments were extr...

    journal_title:Medical image analysis

    pub_type: 杂志文章

    doi:10.1016/j.media.2020.101848

    authors: Ansart M,Epelbaum S,Bassignana G,Bône A,Bottani S,Cattai T,Couronné R,Faouzi J,Koval I,Louis M,Thibeau-Sutre E,Wen J,Wild A,Burgos N,Dormont D,Colliot O,Durrleman S

    更新日期:2021-01-01 00:00:00

  • Segmentation of carpal bones from CT images using skeletally coupled deformable models.

    abstract::The in vivo investigation of joint kinematics in normal and injured wrist requires the segmentation of carpal bones from 3D (CT) images, and their registration over time. The non-uniformity of bone tissue, ranging from dense cortical bone to textured spongy bone, the irregular shape of closely packed carpal bones, sma...

    journal_title:Medical image analysis

    pub_type: 杂志文章

    doi:10.1016/s1361-8415(02)00065-8

    authors: Sebastian TB,Tek H,Crisco JJ,Kimia BB

    更新日期:2003-03-01 00:00:00

  • Automated comprehensive Adolescent Idiopathic Scoliosis assessment using MVC-Net.

    abstract::Automated quantitative estimation of spinal curvature is an important task for the ongoing evaluation and treatment planning of Adolescent Idiopathic Scoliosis (AIS). It solves the widely accepted disadvantage of manual Cobb angle measurement (time-consuming and unreliable) which is currently the gold standard for AIS...

    journal_title:Medical image analysis

    pub_type: 杂志文章

    doi:10.1016/j.media.2018.05.005

    authors: Wu H,Bailey C,Rasoulinejad P,Li S

    更新日期:2018-08-01 00:00:00

  • Improvement of fully automated airway segmentation on volumetric computed tomographic images using a 2.5 dimensional convolutional neural net.

    abstract::We propose a novel airway segmentation method in volumetric chest computed tomography (CT) and evaluate its performance on multiple datasets. The segmentation is performed voxel-by-voxel by a 2.5D convolutional neural net (2.5D CNN) trained in a supervised manner. To enhance the accuracy of the segmented airway tree, ...

    journal_title:Medical image analysis

    pub_type: 杂志文章

    doi:10.1016/j.media.2018.10.006

    authors: Yun J,Park J,Yu D,Yi J,Lee M,Park HJ,Lee JG,Seo JB,Kim N

    更新日期:2019-01-01 00:00:00

  • An information theoretic approach for non-rigid image registration using voxel class probabilities.

    abstract::We propose two information theoretic similarity measures that allow to incorporate tissue class information in non-rigid image registration. The first measure assumes that tissue class probabilities have been assigned to each of the images to be registered by prior segmentation of both of them. One image is then non-r...

    journal_title:Medical image analysis

    pub_type: 杂志文章

    doi:10.1016/j.media.2005.03.004

    authors: D'Agostino E,Maes F,Vandermeulen D,Suetens P

    更新日期:2006-06-01 00:00:00

  • Integrating segmentation methods from the Insight Toolkit into a visualization application.

    abstract::The Insight Toolkit (ITK) initiative from the National Library of Medicine has provided a suite of state-of-the-art segmentation and registration algorithms ideally suited to volume visualization and analysis. A volume visualization application that effectively utilizes these algorithms provides many benefits: it allo...

    journal_title:Medical image analysis

    pub_type: 杂志文章

    doi:10.1016/j.media.2005.04.009

    authors: Martin K,Ibáñez L,Avila L,Barré S,Kaspersen JH

    更新日期:2005-12-01 00:00:00

  • Shape regression machine and efficient segmentation of left ventricle endocardium from 2D B-mode echocardiogram.

    abstract::We present a machine learning approach called shape regression machine (SRM) for efficient segmentation of an anatomic structure that exhibits a deformable shape in a medical image, e.g., left ventricle endocardial wall in an echocardiogram. The SRM achieves efficient segmentation via statistical learning of the inter...

    journal_title:Medical image analysis

    pub_type: 杂志文章

    doi:10.1016/j.media.2010.04.002

    authors: Zhou SK

    更新日期:2010-08-01 00:00:00

  • Towards cross-modal organ translation and segmentation: A cycle- and shape-consistent generative adversarial network.

    abstract::Synthesized medical images have several important applications. For instance, they can be used as an intermedium in cross-modality image registration or used as augmented training samples to boost the generalization capability of a classifier. In this work, we propose a generic cross-modality synthesis approach with t...

    journal_title:Medical image analysis

    pub_type: 杂志文章

    doi:10.1016/j.media.2018.12.002

    authors: Cai J,Zhang Z,Cui L,Zheng Y,Yang L

    更新日期:2019-02-01 00:00:00