91 related articles for article (PubMed ID: 27436568)
1. Semi-automatic classification of textures in thoracic CT scans.
Kockelkorn TT; de Jong PA; Schaefer-Prokop CM; Wittenberg R; Tiehuis AM; Gietema HA; Grutters JC; Viergever MA; van Ginneken B
Phys Med Biol; 2016 Aug; 61(16):5906-24. PubMed ID: 27436568
[TBL] [Abstract][Full Text] [Related]
2. Interactive lung segmentation in abnormal human and animal chest CT scans.
Kockelkorn TT; Schaefer-Prokop CM; Bozovic G; Muñoz-Barrutia A; van Rikxoort EM; Brown MS; de Jong PA; Viergever MA; van Ginneken B
Med Phys; 2014 Aug; 41(8):081915. PubMed ID: 25086546
[TBL] [Abstract][Full Text] [Related]
3. Computerized detection of diffuse lung disease in MDCT: the usefulness of statistical texture features.
Wang J; Li F; Doi K; Li Q
Phys Med Biol; 2009 Nov; 54(22):6881-99. PubMed ID: 19864701
[TBL] [Abstract][Full Text] [Related]
4. High resolution multidetector CT-aided tissue analysis and quantification of lung fibrosis.
Zavaletta VA; Bartholmai BJ; Robb RA
Acad Radiol; 2007 Jul; 14(7):772-87. PubMed ID: 17574128
[TBL] [Abstract][Full Text] [Related]
5. Validation of simplified dosimetry approaches in ⁸⁹Zr-PET/CT: the use of manual versus semi-automatic delineation methods to estimate organ absorbed doses.
Makris NE; van Velden FH; Huisman MC; Menke CW; Lammertsma AA; Boellaard R
Med Phys; 2014 Oct; 41(10):102503. PubMed ID: 25281978
[TBL] [Abstract][Full Text] [Related]
6. Automatic segmentation and recognition of lungs and lesion from CT scans of thorax.
Kakar M; Olsen DR
Comput Med Imaging Graph; 2009 Jan; 33(1):72-82. PubMed ID: 19059759
[TBL] [Abstract][Full Text] [Related]
7. Automated lung volumetry from routine thoracic CT scans: how reliable is the result?
Haas M; Hamm B; Niehues SM
Acad Radiol; 2014 May; 21(5):633-8. PubMed ID: 24703476
[TBL] [Abstract][Full Text] [Related]
8. Toward automated segmentation of the pathological lung in CT.
Sluimer I; Prokop M; van Ginneken B
IEEE Trans Med Imaging; 2005 Aug; 24(8):1025-38. PubMed ID: 16092334
[TBL] [Abstract][Full Text] [Related]
9. Robustness-Driven Feature Selection in Classification of Fibrotic Interstitial Lung Disease Patterns in Computed Tomography Using 3D Texture Features.
Chong DY; Kim HJ; Lo P; Young S; McNitt-Gray MF; Abtin F; Goldin JG; Brown MS
IEEE Trans Med Imaging; 2016 Jan; 35(1):144-57. PubMed ID: 26208309
[TBL] [Abstract][Full Text] [Related]
10. A support vector machine classifier reduces interscanner variation in the HRCT classification of regional disease pattern in diffuse lung disease: comparison to a Bayesian classifier.
Chang Y; Lim J; Kim N; Seo JB; Lynch DA
Med Phys; 2013 May; 40(5):051912. PubMed ID: 23635282
[TBL] [Abstract][Full Text] [Related]
11. Automated aortic calcium scoring on low-dose chest computed tomography.
Isgum I; Rutten A; Prokop M; Staring M; Klein S; Pluim JP; Viergever MA; van Ginneken B
Med Phys; 2010 Feb; 37(2):714-23. PubMed ID: 20229881
[TBL] [Abstract][Full Text] [Related]
12. Solid, part-solid, or non-solid?: classification of pulmonary nodules in low-dose chest computed tomography by a computer-aided diagnosis system.
Jacobs C; van Rikxoort EM; Scholten ET; de Jong PA; Prokop M; Schaefer-Prokop C; van Ginneken B
Invest Radiol; 2015 Mar; 50(3):168-73. PubMed ID: 25478740
[TBL] [Abstract][Full Text] [Related]
13. Automatic coronary calcium scoring in low-dose chest computed tomography.
Isgum I; Prokop M; Niemeijer M; Viergever MA; van Ginneken B
IEEE Trans Med Imaging; 2012 Dec; 31(12):2322-34. PubMed ID: 22961297
[TBL] [Abstract][Full Text] [Related]
14. Automated tube voltage adaptation in combination with advanced modeled iterative reconstruction in thoracoabdominal third-generation 192-slice dual-source computed tomography: effects on image quality and radiation dose.
Scholtz JE; Wichmann JL; Hüsers K; Beeres M; Nour-Eldin NE; Frellesen C; Vogl TJ; Lehnert T
Acad Radiol; 2015 Sep; 22(9):1081-7. PubMed ID: 26163706
[TBL] [Abstract][Full Text] [Related]
15. Semi-automatic software increases CT measurement accuracy but not response classification of colorectal liver metastases after chemotherapy.
van Kessel CS; van Leeuwen MS; Witteveen PO; Kwee TC; Verkooijen HM; van Hillegersberg R
Eur J Radiol; 2012 Oct; 81(10):2543-9. PubMed ID: 22264447
[TBL] [Abstract][Full Text] [Related]
16. Automatic segmentation of thoracic and pelvic CT images for radiotherapy planning using implicit anatomic knowledge and organ-specific segmentation strategies.
Haas B; Coradi T; Scholz M; Kunz P; Huber M; Oppitz U; André L; Lengkeek V; Huyskens D; van Esch A; Reddick R
Phys Med Biol; 2008 Mar; 53(6):1751-71. PubMed ID: 18367801
[TBL] [Abstract][Full Text] [Related]
17. Ultra-Low-Dose CT of the Thorax Using Iterative Reconstruction: Evaluation of Image Quality and Radiation Dose Reduction.
Kim Y; Kim YK; Lee BE; Lee SJ; Ryu YJ; Lee JH; Chang JH
AJR Am J Roentgenol; 2015 Jun; 204(6):1197-202. PubMed ID: 26001228
[TBL] [Abstract][Full Text] [Related]
18. Measurement of mesothelioma on thoracic CT scans: a comparison of manual and computer-assisted techniques.
Armato SG; Oxnard GR; MacMahon H; Vogelzang NJ; Kindler HL; Kocherginsky M; Starkey A
Med Phys; 2004 May; 31(5):1105-15. PubMed ID: 15191298
[TBL] [Abstract][Full Text] [Related]
19. Computer-aided classification of interstitial lung diseases via MDCT: 3D adaptive multiple feature method (3D AMFM).
Xu Y; van Beek EJ; Hwanjo Y; Guo J; McLennan G; Hoffman EA
Acad Radiol; 2006 Aug; 13(8):969-78. PubMed ID: 16843849
[TBL] [Abstract][Full Text] [Related]
20. MDCT-based 3-D texture classification of emphysema and early smoking related lung pathologies.
Xu Y; Sonka M; McLennan G; Guo J; Hoffman EA
IEEE Trans Med Imaging; 2006 Apr; 25(4):464-75. PubMed ID: 16608061
[TBL] [Abstract][Full Text] [Related]
[Next] [New Search]
