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 *

166 related articles for article (PubMed ID: 31698572)

  • 1. Skeletal bone age assessments for young children based on regression convolutional neural networks.
    Hao PY; Chokuwa S; Xie XH; Wu FL; Wu J; Bai C
    Math Biosci Eng; 2019 Jul; 16(6):6454-6466. PubMed ID: 31698572
    [TBL] [Abstract][Full Text] [Related]  

  • 2. Bone age assessment in young children using automatic carpal bone feature extraction and support vector regression.
    Somkantha K; Theera-Umpon N; Auephanwiriyakul S
    J Digit Imaging; 2011 Dec; 24(6):1044-58. PubMed ID: 21347746
    [TBL] [Abstract][Full Text] [Related]  

  • 3. Carpal Bone Segmentation Using Fully Convolutional Neural Network.
    Meng LK; Khalil A; Ahmad Nizar MH; Nisham MK; Pingguan-Murphy B; Hum YC; Mohamad Salim MI; Lai KW
    Curr Med Imaging Rev; 2019; 15(10):983-989. PubMed ID: 32008525
    [TBL] [Abstract][Full Text] [Related]  

  • 4. Automatic bone age assessment based on intelligent algorithms and comparison with TW3 method.
    Liu J; Qi J; Liu Z; Ning Q; Luo X
    Comput Med Imaging Graph; 2008 Dec; 32(8):678-84. PubMed ID: 18835130
    [TBL] [Abstract][Full Text] [Related]  

  • 5. MABAL: a Novel Deep-Learning Architecture for Machine-Assisted Bone Age Labeling.
    Mutasa S; Chang PD; Ruzal-Shapiro C; Ayyala R
    J Digit Imaging; 2018 Aug; 31(4):513-519. PubMed ID: 29404850
    [TBL] [Abstract][Full Text] [Related]  

  • 6. A Deep Automated Skeletal Bone Age Assessment Model with Heterogeneous Features Learning.
    Tong C; Liang B; Li J; Zheng Z
    J Med Syst; 2018 Nov; 42(12):249. PubMed ID: 30390162
    [TBL] [Abstract][Full Text] [Related]  

  • 7. Automatic analysis of hand radiographs for the assessment of skeletal age: a subsymbolic approach.
    Rucci M; Coppini G; Nicoletti I; Cheli D; Valli G
    Comput Biomed Res; 1995 Jun; 28(3):239-56. PubMed ID: 7554858
    [TBL] [Abstract][Full Text] [Related]  

  • 8. Automated bone age assessment: motivation, taxonomies, and challenges.
    Mansourvar M; Ismail MA; Herawan T; Raj RG; Kareem SA; Nasaruddin FH
    Comput Math Methods Med; 2013; 2013():391626. PubMed ID: 24454534
    [TBL] [Abstract][Full Text] [Related]  

  • 9. Regression Convolutional Neural Network for Automated Pediatric Bone Age Assessment From Hand Radiograph.
    Ren X; Li T; Yang X; Wang S; Ahmad S; Xiang L; Stone SR; Li L; Zhan Y; Shen D; Wang Q
    IEEE J Biomed Health Inform; 2019 Sep; 23(5):2030-2038. PubMed ID: 30346295
    [TBL] [Abstract][Full Text] [Related]  

  • 10. Automatic bone age assessment for young children from newborn to 7-year-old using carpal bones.
    Zhang A; Gertych A; Liu BJ
    Comput Med Imaging Graph; 2007; 31(4-5):299-310. PubMed ID: 17369018
    [TBL] [Abstract][Full Text] [Related]  

  • 11. Computer-assisted bone age assessment: image preprocessing and epiphyseal/metaphyseal ROI extraction.
    Pietka E; Gertych A; Pospiech S; Cao F; Huang HK; Gilsanz V
    IEEE Trans Med Imaging; 2001 Aug; 20(8):715-29. PubMed ID: 11513023
    [TBL] [Abstract][Full Text] [Related]  

  • 12. Computer-assisted bone age assessment based on features automatically extracted from a hand radiograph.
    Pietka E
    Comput Med Imaging Graph; 1995; 19(3):251-9. PubMed ID: 7641169
    [TBL] [Abstract][Full Text] [Related]  

  • 13. Bone age determination using only the index finger: a novel approach using a convolutional neural network compared with human radiologists.
    Reddy NE; Rayan JC; Annapragada AV; Mahmood NF; Scheslinger AE; Zhang W; Kan JH
    Pediatr Radiol; 2020 Apr; 50(4):516-523. PubMed ID: 31863193
    [TBL] [Abstract][Full Text] [Related]  

  • 14. Segmenting radiographs of the hand and wrist.
    Manos GK; Cairns AY; Rickets IW; Sinclair D
    Comput Methods Programs Biomed; 1994 Jun; 43(3-4):227-37. PubMed ID: 7956164
    [TBL] [Abstract][Full Text] [Related]  

  • 15. Bone age estimation based on phalanx information with fuzzy constrain of carpals.
    Hsieh CW; Jong TL; Tiu CM
    Med Biol Eng Comput; 2007 Mar; 45(3):283-95. PubMed ID: 17242901
    [TBL] [Abstract][Full Text] [Related]  

  • 16. Incorporated region detection and classification using deep convolutional networks for bone age assessment.
    Bui TD; Lee JJ; Shin J
    Artif Intell Med; 2019 Jun; 97():1-8. PubMed ID: 31202395
    [TBL] [Abstract][Full Text] [Related]  

  • 17. Fully Automated Deep Learning System for Bone Age Assessment.
    Lee H; Tajmir S; Lee J; Zissen M; Yeshiwas BA; Alkasab TK; Choy G; Do S
    J Digit Imaging; 2017 Aug; 30(4):427-441. PubMed ID: 28275919
    [TBL] [Abstract][Full Text] [Related]  

  • 18. Skeletal age determination in young children: analysis of three regions of the hand/wrist film.
    Carpenter CT; Lester EL
    J Pediatr Orthop; 1993; 13(1):76-9. PubMed ID: 8416359
    [TBL] [Abstract][Full Text] [Related]  

  • 19. Traditional and New Methods of Bone Age Assessment-An Overview.
    Prokop-Piotrkowska M; Marszałek-Dziuba K; Moszczyńska E; Szalecki M; Jurkiewicz E
    J Clin Res Pediatr Endocrinol; 2021 Aug; 13(3):251-262. PubMed ID: 33099993
    [TBL] [Abstract][Full Text] [Related]  

  • 20. Computer automated approach to the extraction of epiphyseal regions in hand radiographs.
    Pietka BE; Pośpiech S; Gertych A; Cao F; Huang HK; Gilsanz V
    J Digit Imaging; 2001 Dec; 14(4):165-72. PubMed ID: 11894888
    [TBL] [Abstract][Full Text] [Related]  

    [Next]    [New Search]
    of 9.