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 *

149 related articles for article (PubMed ID: 7488656)

  • 1. Differentiation between nodules and end-on vessels using a convolution neural network architecture.
    Lin JS; Hasegawa A; Freedman MT; Mun SK
    J Digit Imaging; 1995 Aug; 8(3):132-41. PubMed ID: 7488656
    [TBL] [Abstract][Full Text] [Related]  

  • 2. Reduction of false positives in computerized detection of lung nodules in chest radiographs using artificial neural networks, discriminant analysis, and a rule-based scheme.
    Wu YC; Doi K; Giger ML; Metz CE; Zhang W
    J Digit Imaging; 1994 Nov; 7(4):196-207. PubMed ID: 7858017
    [TBL] [Abstract][Full Text] [Related]  

  • 3. Computer-aided detection of mammographic microcalcifications: pattern recognition with an artificial neural network.
    Chan HP; Lo SC; Sahiner B; Lam KL; Helvie MA
    Med Phys; 1995 Oct; 22(10):1555-67. PubMed ID: 8551980
    [TBL] [Abstract][Full Text] [Related]  

  • 4. [Application of a computer-aided detection (CAD) system to digitalized mammograms for identifying microcalcifications].
    Bazzocchi M; Facecchia I; Zuiani C; Londero V; Smania S; Bottigli U; Delogu P
    Radiol Med; 2001 May; 101(5):334-40. PubMed ID: 11438784
    [TBL] [Abstract][Full Text] [Related]  

  • 5. Reduction of false positives in lung nodule detection using a two-level neural classification.
    Lin JS; Lo SB; Hasegawa A; Freedman MT; Mun SK
    IEEE Trans Med Imaging; 1996; 15(2):206-17. PubMed ID: 18215903
    [TBL] [Abstract][Full Text] [Related]  

  • 6. Selection of an optimal neural network architecture for computer-aided detection of microcalcifications--comparison of automated optimization techniques.
    Gurcan MN; Sahiner B; Chan HP; Hadjiiski L; Petrick N
    Med Phys; 2001 Sep; 28(9):1937-48. PubMed ID: 11585225
    [TBL] [Abstract][Full Text] [Related]  

  • 7. Classification of microcalcifications in radiographs of pathologic specimens for the diagnosis of breast cancer.
    Wu YC; Freedman MT; Hasegawa A; Zuurbier RA; Lo SC; Mun SK
    Acad Radiol; 1995 Mar; 2(3):199-204. PubMed ID: 9419548
    [TBL] [Abstract][Full Text] [Related]  

  • 8. Computer aided detection of clusters of microcalcifications on full field digital mammograms.
    Ge J; Sahiner B; Hadjiiski LM; Chan HP; Wei J; Helvie MA; Zhou C
    Med Phys; 2006 Aug; 33(8):2975-88. PubMed ID: 16964876
    [TBL] [Abstract][Full Text] [Related]  

  • 9. Computerized detection of pulmonary nodules in chest radiographs based on morphological features and wavelet snake model.
    Keserci B; Yoshida H
    Med Image Anal; 2002 Dec; 6(4):431-47. PubMed ID: 12494950
    [TBL] [Abstract][Full Text] [Related]  

  • 10. The use of an interactive software program for quantitative characterization of microcalcifications on digitized film-screen mammograms.
    Leichter I; Lederman R; Bamberger P; Novak B; Fields S; Buchbinder SS
    Invest Radiol; 1999 Jun; 34(6):394-400. PubMed ID: 10353031
    [TBL] [Abstract][Full Text] [Related]  

  • 11. Computerized analysis of abnormal asymmetry in digital chest radiographs: evaluation of potential utility.
    Armato SG; Giger ML; MacMahon H
    J Digit Imaging; 1999 Feb; 12(1):34-42. PubMed ID: 10036666
    [TBL] [Abstract][Full Text] [Related]  

  • 12. Categorical variables, interactions and generalized additive models. Applications in computer-aided diagnosis systems.
    Lado MJ; Cadarso-Suárez C; Roca-Pardiñas J; Tahoces PG
    Comput Biol Med; 2008 Apr; 38(4):475-83. PubMed ID: 18328470
    [TBL] [Abstract][Full Text] [Related]  

  • 13. Detection of lung nodules in digital chest radiographs using artificial neural networks: a pilot study.
    Wu YC; Doi K; Giger ML
    J Digit Imaging; 1995 May; 8(2):88-94. PubMed ID: 7612706
    [TBL] [Abstract][Full Text] [Related]  

  • 14. Small lung nodules detection based on local variance analysis and probabilistic neural network.
    Woźniak M; Połap D; Capizzi G; Sciuto GL; Kośmider L; Frankiewicz K
    Comput Methods Programs Biomed; 2018 Jul; 161():173-180. PubMed ID: 29852959
    [TBL] [Abstract][Full Text] [Related]  

  • 15. Computer-aided diagnostic scheme for the detection of lung nodules on chest radiographs: localized search method based on anatomical classification.
    Shiraishi J; Li Q; Suzuki K; Engelmann R; Doi K
    Med Phys; 2006 Jul; 33(7):2642-53. PubMed ID: 16898468
    [TBL] [Abstract][Full Text] [Related]  

  • 16. Multi-domain features for reducing false positives in automated detection of clustered microcalcifications in digital breast tomosynthesis.
    Zhang F; Wu S; Zhang C; Chen Q; Yang X; Jiang K; Zheng J
    Med Phys; 2019 Mar; 46(3):1300-1308. PubMed ID: 30661242
    [TBL] [Abstract][Full Text] [Related]  

  • 17. Optimal neural network architecture selection: improvement in computerized detection of microcalcifications.
    Gurcan MN; Chan HP; Sahiner B; Hadjiiski L; Petrick N; Helvie MA
    Acad Radiol; 2002 Apr; 9(4):420-9. PubMed ID: 11942656
    [TBL] [Abstract][Full Text] [Related]  

  • 18. Computer-aided diagnosis of endobronchial ultrasound images using convolutional neural network.
    Chen CH; Lee YW; Huang YS; Lan WR; Chang RF; Tu CY; Chen CY; Liao WC
    Comput Methods Programs Biomed; 2019 Aug; 177():175-182. PubMed ID: 31319946
    [TBL] [Abstract][Full Text] [Related]  

  • 19. Computer-aided detection of lung nodules: false positive reduction using a 3D gradient field method and 3D ellipsoid fitting.
    Ge Z; Sahiner B; Chan HP; Hadjiiski LM; Cascade PN; Bogot N; Kazerooni EA; Wei J; Zhou C
    Med Phys; 2005 Aug; 32(8):2443-54. PubMed ID: 16193773
    [TBL] [Abstract][Full Text] [Related]  

  • 20. A novel computer-aided lung nodule detection system for CT images.
    Tan M; Deklerck R; Jansen B; Bister M; Cornelis J
    Med Phys; 2011 Oct; 38(10):5630-45. PubMed ID: 21992380
    [TBL] [Abstract][Full Text] [Related]  

    [Next]    [New Search]
    of 8.