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Journal Abstract Search

652 related items for PubMed ID: 25601306

  • 21. An adaptive morphology based segmentation technique for lung nodule detection in thoracic CT image.
    Halder A, Chatterjee S, Dey D, Kole S, Munshi S.
    Comput Methods Programs Biomed; 2020 Dec; 197():105720. PubMed ID: 32877818
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  • 22. A pulmonary nodule view system for the Lung Image Database Consortium (LIDC).
    Lin H, Chen Z, Wang W.
    Acad Radiol; 2011 Sep; 18(9):1181-5. PubMed ID: 21652230
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  • 23. Content-Based Image Retrieval System for Pulmonary Nodules: Assisting Radiologists in Self-Learning and Diagnosis of Lung Cancer.
    Dhara AK, Mukhopadhyay S, Dutta A, Garg M, Khandelwal N.
    J Digit Imaging; 2017 Feb; 30(1):63-77. PubMed ID: 27678255
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  • 24. Robust semi-automatic segmentation of pulmonary subsolid nodules in chest computed tomography scans.
    Lassen BC, Jacobs C, Kuhnigk JM, van Ginneken B, van Rikxoort EM.
    Phys Med Biol; 2015 Feb 07; 60(3):1307-23. PubMed ID: 25591989
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  • 25. Soft computing approach to 3D lung nodule segmentation in CT.
    Badura P, Pietka E.
    Comput Biol Med; 2014 Oct 07; 53():230-43. PubMed ID: 25173811
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  • 26. Differential geometry-based techniques for characterization of boundary roughness of pulmonary nodules in CT images.
    Dhara AK, Mukhopadhyay S, Saha P, Garg M, Khandelwal N.
    Int J Comput Assist Radiol Surg; 2016 Mar 07; 11(3):337-49. PubMed ID: 26337440
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  • 27. 3D skeletonization feature based computer-aided detection system for pulmonary nodules in CT datasets.
    Zhang W, Wang X, Li X, Chen J.
    Comput Biol Med; 2018 Jan 01; 92():64-72. PubMed ID: 29154123
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  • 28. Robust explanation supervision for false positive reduction in pulmonary nodule detection.
    Zhao Q, Chang CW, Yang X, Zhao L.
    Med Phys; 2024 Mar 01; 51(3):1687-1701. PubMed ID: 38224306
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  • 29. Computer-Aided Diagnosis (CAD) of Pulmonary Nodule of Thoracic CT Image Using Transfer Learning.
    Zhang S, Sun F, Wang N, Zhang C, Yu Q, Zhang M, Babyn P, Zhong H.
    J Digit Imaging; 2019 Dec 01; 32(6):995-1007. PubMed ID: 31044393
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  • 30. BRISC-an open source pulmonary nodule image retrieval framework.
    Lam MO, Disney T, Raicu DS, Furst J, Channin DS.
    J Digit Imaging; 2007 Nov 01; 20 Suppl 1(Suppl 1):63-71. PubMed ID: 17701069
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  • 31. An integrated segmentation and shape-based classification scheme for distinguishing adenocarcinomas from granulomas on lung CT.
    Alilou M, Beig N, Orooji M, Rajiah P, Velcheti V, Rakshit S, Reddy N, Yang M, Jacono F, Gilkeson RC, Linden P, Madabhushi A.
    Med Phys; 2017 Jul 01; 44(7):3556-3569. PubMed ID: 28295386
    [Abstract] [Full Text] [Related]

  • 32. Potential lung nodules identification for characterization by variable multistep threshold and shape indices from CT images.
    Iqbal S, Iqbal K, Arif F, Shaukat A, Khanum A.
    Comput Math Methods Med; 2014 Jul 01; 2014():241647. PubMed ID: 25506388
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  • 33. Segmentation of pulmonary nodules in CT images based on 3D-UNET combined with three-dimensional conditional random field optimization.
    Wu W, Gao L, Duan H, Huang G, Ye X, Nie S.
    Med Phys; 2020 Sep 01; 47(9):4054-4063. PubMed ID: 32428969
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  • 34. Deep Deconvolutional Residual Network Based Automatic Lung Nodule Segmentation.
    Singadkar G, Mahajan A, Thakur M, Talbar S.
    J Digit Imaging; 2020 Jun 01; 33(3):678-684. PubMed ID: 32026218
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  • 35. Detection of pulmonary ground-glass opacity based on deep learning computer artificial intelligence.
    Ye W, Gu W, Guo X, Yi P, Meng Y, Han F, Yu L, Chen Y, Zhang G, Wang X.
    Biomed Eng Online; 2019 Jan 22; 18(1):6. PubMed ID: 30670024
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  • 36. The Lung Image Database Consortium (LIDC): an evaluation of radiologist variability in the identification of lung nodules on CT scans.
    Armato SG, McNitt-Gray MF, Reeves AP, Meyer CR, McLennan G, Aberle DR, Kazerooni EA, MacMahon H, van Beek EJ, Yankelevitz D, Hoffman EA, Henschke CI, Roberts RY, Brown MS, Engelmann RM, Pais RC, Piker CW, Qing D, Kocherginsky M, Croft BY, Clarke LP.
    Acad Radiol; 2007 Nov 22; 14(11):1409-21. PubMed ID: 17964464
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  • 37. Automated system for lung nodules classification based on wavelet feature descriptor and support vector machine.
    Madero Orozco H, Vergara Villegas OO, Cruz Sánchez VG, Ochoa Domínguez Hde J, Nandayapa Alfaro Mde J.
    Biomed Eng Online; 2015 Feb 12; 14():9. PubMed ID: 25888834
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  • 38. Toward Understanding the Size Dependence of Shape Features for Predicting Spiculation in Lung Nodules for Computer-Aided Diagnosis.
    Niehaus R, Raicu DS, Furst J, Armato S.
    J Digit Imaging; 2015 Dec 12; 28(6):704-17. PubMed ID: 25708891
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  • 39. Lung Nodule Detection in CT Images Using a Raw Patch-Based Convolutional Neural Network.
    Wang Q, Shen F, Shen L, Huang J, Sheng W.
    J Digit Imaging; 2019 Dec 12; 32(6):971-979. PubMed ID: 31062113
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  • 40. The Lung Image Database Consortium (LIDC) data collection process for nodule detection and annotation.
    McNitt-Gray MF, Armato SG, Meyer CR, Reeves AP, McLennan G, Pais RC, Freymann J, Brown MS, Engelmann RM, Bland PH, Laderach GE, Piker C, Guo J, Towfic Z, Qing DP, Yankelevitz DF, Aberle DR, van Beek EJ, MacMahon H, Kazerooni EA, Croft BY, Clarke LP.
    Acad Radiol; 2007 Dec 12; 14(12):1464-74. PubMed ID: 18035276
    [Abstract] [Full Text] [Related]

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