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 *

121 related articles for article (PubMed ID: 31728804)

  • 1. Generate Structured Radiology Report from CT Images Using Image Annotation Techniques: Preliminary Results with Liver CT.
    Loveymi S; Dezfoulian MH; Mansoorizadeh M
    J Digit Imaging; 2020 Apr; 33(2):375-390. PubMed ID: 31728804
    [TBL] [Abstract][Full Text] [Related]  

  • 2. Adapting content-based image retrieval techniques for the semantic annotation of medical images.
    Kumar A; Dyer S; Kim J; Li C; Leong PH; Fulham M; Feng D
    Comput Med Imaging Graph; 2016 Apr; 49():37-45. PubMed ID: 26890880
    [TBL] [Abstract][Full Text] [Related]  

  • 3. Computerized Prediction of Radiological Observations Based on Quantitative Feature Analysis: Initial Experience in Liver Lesions.
    Banerjee I; Beaulieu CF; Rubin DL
    J Digit Imaging; 2017 Aug; 30(4):506-518. PubMed ID: 28639186
    [TBL] [Abstract][Full Text] [Related]  

  • 4. On combining image-based and ontological semantic dissimilarities for medical image retrieval applications.
    Kurtz C; Depeursinge A; Napel S; Beaulieu CF; Rubin DL
    Med Image Anal; 2014 Oct; 18(7):1082-100. PubMed ID: 25036769
    [TBL] [Abstract][Full Text] [Related]  

  • 5. A hierarchical knowledge-based approach for retrieving similar medical images described with semantic annotations.
    Kurtz C; Beaulieu CF; Napel S; Rubin DL
    J Biomed Inform; 2014 Jun; 49():227-44. PubMed ID: 24632078
    [TBL] [Abstract][Full Text] [Related]  

  • 6. Automatic Generation of Structured Radiology Reports for Volumetric Computed Tomography Images Using Question-Specific Deep Feature Extraction and Learning.
    Loveymi S; Dezfoulian MH; Mansoorizadeh M
    J Med Signals Sens; 2021; 11(3):194-207. PubMed ID: 34466399
    [TBL] [Abstract][Full Text] [Related]  

  • 7. A fully automatic end-to-end method for content-based image retrieval of CT scans with similar liver lesion annotations.
    Spanier AB; Caplan N; Sosna J; Acar B; Joskowicz L
    Int J Comput Assist Radiol Surg; 2018 Jan; 13(1):165-174. PubMed ID: 29147954
    [TBL] [Abstract][Full Text] [Related]  

  • 8. Relevance feedback for enhancing content based image retrieval and automatic prediction of semantic image features: Application to bone tumor radiographs.
    Banerjee I; Kurtz C; Devorah AE; Do B; Rubin DL; Beaulieu CF
    J Biomed Inform; 2018 Aug; 84():123-135. PubMed ID: 29981490
    [TBL] [Abstract][Full Text] [Related]  

  • 9. Predicting visual semantic descriptive terms from radiological image data: preliminary results with liver lesions in CT.
    Depeursinge A; Kurtz C; Beaulieu C; Napel S; Rubin D
    IEEE Trans Med Imaging; 2014 Aug; 33(8):1669-76. PubMed ID: 24808406
    [TBL] [Abstract][Full Text] [Related]  

  • 10. Automatic annotation of radiological observations in liver CT images.
    Gimenez F; Xu J; Liu Y; Liu T; Beaulieu C; Rubin D; Napel S
    AMIA Annu Symp Proc; 2012; 2012():257-63. PubMed ID: 23304295
    [TBL] [Abstract][Full Text] [Related]  

  • 11. Computer-Aided Medical Image Annotation: Preliminary Results With Liver Lesions in CT.
    Marvasti NB; Yoruk E; Acar B
    IEEE J Biomed Health Inform; 2018 Sep; 22(5):1561-1570. PubMed ID: 29990179
    [TBL] [Abstract][Full Text] [Related]  

  • 12. Effective staging of fibrosis by the selected texture features of liver: Which one is better, CT or MR imaging?
    Zhang X; Gao X; Liu BJ; Ma K; Yan W; Liling L; Yuhong H; Fujita H
    Comput Med Imaging Graph; 2015 Dec; 46 Pt 2():227-36. PubMed ID: 26455963
    [TBL] [Abstract][Full Text] [Related]  

  • 13. Content-based histopathology image retrieval using a kernel-based semantic annotation framework.
    Caicedo JC; González FA; Romero E
    J Biomed Inform; 2011 Aug; 44(4):519-28. PubMed ID: 21296682
    [TBL] [Abstract][Full Text] [Related]  

  • 14. Advancing Semantic Interoperability of Image Annotations: Automated Conversion of Non-standard Image Annotations in a Commercial PACS to the Annotation and Image Markup.
    Swinburne NC; Mendelson D; Rubin DL
    J Digit Imaging; 2020 Feb; 33(1):49-53. PubMed ID: 30805778
    [TBL] [Abstract][Full Text] [Related]  

  • 15. A boosting framework for visuality-preserving distance metric learning and its application to medical image retrieval.
    Yang L; Jin R; Mummert L; Sukthankar R; Goode A; Zheng B; Hoi SC; Satyanarayanan M
    IEEE Trans Pattern Anal Mach Intell; 2010 Jan; 32(1):30-44. PubMed ID: 19926897
    [TBL] [Abstract][Full Text] [Related]  

  • 16. Explaining the black-box smoothly-A counterfactual approach.
    Singla S; Eslami M; Pollack B; Wallace S; Batmanghelich K
    Med Image Anal; 2023 Feb; 84():102721. PubMed ID: 36571975
    [TBL] [Abstract][Full Text] [Related]  

  • 17. Position tracking of moving liver lesion based on real-time registration between 2D ultrasound and 3D preoperative images.
    Weon C; Hyun Nam W; Lee D; Lee JY; Ra JB
    Med Phys; 2015 Jan; 42(1):335-47. PubMed ID: 25563273
    [TBL] [Abstract][Full Text] [Related]  

  • 18. AAR-LN-DQ: Automatic anatomy recognition based disease quantification in thoracic lymph node zones via FDG PET/CT images without Nodal Delineation.
    Xu G; Udupa JK; Tong Y; Odhner D; Cao H; Torigian DA
    Med Phys; 2020 Aug; 47(8):3467-3484. PubMed ID: 32418221
    [TBL] [Abstract][Full Text] [Related]  

  • 19. Automatic medical X-ray image classification using annotation.
    Zare MR; Mueen A; Seng WC
    J Digit Imaging; 2014 Feb; 27(1):77-89. PubMed ID: 24092327
    [TBL] [Abstract][Full Text] [Related]  

  • 20. Fully-automated functional region annotation of liver via a 2.5D class-aware deep neural network with spatial adaptation.
    Tian Y; Xue F; Lambo R; He J; An C; Xie Y; Cao H; Qin W
    Comput Methods Programs Biomed; 2021 Mar; 200():105818. PubMed ID: 33218708
    [TBL] [Abstract][Full Text] [Related]  

    [Next]    [New Search]
    of 7.