These tools will no longer be maintained as of December 31, 2024. Archived website can be found here. PubMed4Hh GitHub repository can be found here. Contact NLM Customer Service if you have questions.


BIOMARKERS

Molecular Biopsy of Human Tumors

- a resource for Precision Medicine *

146 related articles for article (PubMed ID: 9725142)

  • 21. A computerized method for automated identification of erect posteroanterior and supine anteroposterior chest radiographs.
    Kao EF; Lin WC; Hsu JS; Chou MC; Jaw TS; Liu GC
    Phys Med Biol; 2011 Dec; 56(24):7737-53. PubMed ID: 22094308
    [TBL] [Abstract][Full Text] [Related]  

  • 22. Automatic detection of lesions in lung regions that are segmented using spatial relations.
    Hassen DB; Taleb H
    Clin Imaging; 2013; 37(3):498-503. PubMed ID: 23601768
    [TBL] [Abstract][Full Text] [Related]  

  • 23. Image feature analysis and computer-aided diagnosis in digital radiography: automated analysis of sizes of heart and lung in chest images.
    Nakamori N; Doi K; Sabeti V; MacMahon H
    Med Phys; 1990; 17(3):342-50. PubMed ID: 2143554
    [TBL] [Abstract][Full Text] [Related]  

  • 24. Image-processing technique for suppressing ribs in chest radiographs by means of massive training artificial neural network (MTANN).
    Suzuki K; Abe H; MacMahon H; Doi K
    IEEE Trans Med Imaging; 2006 Apr; 25(4):406-16. PubMed ID: 16608057
    [TBL] [Abstract][Full Text] [Related]  

  • 25. Computer-aided diagnosis for the detection and classification of lung cancers on chest radiographs ROC analysis of radiologists' performance.
    Shiraishi J; Abe H; Li F; Engelmann R; MacMahon H; Doi K
    Acad Radiol; 2006 Aug; 13(8):995-1003. PubMed ID: 16843852
    [TBL] [Abstract][Full Text] [Related]  

  • 26. False-positive reduction in computer-aided diagnostic scheme for detecting nodules in chest radiographs by means of massive training artificial neural network.
    Suzuki K; Shiraishi J; Abe H; MacMahon H; Doi K
    Acad Radiol; 2005 Feb; 12(2):191-201. PubMed ID: 15721596
    [TBL] [Abstract][Full Text] [Related]  

  • 27. Automated iterative neutrosophic lung segmentation for image analysis in thoracic computed tomography.
    Guo Y; Zhou C; Chan HP; Chughtai A; Wei J; Hadjiiski LM; Kazerooni EA
    Med Phys; 2013 Aug; 40(8):081912. PubMed ID: 23927326
    [TBL] [Abstract][Full Text] [Related]  

  • 28. [An automatic method segmenting lung regions from digital chest radiograph].
    Cao X; Jiang D; Zheng C
    Sheng Wu Yi Xue Gong Cheng Xue Za Zhi; 1998 Dec; 15(4):393-6. PubMed ID: 12552787
    [TBL] [Abstract][Full Text] [Related]  

  • 29. Segmentation and Image Analysis of Abnormal Lungs at CT: Current Approaches, Challenges, and Future Trends.
    Mansoor A; Bagci U; Foster B; Xu Z; Papadakis GZ; Folio LR; Udupa JK; Mollura DJ
    Radiographics; 2015; 35(4):1056-76. PubMed ID: 26172351
    [TBL] [Abstract][Full Text] [Related]  

  • 30. Temporal subtraction in chest radiography: automated assessment of registration accuracy.
    Armato SG; Doshi DJ; Engelmann R; Croteau CL; MacMahon H
    Med Phys; 2006 May; 33(5):1239-49. PubMed ID: 16752558
    [TBL] [Abstract][Full Text] [Related]  

  • 31. Evaluation of a real-time interactive pulmonary nodule analysis system on chest digital radiographic images: a prospective study.
    van Beek EJ; Mullan B; Thompson B
    Acad Radiol; 2008 May; 15(5):571-5. PubMed ID: 18423313
    [TBL] [Abstract][Full Text] [Related]  

  • 32. Quantitative computerized analysis of diffuse lung disease in high-resolution computed tomography.
    Uchiyama Y; Katsuragawa S; Abe H; Shiraishi J; Li F; Li Q; Zhang CT; Suzuki K; Doi K
    Med Phys; 2003 Sep; 30(9):2440-54. PubMed ID: 14528966
    [TBL] [Abstract][Full Text] [Related]  

  • 33. Unsupervised segmentation of lung fields in chest radiographs using multiresolution fractal feature vector and deformable models.
    Lee WL; Chang K; Hsieh KS
    Med Biol Eng Comput; 2016 Sep; 54(9):1409-22. PubMed ID: 26530048
    [TBL] [Abstract][Full Text] [Related]  

  • 34. A computer-aided diagnosis system for detection of lung nodules in chest radiographs with an evaluation on a public database.
    Schilham AM; van Ginneken B; Loog M
    Med Image Anal; 2006 Apr; 10(2):247-58. PubMed ID: 16293441
    [TBL] [Abstract][Full Text] [Related]  

  • 35. Computer-aided diagnosis of emphysema in COPD patients: neural-network-based analysis of lung shape in digital chest radiographs.
    Coppini G; Miniati M; Paterni M; Monti S; Ferdeghini EM
    Med Eng Phys; 2007 Jan; 29(1):76-86. PubMed ID: 16540362
    [TBL] [Abstract][Full Text] [Related]  

  • 36. An edge-region force guided active shape approach for automatic lung field detection in chest radiographs.
    Xu T; Mandal M; Long R; Cheng I; Basu A
    Comput Med Imaging Graph; 2012 Sep; 36(6):452-63. PubMed ID: 22608158
    [TBL] [Abstract][Full Text] [Related]  

  • 37. Image feature analysis and computer-aided diagnosis in digital radiography: detection and characterization of interstitial lung disease in digital chest radiographs.
    Katsuragawa S; Doi K; MacMahon H
    Med Phys; 1988; 15(3):311-9. PubMed ID: 3405134
    [TBL] [Abstract][Full Text] [Related]  

  • 38. Improved method for automatic identification of lung regions on chest radiographs.
    Li L; Zheng Y; Kallergi M; Clark RA
    Acad Radiol; 2001 Jul; 8(7):629-38. PubMed ID: 11450964
    [TBL] [Abstract][Full Text] [Related]  

  • 39. Computerized delineation and analysis of costophrenic angles in digital chest radiographs.
    Armato SG; Giger ML; MacMahon H
    Acad Radiol; 1998 May; 5(5):329-35. PubMed ID: 9597100
    [TBL] [Abstract][Full Text] [Related]  

  • 40. Computer-aided detection improves detection of pulmonary nodules in chest radiographs beyond the support by bone-suppressed images.
    Schalekamp S; van Ginneken B; Koedam E; Snoeren MM; Tiehuis AM; Wittenberg R; Karssemeijer N; Schaefer-Prokop CM
    Radiology; 2014 Jul; 272(1):252-61. PubMed ID: 24635675
    [TBL] [Abstract][Full Text] [Related]  

    [Previous]   [Next]    [New Search]
    of 8.